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Building Resiliency to Climate Change Through Wetland Management and Restoration

  • Kimberli J. PonzioEmail author
  • Todd Z. Osborne
  • Gillian T. Davies
  • Ben LePage
  • Pallaoor V. Sundareshwar
  • S. J. Miller
  • A. M. K. Bochnak
  • S. A. Phelps
  • M. Q. Guyette
  • K. M. Chowanski
  • L. A. Kunza
  • P. J. Pellechia
  • R. A. Gleason
  • C. Sandvik
Chapter
Part of the Ecological Studies book series (ECOLSTUD, volume 238)

Abstract

Never before has the resiliency of wetland ecosystems to climatic and anthropogenic stressors been more important or more recognized by those who study these unique ecosystems. The goal of this chapter is to discuss a variety of management and restoration approaches to building resiliency in wetlands that are subjected to changing conditions. We examine wetland responses to changing climatic and hydrologic conditions at multiple spatial (global to microscopic level) and temporal (100-million-year to 1-year) scales which informs our perspective on predicting future wetland responses to both anthropogenic and natural perturbations. Additionally, we introduce the utility of having advanced tools for monitoring changes at the biogeochemical scale, which is likely to be one of the first indicators of change to be detected. The case studies that we present enable us to learn techniques and approaches to address current and future stressors (natural and anthropogenic) on both coastal and inland wetland ecosystems and contain the common thread of carbon sequestration and biogeochemical cycling. We focus on the functional roles of wetlands in providing ecosystem services and how those ecosystem services are best protected, managed, and restored in light of a variety of stressors, such as global climate change, increased water use and demand, and land use changes. Wise-use approaches that enhance wetland biodiversity and resiliency to these changes and impacts are discussed, as are wetland-specific ecosystem services that provide enhanced water quality, water supply, flood protection, storm damage protection, pollution attenuation, and climate change resiliency for adjacent human communities.

Keywords

Wetlands Resiliency Carbon Climate change Polar wetlands Paleoecology Hydrology Subsidence Sea level rise Peat collapse Landward migration Biogeochemical function Phosphorus Ecosystem services Wetland restoration 

10.1 Introduction

Never before has the resiliency of wetland ecosystems to climatic and anthropogenic stressors been more important or more recognized by those who study these unique ecosystems. The goal of this chapter is to summarize and synthesize the content of a session at the 10th INTECOL International Wetlands Conference entitled “Building Resiliency to Changing Conditions in Wetland Management and Restoration Projects on Multiple Temporal and Spatial Scales.” With the following synopsis, we highlight a diversity of scientific approaches to addressing critical issues of climate change and anthropogenic influence on wetland systems. We provide an overview of five of the seven presentations, and all address resiliency in wetlands to changing climatic and hydrologic conditions.

We begin with a comprehensive global overview of wetlands in the carbon cycle and showcase opportunities and priorities for protecting existing wetland carbon stocks and the identification of hydrologic conditions that allow for climate change mitigation through carbon sequestration. We introduce the concept that wetlands have a disproportionately large role in carbon sequestration and long-term storage and that protecting and conserving existing wetlands, rather than restoring or creating new wetlands, may be the best way to protect carbon banks and other ecosystem services. We explore the reasons wetlands are particularly vulnerable to small changes in hydrology and how changes in climate have already impacted wetland ecosystems. We then examine the interaction between climate and wetlands through geologic time and discuss how increasing global temperatures are expected to change vegetation zonation in the polar regions, based on past “greenhouse” conditions.

This exercise gives us insight into the mechanism of evolutionary processes that may help us better predict what a “green Arctic” will look like. To illustrate the local effects of a global issue (climate change), we offer coastal and inland examples of how direct and indirect impacts, especially regarding hydrology, change the resiliency and functioning of these wetlands. In the first example, we discuss how sea level rise is impacting wetlands along Florida’s coasts. We investigate how observations of saltwater intrusion into coastal freshwater marshes of the Florida Everglades and coastal forests of Florida’s Gulf Coast can provide insight into ecosystem trajectories of vegetation communities. Additionally, we utilize observations of coastal development patterns to highlight the need for consideration of wetland expansion within urbanized landscapes.

In our second example, we present case studies in the St. Johns River floodplain in Central Florida that examine the impacts of water management on an inland, freshwater system. We consider how hydrology, as a major driving force in wetlands, changes ecosystem function and structure by changing plant distributions, water quality, carbon sequestration, and soil accretion and loss. We address how evaluating the response of wetlands that experience variable hydrologic conditions (unnatural draining or prolonged flooding) may help us to predict future impacts of expected water shortages and changing weather patterns as a result of climate change. Finally, to understand how ecosystems respond to natural or induced change (primarily land use changes, which could also be applied for assessing impacts from climate change), we offer the example of an integrated indicator of ecosystem function across a network of wetlands in the Prairie Pothole Region of the northern United States. The approach of comparative evaluation of P-forms and vegetation metrics, under varying land uses and restoration stages, is a novel perspective on functional status assessment in wetlands.

Overall, we examine wetland responses to changing climatic and hydrologic conditions at multiple spatial (global to microscopic level) and temporal (100-million year to 1-year) scales which informs our perspective on predicting future wetland responses to both anthropogenic and natural perturbations. Additionally, we introduce the utility of having advanced tools for monitoring changes at the biogeochemical scale, which is likely to be one of the first indicators of change to be detected. The case studies that we present enable us to learn techniques and approaches to address current and future stressors (natural and anthropogenic) on both coastal and inland wetland ecosystems and contain the common thread of carbon sequestration and biogeochemical cycling. We focus on the functional roles of wetlands in providing ecosystem services and how those ecosystem services are best protected, managed, and restored in light of a variety of stressors, such as global climate change, increased water use and demand, and land use changes. Wise-use approaches that enhance wetland biodiversity and resiliency to these changes and impacts are discussed, as are wetland-specific ecosystem services that provide enhanced water quality, water supply, flood protection, storm damage protection, pollution attenuation, and climate change resiliency for adjacent human communities.

10.2 Wetlands and Climate Change: Current Scientific Findings and Their Management Implications

  • G. T. Davies

10.2.1 Introduction

Smart and effective management of our communities and wetlands is informed by an understanding of how wetlands function in the global carbon cycle, how wetlands are being impacted by climate change, and how wetlands provide climate adaptation and resilient ecosystem services. This section of the chapter presents recent scientific findings about the role of wetlands relative to climate change and implications for policy and management.

10.2.2 Climate Condition

Researchers report that although wetlands occupy a mere 5–8% of the global land surface, they store approximately 20–30% of the world’s soil carbon (Nahlik and Fennessy 2016) and are also responsible for contributing significantly to annual global methane emissions, with estimates often ranging from 20 to 50% (Keddy 2010; Zhu et al. 2016). Peatlands and coastal wetlands are particularly significant in terms of carbon sequestration and storage (Chmura et al. 2003; Bridgham et al. 2006; Keddy 2010). Wetlands are thought to be significant drivers of past glacial/interglacial cycles and are likely to act as significant feedbacks in current and future climatic changes (Bridgham et al. 2014). In fact, wetlands were integral to the initiation of the current anthropogenic warming trend because fossil fuel consumption releases the carbon originally stored as ancient wetland peat deposits (which became coal and oil deposits). The greatest fossil fuel accumulation occurred during the Carboniferous Period, 286–360 million years ago (Keddy 2010; Maltby and Acreman 2011). This historical relationship between wetlands and the origins of anthropogenic climate change highlights the significance of wetlands in regulating atmospheric carbon levels and therefore in playing a role in regulating climate and further suggests that wetlands and their management have the potential to play a significant role in our response to climate change, as discussed below.

We are already seeing significant ecological changes resulting from global climate change. These changes include rising average temperatures, more high-heat days, increases in extreme weather events, sea level rise, and changes to the hydrologic cycle (including both increased and decreased rainfall, increased drought, and increased intensity of precipitation events). These changes have resulted in a loss of biodiversity as well as damages to ecosystems and human communities (Erwin 2009; Intergovernmental Panel on Climate Change 2014). While climate change occurs across the entire planet, the impacts are particularly evident at the local scale. Dr. Bill Moomaw, of Tufts University, put this more succinctly, “Climate change is a global issue that manifests itself locally.” The local manifestation of a global challenge presents opportunities for wetland scientists, practitioners, managers, and policymakers. Wetland-focused climate mitigation, adaptation, and resiliency measures implemented at local, regional, national, and international scales, particularly when implemented in an integrated and cross-sectoral manner, contribute to reducing climate impacts and/or slowing climate change (Finlayson et al. 2005; Moomaw et al. 2018).

Climate change discussions have tended to focus on reduction of greenhouse gas emissions from industry, transportation, and other human activities involving fossil fuel consumption, and this is indeed critically important. In addition, global climate change can be understood more broadly, with the realization that anthropogenic greenhouse gas emission is a land use change and ecosystem change problem (Nahlik and Fennessy 2016), as well as an industrial, transportation, and human activity emission problem. When we disrupt natural carbon sequestration processes and existing ecosystem carbon banks (long-term storage of carbon in soils and biomass) by disturbing or converting functioning ecosystems to developed landscapes, we are often reducing or eliminating the capacity for ecosystems, especially wetlands, to remove carbon from the atmosphere and/or to function as carbon banks and, in some cases, are increasing carbon emissions to the atmosphere (Moomaw et al. 2018). This is particularly true when we disturb or eliminate wetlands, given their disproportionate role in the global carbon cycle. In addition, it is difficult to reverse the impact of disturbance when freshwater wetlands are created (Neubauer and Megonigal 2015).

10.2.3 Current Research

Wetland biogeochemical processes include the sequestration of atmospheric carbon (i.e., carbon dioxide) into plant biomass through photosynthesis, as well as efficient storage of carbon in soil resulting from anaerobic conversion of decaying plant material into soil organic matter (Moomaw et al. 2018). Methanogenesis also occurs in anaerobic soils in freshwater wetlands. In natural wetlands, carbon sequestration exceeds emission of methane, leading to net storage of carbon, rather than net emission of carbon. In this way, natural wetlands act as planetary coolants. In contrast, disturbance of freshwater wetlands can lead to a biogeochemical shift such that carbon emitted as methane exceeds sequestration of atmospheric carbon, thereby transforming the wetland into a net carbon emitter. Similarly, newly created freshwater wetlands are often net carbon emitters until they reach a switchover point decades, hundreds, or thousands of years after their creation, at which point they become net carbon sequesterers (Neubauer 2014). Coastal saltwater wetlands are highly effective and efficient carbon sequestration engines and do not tend to become net carbon emitters when recently created, due to their differing soil biogeochemistry. However, they can become net carbon emitters if disturbed (Bridgham et al. 2006; Moseman-Valtierra et al. 2016; Moomaw et al. 2018). Restoration of drained or disturbed freshwater and saltwater wetlands can restore carbon sequestration functions such that wetland carbon emissions are reduced and carbon storage is increased (Moomaw et al. 2018).

This understanding of how wetlands function in the global carbon cycle highlights the importance of protecting existing wetlands as significant soil carbon banks and preventing their conversion to disturbed ecosystems or to developed land that function as net carbon emitters (Junk et al. 2013; Nahlik and Fennessy 2016). This understanding also provides insight into how we approach wetland creation and restoration and how to design carbon banking systems that might reference created, restored, and undisturbed wetlands (Moseman-Valtierra et al. 2016).

Wetlands are particularly sensitive to the impacts of climate change because they exist at the transition between dry land and aquatic ecosystems. Even small changes in temperature and/or hydrologic cycles can result in significant changes to wetland hydrology, soils, vegetation, and fauna (Erwin 2009; Lawler 2009). Wetlands are anticipated to be negatively impacted by climate change through warming temperatures; spread of invasive species, pests, and diseases enabled by warmer temperatures; severe storm events and their consequences such as increased flooding, landslides, mudslides, avalanches, and soil erosion; drought; decreased water quality and quantity; changes in flow regimes and sediment transport; habitat loss; and sea level rise and coastal erosion (Finlayson et al. 2005; Kusler 2006; Erwin 2009; Lawler 2009). Tidal wetlands are at risk of being caught in “coastal squeeze” between rising sea levels and upgradient development or sharply rising natural topography (Nicholls 2004; Torio and Chmura 2013). Acute extreme weather events and synergistic impacts from multiple stressors in combination with climate change may lead to long-lasting ecological reorganizations (Finlayson et al. 2005; Erwin 2009). As the climate changes and wetlands experience multiple stressors, we can expect changes to the traditional ecosystem services that a given wetland provides (Finlayson et al. 2005).

10.2.4 Wetland and Human Community Adaptation, Resiliency, and Ecological Carbon Conservation

It is important that we identify Best Management Practices that will promote ecosystem resilience, protection of existing ecosystem carbon, increased capacity to sequester and store ecosystem carbon, and maintenance of ecosystem services in the face of climate change and other stressors. Measures that can be taken include protection of water tables and water regimes, protection of existing ecological carbon banks, enhancement of ecological carbon sequestration (i.e., through wetland restoration and saltwater wetland creation as well as afforestation and reforestation), maximizing ecosystem connectivity, increasing buffer zones, protection of large undisturbed ecosystems, minimizing other stressors, incorporating climate change modeling into wetland management, restoration and creation, planning wetland management, restoration and creation at the watershed and landscape scales, and maintaining biodiversity (Anderson et al. 2016a, b; Christie and Kusler 2009; Lawler 2009; Moomaw et al. 2018).

The importance of traditional wetland ecosystem services (Woodward and Wui 2001; Keddy 2010; Mitsch and Gosselink 2015), including flood storage, storm damage protection, water supply during droughty times, water quality improvement, coastal storm buffering, localized cooling, maintaining local and regional hydrologic regimes and microclimates, stormwater management, biodiversity and habitat protection, erosion control, and wave attenuation, increases as climate change accelerates the intensity and/or frequency of heavy precipitation, flooding, drought, increasing temperatures, and sea level rise. Landscapes with greater density of wetlands (i.e., wetland mosaics) have been found to support greater ecological resiliency and biodiversity, as they create temperature and humidity gradients on the landscape, diversify habitat types, and facilitate increased landscape connectivity, allowing species to migrate locally during high-heat events and regionally over time (Adamus 2007; Lawler 2009; Anderson et al. 2016a). Wetland ecosystem services support ecological and human community adaptation and resiliency in the face of climate change (Anderson et al. 2016a; Narayan et al. 2016) and thus are more important than ever.

10.2.5 Summary

Wetlands are a 3-for-1 deal: they provide traditional ecosystem services, climate change adaptation services, and carbon storage/sequestration and emission reduction services. However, wetlands are faced with multiple challenges, such as climate change, land conversion, and invasive species. These stressors often act synergistically, and we must plan for and anticipate how our ecosystems and wetlands are changing and look for ways to maximize ecosystem/wetland and human community health, as well as the protection and delivery of ecosystem services in the face of these synergistic challenges.

10.3 A 100-Million-Year History of Polar Wetlands: Their Utility for Predicting the Future

  • B. LePage

10.3.1 An Ice-Free Planet

Geologically, climate change and a return to hothouse conditions is inevitable, and the greatest change will be seen at the poles. Since 1980, the surface and lower troposphere temperatures in the Arctic have experienced the most rapid warming on the planet of about 1 °C per decade (Anisimov et al. 2007, IPCC 2013). Using the B2 emission scenario,1 the ACIA (2005) indicate global temperature will increase ca. 2.6 °C by 2100, whereas in the Arctic, it will be about 5 °C. Warming in the polar regions will change the reflectivity (albedo) of the land and ocean, ocean water composition and circulation, and greenhouse gas emissions, especially CO2 and methane from soil oxidation, melting permafrost, and destabilization of clathrates in ocean sediment. The Arctic Climate Impact Assessment (ACIA 2005) also reported precipitation in the Arctic has increased by 8% over the last 100 years and a 20% increase by the end of this century is expected. Increased precipitation impacts physical processes that include albedo, glacial ablation, snowpack heat transfer and formation, surface energy exchange, snow metamorphism, melt timing and duration, permafrost stability, nutrient cycling, vegetation growth patterns, vegetation community composition, animal grazing, animal habitats, and fire frequency (Mård et al. 2017). In the polar regions, such changes have the potential to substantially and significantly influence radiative, thermal, and biological feedbacks that could further impact Arctic Ocean stratification, sea ice formation, and thermohaline circulation, accelerated permafrost degradation, increased erosion rates, altered productivity and biodiversity in terrestrial ecosystems, and changes to groundwater and surface water flow (ACIA 2005; AMAP 2017; Mård et al. 2017).

The Intergovernmental Panel on Climate Change (IPCC 2013) reported there is medium confidence that methane emissions from Arctic wetlands will increase due to increasing CO2 concentrations and temperature. The transition from cryic to boreal and ultimately temperate conditions in the polar regions will greatly alter global climate, carbon cycling, and biodiversity. As scientists work through the hundreds of questions that come with global climate change, those focused on the effects of forested and ice-free polar regions are perhaps the least well understood. From a purely ecological point of view, the physiognomy of green polar regions will depend on temperature, water availability, and light regime. Looking back to the plant fossil record from the polar regions up to 100 million years may provide useful calibration points, given that our understanding of lush plant growth in the polar regions under hothouse conditions is reasonably well understood.

The current total wetland area in the world is about 9 million km2 (ca. 6%) of the total land surface area (Schuyt and Brander 2004; Mitsch and Gosselink 2007). The National Ice and Snow Data Center (2018) reports 10% of total land area on Earth (ca. 150 million km2) is currently covered with glacial ice and another 10% is covered by tundra (https://www.britannica.com/science/tundra). If we assume that at least 50% of the 30 million km2 that are currently classified as ice (Greenland and Antarctica) and tundra become wetland and the current wetland area of 9 million km2 is maintained, then in an ice-free world, the total wetland area could nearly triple in size to around 24 million km2 (16% of the total land area). The increase in global wetland area will have striking implications for the planet on so many levels, but the effects will be the most pronounced in the polar regions.

10.3.2 Former Polar Wetlands

The concept of a warm Earth with no continental ice sheets is difficult for people to embrace because it is predicated on present conditions. Extensive coal-forming (forested wetlands) environments were typical of the regional landscape, and cool- to warm-temperate climatic conditions prevailed throughout the polar regions in the past (Harland et al. 1976; Ricketts and Embry 1984; Pedersen et al. 2006; Arbuzov et al. 2011). These ancient wetland deposits are exceptionally well-preserved assemblages of plant fossils and demonstrate that the landscape consisted of a mosaic of plant communities that ranged from wetlands to upland forests as far back as 100 million years ago (Heer 1868–1883; Kryshtofovich 1928; Schloemer-Jäger 1958; Sveshnikova and Budantsev 1969; McIver and Basinger 1999; LePage et al. 2005; LePage 2007, 2009; Williams et al. 2010; Herman 2013). Two of more recently and extensively studied forested wetland communities are from the late Paleocene (ca. 55 million years old (Myr)) on Ellesmere Island and middle Eocene (ca. 45 Myr) on Axel Heiberg Island, Nunavut, Canada. At these times (often referred to as the early Tertiary), these lowland wetland forests were dominated by redwoods (Taxodiaceae) and part of a vast circumpolar landscape that was structurally and compositionally similar (LePage et al. 2005; LePage 2007; Williams et al. 2009). Some were high biomass, moderately productive, and characteristic of modern cool-temperate forests (Williams et al. 2003). Clearly, climate in the polar regions during the early Tertiary was favorable for forest growth, and given the size of the fossil trees that have been measured and the geographic extent of early Tertiary coal deposits, these forests probably represent the maximum productivity achievable near the poles.

Today these regions are devoid of trees, and the cryic environment is a stark reminder that we are living at a time when icehouse conditions are prevalent and that there are no modern analogs for these ancient polar forests that we can use to better predict how plants will respond to warming global conditions and a hothouse Earth. However, the study and understanding of the information contained in the polar plant (and animal) fossil record may allow us to glean useful information on the evolutionary processes associated with changing vegetation communities, which then may allow us to better predict the eventual structure and composition of polar ecosystems that we might expect to see in the future.

Temperature and light regime were identified as important variables that would probably have the greatest impact on the evolution of the vegetation in the polar regions. The discussion that follows presents important elements related to these variables that warrant further refinement in our quest for understanding the future of wetlands in the polar regions.

10.3.3 Temperature

At the most fundamental level, temperature is responsible for the physical and ecological conditions that determine the type of plants that can grow above the Arctic (and Antarctic) Circle. Tree line exists for many reasons, but cold air and soil temperatures and a growing season that is too short for trees are the primary reasons. MacDonald et al. (2008) indicate tree phenology, growth, nutrient acquisition, meristem activity, and reproduction are impacted by cold temperatures, but the ability to overcome the physical limitations also provides certain tree species with a competitive advantage. For example, Sakai (1971) and Sakai and Larcher (1987) have shown that the bud/meristem in species of tamarack (Larix) can survive temperatures as low as –60 °C, giving it a competitive advantage over the other boreal taxa because at these low temperatures other boreal species cannot survive. As climate continues to warm, it was generally assumed that plant species would migrate northward and studies have shown this to be largely true (Payette 1993; Beauregard and Blois 2014; Boisvert-Marsh et al. 2014). However, when summer temperature is included in the envelope of suitable growing conditions, important tree line species such as balsam fir (Abies balsamea), white spruce (Picea glauca), and black spruce (P. mariana) showed a reversed trend with increased migration to the south. As a result, the long-held idea that heralds the northward migration of species into the tundra and deglaciated areas as climate continues to warm appears to be subject to change and puts our understanding of all of the mechanisms and processes that will govern the evolution and emergence of a polar flora into question (ACIA 2005; Boisvert-Marsh et al. 2014).

The impact and role of temperature on vegetation are clear, but temperature also plays an important role in nutrient acquisition and methane production. Read (1984) proposed plant mycorrhizal (fungal) associations correspond largely to the environment in which they occur, which then determines their respective nutrient acquisition strategies. Most plants establish mycorrhizal associations, and these associations influence plant productivity and diversity and play a key role in carbon, nitrogen, and phosphorous cycling (McGuire et al. 2013; van der Heijden et al. 2015). Trees growing on mineral and nutrient-rich soils at low latitudes and altitudes, where the temperature is warm, use an AM (arbuscular mycorrhizal) strategy. In these warmer and more temperate environments, organic turnover is high, phosphorous in soil is limited, and the AM fungi are effective at harvesting phosphorous from the soil and mobilizing it to plants (Smith and Read 2008; Qu et al. 2009; McGuire et al. 2013). At higher elevations and latitudes, the climate becomes colder, the soil becomes organic rich because biomass accumulation is greater than decomposition, and the nitrogen and phosphorous pools are in a form that is generally not available to plants. In these montane and boreal environments, the soil becomes acidic, nitrogen and phosphorous are limited, and plants utilize an ECM (ectomycorrhizal) strategy (Smith and Read 2008; Qu et al. 2009; McGuire et al. 2013). Although ECM plants can grow in the same habitats where AM plants dominate the landscape, and vice versa, they are generally not abundant.

Therefore, it stands to reason that the boreal tree line forest, which is largely composed of members of the pine family (Pinaceae) that form obligate ECM associations (Agerer 1987), is likely to be the first trees to occupy the tundra and deglaciated areas. The early Tertiary plant fossil record indicates that for millions of years, the polar ecosystems were dominated by plants that formed AM associations. While the expectation is that temperate AM-dominated ecosystems will return to the polar regions with continued global change and warming, the timing and ultimate composition of the flora and what the transition will look like are unknown.

10.3.4 Methane

Global methane emissions from natural wetlands indicate that the high-latitude wetlands were probably important sources of methane during the early Tertiary. Fossil forests and extensive coal deposits indicate that dawn redwood (Metasequoia) dominated wetlands were common from about 50°N to the Arctic Ocean during this time (LePage et al. 2005). Using the data of Cao et al. (1998) on the current latitudinal distribution of annual net primary productivity (NPP) and the estimates of Eocene wetland forest productivity from Williams et al. (2003) (7–8 Mg ha–1 year–1 for above- and belowground NPP), the annual NPP in the polar latitudes was approximately 6–8 times higher in the Eocene than it is at present. Global patterns of NPP and methane emissions are reasonably well correlated on the modern Earth (Cao et al. 1998). So, if it is assumed that the high latitudes (>50°N), during the early Tertiary, contributed about 50% more wetlands than at present and infer the same rate of conversion of NPP to methane as is seen in modern temperate climates, the high-latitude wetland forests of the early Tertiary could then have emitted 3–5 times more methane than at present. This contribution becomes important because the addition of 3–5 times more methane into the atmosphere would have been sufficient to generate polar stratospheric clouds (PSCs), which Sloan et al. (1999) have shown were needed to keep the polar regions warm during the dark winter months. Without a viable forcing mechanism to warm the poles, most global climate models indicate winter temperatures in the mid- to high latitudes were around −20 °C (Sloan 1998), and if this were the case, forests with boreal characteristics may then be expected to develop. However, this estimate is 10–30 °C below those derived from the plant fossils (Huber and Caballero 2011). Climate modeling indicates that PSC could increase surface temperatures in the Arctic during winter months by as much as 20 °C, which would also be in agreement with the character of the early Tertiary vegetation known from the polar regions (Sloan 1998; Sloan et al. 1999).

The current expectation is that the encroachment, establishment, and occupation of boreal forest elements into all areas of the tundra and deglaciated areas will occur, and as climate continues to warm, these forests will give way to temperate ecosystems (ACIA 2005). While this concept is very simple and may well be the outcome, the variables that feed into this model are likely to be numerous, and those that we are aware of are yet to be fully understood. Nevertheless, the role of wetlands in these processes will be integral to how these regions will evolve. Therefore, from the standpoint of dependencies, the type of vegetation that could grow in the polar regions depends in part on winter temperature. Winter temperature depends on PCS formation, because without PSC, summer temperature alone is insufficient to maintain a more equable temperature range and temperate ecosystems. PSCs depend on the relationship between methane production, wetland area, and litter quality. Litter quality is important because the litter produced by many representatives of the boreal forest such as the pine family (Pinaceae) is of poor quality and insufficient to generate the methane needed to produce and sustain PSC. While increasing wetland area will contribute to more methane production, the crux of the problem is that the composition of the vegetation growing in the wetlands determines litter quality, which then drives PSC formation. From the standpoint of warmer winter temperatures and evolution of polar plant communities, the important first steps seem to be linked to the initial trajectory and development of the early polar wetlands as global climate continues to warm. The fossil record shows clearly that stable temperate ecosystems existed in the polar regions for millions of years in the past and there is no reason to dismiss the notion that similar conditions will exist in the future. However, whether PSCs are alone responsible for warming the poles in the winter is not yet resolved, and the question of the time it will take to return to such conditions is not at all understood.

10.3.5 Light

Above the Arctic and Antarctic Circles, the quality and quantity of light is unique. For 3 months a year during the summer, plants grow under 24 h of continuous and low-angle light. The light regime is an important but a poorly understood, physiological parameter associated with plant growth responses in the polar regions. As MacDonald et al. (2008) pointed out previously, temperature plays an important role in plant responses, but germination, growth, flowering, frost hardening, and dormancy are all responses to day length, light quantity, and light quality. In an elegant experiment where photocontrol of growth and dormancy in woody plants was tested, Downs (1962) exposed white spruce (Picea glauca), Japanese larch (Larix kaempferi), Douglas fir (Pseudotsuga menziesii), and Monterey pine (Pinus radiata) seedlings to different light treatments, including a 24-h photoperiod for up to 1 year. The results showed progressively greater growth and fresh weight of these seedlings with increased exposure to light. However, the coast redwood (Sequoia sempervirens) did not respond similarly to the other seedlings. The redwoods progressively increase growth and fresh weight when exposed to 12-, 14-, and 16-h photoperiods but then decreased substantially when exposed to 20- and 24-h photoperiods. The coast redwood is a good example of an important species that has a predetermined distributional range that appears to be governed by the amount of light received. We would not expect to see the coast redwood at latitudes where the amount of light approaches or exceeds 20 h day–1.

The plant fossil record also indicates that lower amounts of photosynthetically active radiation (PAR) and lower angle incident light in the polar regions did not limit the structure and character of the vegetation communities, but light might have a strong influence on species composition. These results suggest that some tree line species simply may not be well adapted to growing in a polar light regime and that light may act as a barrier or filter to expansion or migration of plant taxa into the high latitudes.

10.3.6 Conclusions

Wetlands have played a crucial role in the evolution and terrestrialization of the planet. The presence of coal and peat deposits in the geologic record attest to the widespread distribution of past wetland communities over the planet for at least 440 million years. In the polar regions and over the span of approximately 100 million years, climate cooled, and the vegetation shifted from a temperate to boreal character and ended in glaciation. As global temperature increases, there is consensus that the vegetation zones and species ranges will migrate altitudinally and latitudinally. There is already evidence that the tree line is moving northward (ACIA 2005; IPCC 2013; Martin et al. 2017). The prediction that glaciated areas and tundra will warm and existing herbaceous vegetation will give way to encroaching boreal shrubs and trees is reasonable, but other scenarios may emerge. As was the case in the past, the assumption is that with continued warming at the poles, taxonomically diverse and structurally complex forests will develop. However, our ability to accurately predict the critical biotic and abiotic thresholds that will mark the emergence and evolution of new (compositionally and structurally) vegetation assemblages is being challenged. There is no doubt that the role that wetlands play in the future will be significant, but the innumerable biotic and abiotic relationships and complexities preclude even an attempt to determine what a green Arctic and Antarctica might look like.

10.4 Climate Change and Coastal Wetlands: Planning for Resiliency in the Face of a Rising Tide

  • T. Z. Osborne

10.4.1 Introduction

Climate change is a real and pressing issue facing natural resource managers and requires planning for the protection of coastal wetland resources. Understanding the ecological trajectory of coastal wetlands that currently are, or in the future will experience, effects of sea level rise (SLR) and altered temperature regimes is critical to anticipating future coastal ecosystem form and function. This is especially important in areas where wetlands play a regionally significant role as storage pools of ecologically relevant elements (carbon, nitrogen, phosphorus) (Osborne et al. 2011) and critical habitat for fisheries (Johnston and Caretti 2017) or provide other desirable ecosystem services (Craft et al. 2008; Barbier et al. 2011). In this section, we look beyond the classical attributes of wetland hydrology, such as water depth, duration of inundation, or even flow metrics, and discuss how the change from fresh water to brackish or even full-strength sea water, due to SLR, affects dominant plant communities and associated wetland functions.

Observations of saltwater intrusion into the coastal freshwater marshes of the Florida Everglades and coastal forests of Florida’s Gulf Coast provide insight into ecosystem trajectories, particularly that of vegetation communities. The synthesis of these observations suggests significant changes to ecosystem form and function within the footprint of saltwater transgression, providing resource managers with potential approaches to plan for ecosystem changes. Observations of coastal development patterns that exemplify the need for consideration of wetland expansion within urbanized landscapes or risk complete loss of riparian wetlands also provide insight.

10.4.2 Sea Level Rise in the Florida Coastal Everglades (FCE)

South Florida has been a focal point for SLR issues with the City of Miami already experiencing significant saltwater transgression events on King Tide cycles. Due to proximity, much attention has been focused on the future of FCE wetlands due to SLR and the associated impacts to the southern reaches of Everglades National Park (ENP) (Chambers et al. 2014; Saha et al. 2011). While the extent of mangrove advancement throughout ENP has dominated management discussions and planning, the processes of SLR-associated shifts in vegetation community structure are poorly understood. Ostensibly, historic dominant vegetation, sawgrass (Cladium jamaicense), is exposed to ever-increasing salinity stress until a critical point is met based upon plant tolerance, where then the community shifts to more halophytic species (Troxler et al. 2014). In the case of the southern ENP, this more salt-tolerant species is red mangrove (Rhizophora mangle). Perhaps of greater importance, associated with the loss of sawgrass is a concomitant loss of freshwater organic soils through destabilization and erosion. The mechanism of soil loss, termed “peat collapse,” while still scientifically undefined, can also catalyze a catastrophic shift in habitat type as resulting loss of soil elevation (potentially 10–20 cm) which may inhibit future vegetation recruitment (Fig. 10.1). The transect depicted in Fig. 10.1 demonstrates the community shift along a gradient of salinity exposure from brackish/marine (Site 4) to the freshwater interface (Site 1). Visual examination of this transect also enables a view of the successional stages that will likely take place as SLR continues. As saltwater transgression events move farther into freshwater marshes, red mangrove propagules are transported upstream and establish in freshwater areas (Site 1). As salinity incursions become more frequent, destabilization of soils results in more open water habitat within the mangrove–marsh community mosaic (Site 2). Further increase of salinization events results in fragmented mangrove and open water habitats that continue to diverge until a roughly equal distribution of mangrove and open water habitats exists (Site 4). Although this transition is well known to Everglades researchers, it provides a noteworthy example of potentially dramatic changes to coastal wetlands and their likely future trajectories under current SLR projections. The historic form of the system is altered as freshwater marsh transitions to brackish swamp and many ecological functions of the system are likewise changed (Gaiser et al. 2006). For example, carbon (C) sequestration declines initially with peat collapse (Chambers et al. 2011, 2014) and slowly returns with the maturation of mangrove communities (Simpson et al. 2017). However, the total C stored in the system may take centuries to return based upon current accretion rates and the significantly decreased spatial extent of vegetation observed (Sites 3–4).
Fig. 10.1

Transition from mangrove to freshwater emergent marsh in the southern most portion of the Florida Coastal Everglades. Transect demonstrates vegetation community shifts from freshwater emergent marsh dominated by Cladium jamaicense with very sparse Rhizophora mangle (1); increase in coverage of R. mangle and concomitant loss of soil elevation due to “peat collapse” (2); dominance of spatial coverage by R. mangle and fragmentation of vegetation patches (3); equal distribution of R. mangle and open water habitats

Peat collapse can also accelerate export of nutrients such as nitrogen and phosphorus originally contained in the soils (Chambers et al. 2011, 2014; Osborne et al. 2017), thus reducing another critical ecosystem service and nutrient sequestration. Alternatively, critical fish (Boucek and Rehage 2015) and wading bird habitat (Wingard and Lorenz 2014) increases with increased mangrove cover, and resiliency to storm erosion is also increased, suggesting there are ecosystem service trade-offs to be considered by resource managers.

10.4.3 Sea Level Rise on Florida’s Gulf Coast

Due to the recognized ecological value of coastal wetlands, landward migration of salt marsh in response to SLR has been a significant topic of research recently (Craft et al. 2008; Fagherazzi et al. 2012; Kirwan and Megonigal 2013; Kirwan et al. 2010). A prominent example of coastal wetlands in transition is found along the central Gulf Coast of Florida where very low topographic relief, combined with a low-energy shoreline, creates large transition zones in which coastal forests are retreating in the face of SLR (Raabe and Stumpf 2016; Geselbracht et al. 2011). Like the FCE, the example transect we examine here (Fig. 10.2) spans a transition from marine to freshwater habitats. However, in this case, vegetation community shifts are going in the opposite direction; salt marshes and mangroves are replacing forests. Site A on the transect (Fig. 10.2) represents open water habitat overlying sandy sediments with occasional seagrass establishment occurring. Transitioning toward freshwater and upland boundary, an increased prominence of salt marsh, dominated by smooth cordgrass (Spartina alterniflora), and black mangrove (Avicennia germinans) is observed (Site B). This vegetation community is following closely behind the salinity front where freshwater emergent species and terrestrial woody vegetation are succumbing to salinity stress (Site C – note the standing dead trees). Site D represents the freshwater endmember of the transect containing intact costal forest interspersed with open water habitats and emergent freshwater marshes.
Fig. 10.2

Gradient of vegetation induced by saltwater transgression across the marine to maritime forest continuum (inset pictures correspond to letters on transect). Points across transect (ad) represent transition from shallow Gulf of Mexico waters dominated by open water/seagrass meadows (Thalassia testudinum) (a) to mixed salt marsh (Spartina alterniflora) and mangrove (Avicennia germinans) habitats (b), to retreating forests and freshwater marshes with low density halophytic vegetation (Juncus roemerianus) encroachment (c), and to current maritime forest (Quercus virginiana, Sabal palmetto) with interspersed isolated wetlands (Cladium jamaicense) (d)

Similar to the FCE, there are substantial alterations to ecosystem forms, such as shifts from vegetated habitat to vegetated open water/seagrass beds or terrestrial forest to salt marsh. These shifts can reduce ecosystem services such as carbon and nutrient sequestration in much the same manner as FCE. Further, because these areas are low energy and spatially removed from sediment sources, marsh accretion does not keep pace with SLR (Kirwan et al. 2010; DeLaune and White 2012) resulting in a landward migration of marsh/mangrove habitat. Fortunately, low-slope topography resulting in significant gains in marsh area has been documented (Raabe and Stumpf 2016) that offsets the loss of salt marsh at the trailing edge of the transition zone. Hence, while this transition zone is a moving target for resource managers, there is a positive gain in spatial extent of aquatic habitat in the form of salt marsh and seagrass. Unfortunately, this positive gain in coastal wetland extent in response to SLR relies on expansion in unobstructed areas without anthropogenic constraints.

10.4.4 Risk of Coastal Wetland Loss in Urbanized Landscapes

The previous two examples of SLR-altered coastal wetlands utilize relatively natural areas (FCE and FL Gulf Coast); however, this final example examines SLR in the urbanized landscape to provide cautionary guidance for resource managers tasked with protecting dwindling coastal wetlands. While FCE and the Gulf Coast examples demonstrated clear visual trajectories of vegetation communities in transition of freshwater marshes and coastal forests to brackish marsh and mangrove swamp, the continued transformation (and thus net balance or potential gain of coastal wetlands) is predicated on the availability of natural areas for SLR to drive expansion of coastal marshes (Kirwan and Megonigal 2013; Kirwan et al. 2010). A latitudinal gradient of coastal development on Florida’s east coast provides an opportunity to visualize the effects coastal wetland expansion without sufficient opportunity for coastal wetland expansion with SLR (Fig. 10.3). Site A, located on the Matanzas River in NE FL, is a moderately developed landscape with what we have denoted as a medium level of marsh expansion potential utilizing natural area easements and low-lying river watersheds. Site B demonstrates older developments along the shores of the Indian River Lagoon in Cocoa Beach, FL, where shorelines have little to no room for expansion beyond isolated parks and nature preserves. This example results in net loss of wetland habitat as SLR proceeds. Finally, Site C, located in South Beach, Miami, demonstrates the oldest development that is also highest density and allows for no landward migration of coastal wetlands. In this last case, shoreline armoring is already necessary to protect property from SLR and effectively negates any shoreline vegetation establishment. In this case, there is already significant loss of coastal wetland habitat due to development, and thus no expansion potential exists (Kornis et al. 2017). This gradient allows for us to visualize the effects of the anthropogenic environment on wetland habitat with respect to future SLR. The need for resource managers and municipal planners to consider, and include, areas for coastal wetland expansion is clear. Under these conditions, the loss of ecosystem services is directly linked to the overall loss of coastal wetlands, and thus to protect these desired services, planned locations for marsh expansion are needed.
Fig. 10.3

Gradient of shoreline development setback. Medium riparian easement, Matanzas River in St. Augustine, FL (a); low riparian easement, Indian River Lagoon, Melbourne, FL (b); and no remaining riparian easement, South Beach Miami, FL (c)

10.4.5 Summary

The goal with this work was to provide resource managers and research scientists alike with ecosystem trajectories which include alterations to C and nutrient sequestration, habitat, and protection from storm events. These trajectories form the basis for which to forecast change and resiliency in coastal wetlands and plan for protection of highly functioning wetland resources.

The examples of SLR-induced alterations to both natural (FCE and Gulf Coast lowlands) and urbanized (FL east coast) landscapes provide an opportunity to visualize potential future form and function of coastal wetlands. The Florida Coastal Everglades is a site of significant transition from freshwater, sawgrass-dominated marsh to a brackish-water mangrove swamp. With this evolution comes changes in overall ecosystem services such as C and nutrient sequestration and fish and wading bird habitat (Barbier et al. 2011). While some C and nutrient sequestration is likely lost, there are gains in habitat and storm protection at the freshwater/saltwater interface in FCE. The Gulf Coast transect demonstrated the opposite vegetation trajectory (from forested to emergent marsh). However, this transition zone demonstrated a net gain in overall wetland habitat (Raabe and Stumpf 2016) in that upland forest was also observed to transition into brackish marsh. While net sequestration of C and nutrients is likely diminished as freshwater wetlands are transgressed by saline waters (Chambers et al. 2011, 2013), net gain in habitat and thus long-term C storage is increased. It is important to note that the change of one wetland type to another is not necessarily positive or negative; rather it is likely a transfer of balance between current and future ecosystem services.

Finally, the examination of a gradient in shoreline development on the east coast of Florida demonstrates the potential loss of almost all ecosystem services if marshes and mangroves are not allowed to migrate landward under pressures of SLR. Thus, it is imperative that planners and resource managers recognize and accommodate marsh expansion in remaining areas where open expansion easements still exist.

10.5 Lessons Learned in Hydrologic Management of Wetland Conservation Areas in the Upper St. Johns River Basin, Florida, USA

  • K. J. Ponzio
  • S. J. Miller
  • A. M. K. Bochnak
  • S. A. Phelps
  • M. Q. Guyette

10.5.1 History of Hydrologic Alteration

While climate change effects in coastal/tidal ecosystems are more obvious and direct (i.e., as a result of SLR and salinization, as discussed in Sect. 10.4), those in freshwater/inland systems may be more subtle. Inland systems may be variably impacted through changes in species distribution and phenology, increased productivity due to higher temperatures, longer growing seasons, and increased CO2 supply and by changes in weather patterns and water availability. The Natural Resources Defense Council (2010) projected that Central Florida will have an extreme risk for water shortages by 2050 due to increased human water demand, increased evapotranspiration, and rainfall deficits. This necessitates the wise use and management of water resources, both for human needs and the needs of wetland ecosystems. This section presents three case studies describing the role of hydrology as a major driver and stressor in wetlands and the lessons learned in water management of these areas. These lessons can be applied to predict future responses to climate change impacts since these areas have either experienced severe draining, long-term flooding, or short-term intense drying events.

The case studies are located in the United States in East Central Florida at the headwaters of the St. Johns River in an area known as the Upper St. Johns River Basin (USJRB) (Fig. 10.4). The headwater wetlands in the USJRB originally encompassed nearly 162,000 ha and are gently sloping with a 1/3 m elevation decline over a long 8 km distance in a northerly direction (Miller et al. 1998). These wetlands were historically characterized by a mosaic of habitats dominated by herbaceous marshes that visually resembled the Florida Everglades and are underlain by deep organic soils that developed over thousands of years. As mentioned in Sect. 10.2, these types of peatlands are particularly significant in reducing the impact of climate change by keeping carbon in long-term soil storage and preventing release of important greenhouses gases to the atmosphere.
Fig. 10.4

Location of FDMCA (8300 ha), BCMCA (8400 ha), and SJMCA (8700 ha) and referenced project features in the USJRB

Over the last century, there has been a drastic loss of wetlands in the USJRB. Beginning in the early 1900s, the historic floodplain was diked and drained, and by the 1970s, 62% of the 100-year floodplain had been converted to agriculture (Lowe et al. 1984). Agricultural development led to widespread ecological degradation of the USJRB, including a loss of water storage resulting in increased flooding, diminished water quality due to nutrient enrichment, disruption of the natural hydrologic and fire regimes, decreases in fish and wildlife populations, and exotic and invasive species encroachment (Cox et al. 1982; Fall 1982; Lowe et al. 1984; Hall 1987).

To provide enhanced flood protection and reverse environmental degradation, the St. Johns River Water Management District (District) partnered with the US Army Corps of Engineers (ACOE) to restore the historic USJRB floodplain using a “semi-structural” approach, whereby wetland storage capacity was expanded through extensive floodplain acquisition and the construction of numerous levees, canals, and water control structures to manage water levels (Sterling and Padera 1998). Toward that end, the District began purchasing former floodplain wetlands in the mid-1980s, and, to date, over 29,000 ha have been reclaimed and restored. The total project area currently exceeds 64,000 ha.

The focus of this discussion involves three large project areas where the District has been managing water levels for the past four decades—the St. Johns Marsh Conservation Area (SJMCA) which has been severely drained; the Ft. Drum Marsh Conservation Area (FDMCA) which experienced nearly permanent flooding; and the Blue Cypress Marsh Conservation Area (BCMCA) which more recently experienced short-term and intense drying events (Fig. 10.4). Since hydrology drives vegetative community structure and soil formation (Lowe 1983; Keddy and Fraser 2003; Reddy and DeLaune 2008; Mitsch and Gosselink 2015), hydrologic alterations are expected to have a cascade of effects in the ecosystem.

10.5.2 St. Johns Marsh Conservation Area

Hydrologic alterations beginning in the 1920s included the construction of the Fellsmere Grade (which bisected the marsh), construction of highway US192, excavation of perimeter drainage canals (such as the C-40), and removal of natural flow restrictions at the outlet (current weir location) of downstream Lake Washington (Fig. 10.4; Cox et al. 1982; Hall 1987). These changes reduced average water levels in SJMCA by 0.73 m. Hydroperiods or inundation frequencies, in the southern, middle, and northern sections of the SJMCA, were reduced from nearly constant inundation (100%) to 12%, 35%, and 60%, respectively. Changes in soil elevation, plant community shifts, and nutrient and gaseous fluxes were measured to assess the ecological implications of hydrologic changes.

A topographic change analysis between 2000 and 2009 showed that SJMCA experienced oxidation of the underlying peat soils and land subsidence. Maximum loss was 30 cm at the drier southern section, while most other areas had a loss of 3–15 cm (Fox et al. 2014). An area greater than 2100 ha experienced a total soil loss equal to 1,849,900 m3 or 30,555 m3 year–1 (Fox et al. 2014).

Drainage of the area caused shifts in wetland plant communities, mainly conversion of herbaceous marsh to a shrubby/forested system dominated by Carolina willow (Salix caroliniana). The extent of shrub wetland more than doubled over 20 years (Fig. 10.5; Hall et al. 2017). This encroachment likely occurred as a result of drainage creating optimal conditions for seed germination. Carolina willow communities have higher nutrient flux rates than most other herbaceous plant communities in the marsh (Lusby et al. 1998; Adler et al. 2008; Osborne et al. 2014; Bochnak et al. 2015; Hall et al. 2017), which may have downstream water quality implications. In addition, Carolina willow contributes more CO2 to the atmosphere than other herbaceous marsh plants, such as sawgrass (Cladium jamaicense) (Budny and Benscoter 2016). Carolina willow also has a greater transpiration rate than many herbaceous wetland plants, which has implications for further drying of the ecosystem (Budny and Benscoter 2016; Fauth et al. 2016). Overall, hydrologic alterations in SJMCA resulted in a tremendous loss of soil, a shift in the plant community from herbaceous to woody, increased nutrient loading for phosphorus and nitrogen, increased CO2 flux to the atmosphere, and increased evapotranspiration. These changes all have further implications for wildlife use, downstream water quality degradation, and climate change. Drying and loss of peat soils is of special concern in the global carbon cycle, because the wetlands are converted from carbon sinks to sources and provide a positive feedback loop for further climate change (Lovejoy and Hannah 2006).
Fig. 10.5

Chronosequence of shrub encroachment (primarily Carolina willow) in SJMCA from 1989 to 2009

Recognizing the need to rehydrate the drained marsh in SJMCA, the District installed earthen plugs in C-40 canal in 1986. However, these plugs led to uneven rewetting of the marsh, with areas downstream of the plugs remaining too dry and areas upstream becoming permanently flooded. In 1996, the District began a process of manipulating the C-40 plugs, including the installation of culverts, to most effectively rehydrate SJMCA. The primary hydrologic goals were to hydrate the marsh greater than 60% of the time while allowing periodic drying during the dry season (May–June) to occur at least once every 4 years. An inundation of 60% or greater is needed to prevent further oxidation and loss of organic soils, while periodic drying is needed to facilitate germination of many marsh plants (Miller et al. 1996). Delaying drying until May and June also minimizes exposure of the organic soils during the peak of willow seed production which occurs earlier in March and April. From 2000 to 2017, flooding of the SJMCA mostly increased, but hydrologic targets were not met as the southern, middle, and northern sections were still only flooded for 29%, 48%, and 23% of the time, respectively (S.J. Miller, SJRWMD, pers. comm.). Higher flooding duration in the midsection of the marsh reflects the positive, upstream effects of canal plug E7, which was operational throughout that time (Fig. 10.4). In 2017, two-dimensional hydrologic modeling was used to determine optimal locations and dimensions for future plugs. Modeling indicates that, by installing two additional canal plugs on the western side (W3, W4) and lengthening and installing gated culverts in four plugs on the eastern side (E2, E3, E4, E6), optimal hydrologic conditions over much of SJMCA can be created. These management activities should facilitate restoration of herbaceous marsh plant communities, have positive impacts on water quality, and improve the value of the SJMCA as fish and wildlife habitat.

10.5.3 Fort Drum Marsh Conservation Area

While drained conditions were the cause of ecosystem changes in SJMCA, prolonged hydroperiods and deeper water depths could have caused different, and potentially opposite, changes in the FDMCA in the southernmost extent of the USJRB (Fig. 10.4). Alterations to FDMCA began in the 1930s when a major highway (SR60) was constructed at its northern end and, in 1963, when the Florida Turnpike was constructed at the southern end. In the 1950s and 1960s, much of the upland area and the transitional wetlands in FDMCA were drained and developed for cattle grazing. In 1991, as part of the initial construction of the USJRB project, a north-south levee (L-79) was constructed that interrupted the historical southwestern to northeastern flow pattern.

To facilitate flow within the project, water control structures were installed under SR60 in 1991 (Fig. 10.4). While these structures provided for adequate flood-related discharges, they were not effective in allowing continuous downstream discharges under low-flow conditions. This resulted in nearly permanent inundation of herbaceous marshes within FDMCA. The District attempted to improve downstream flows during the dry season by excavating a spreader ditch north of SR60 that connected structures S252 A, B, and C. Unfortunately, this spreader ditch did not improve low-flow discharges. Later survey data taken in the downstream marsh indicated a ridge of slightly higher ground elevations was responsible for impounding water in FDMCA. In 1998, the ACOE installed an additional structure (S252D) that allowed for low-flow discharges to occur from FDMCA to the east through L-79.

A hydrograph of water levels in the marsh spanning from 1942 to 2016 is shown in Fig. 10.6. The average marsh elevation, determined from 1983 surveys, was 7.16 m. The historical average annual depth of water, using this ground elevation, was 0.20 m, and water levels fell below marsh ground elevation frequently.
Fig. 10.6

FDMCA hydrograph from 1942 to 2016 indicating historical marsh elevation at 7.16 m and contemporary marsh elevation at 7.44 m (thick, horizontal lines). Historical average water level (7.36 m), post L-79 construction average water level (7.75 m), and post S252D construction average water level (7.69 m) are depicted with dashed lines. Vertical dotted lines demarcate the construction of L-79 and S252D (SJRWMD, unpublished data)

After L-79 levee construction, the average annual water level in FDMCA increased to 7.75 m (approximately 0.4 m higher than historical), and the marsh was flooded nearly 100% of the time. Once the S252D structure was installed, mean annual water elevation dropped only slightly to 7.69 m. While the structure was partially effective in alleviating flooding, the District closed the structure in 2007, due to surrounding landowner concerns about flooding. As a result, a concomitant increase in water elevation at the end of the hydrograph is evident. However, in 2017, after tailwater and flooding concerns were addressed, the District resumed operation of S252D, and the structure is currently being opened from March through May to facilitate periodic drying of the marsh.

In FDMCA, plant community shifts, changes in marsh elevation, and soil accretion rates were measured to determine the ecological effects of extended flooding. It was expected that deeper, prolonged flooding would convert sawgrass, and other emergent plant communities, to open water and slough communities with floating-leaved species, such as white water lily (Nymphaea odorata). However, the marsh vegetation did not respond as predicted. Vegetation communities between 1994 and 2001 were compared at 601 points, and only 24% of these points indicated a plant community shift. None of the plant communities converted to open water, and only two points changed to lilies. Of the points that were sawgrass in 1994, 11% changed to another emergent, herbaceous community type, but none to open water or lilies. However, between 1994 and 2001, there were some other plant community changes that are consistent with prolonged hydroperiods and deeper inundation. The most notable was a marked invasion of two exotic species, primrose willow (Ludwigia peruviana) and Cuban bulrush (Cyperus blepharoleptos) in some areas, which accounted for most of the overall documented change in plant communities. These species are capable of colonizing deep water and creating floating mats that can survive water levels unsuitable for other emergent plants. Floating mats of Cuban bulrush frequently break loose and can invade sparsely vegetated areas and may eliminate other marsh species by overtopping and scouring stressed, emergent vegetation.

Vegetation mapping of FDMCA also occurred in 2008, and comparisons were made at the same points as those evaluated in 2001. Between 1994 and 2008, 63% of the points changed, but again, relatively few transitioned to open water or lilies. From 1994 to 2008, there was much greater conversion of sawgrass to mixed shrub swamp, which might be expected with lower water levels (not deeper and prolonged inundation that occurred in FDMCA). A greater than fivefold increase of the mixed shrub community occurred between 2001 and 2008. This may have occurred because mat-forming primrose willow and Cuban bulrush provided a nursery or seed bed for other emergent species and shrubs. These shrubs and other plants slowly build thicker and thicker mats or “quasi-substrate,” and eventually the weight of the floating mat causes it to sink and become rooted.

Coincident elevation survey points taken in FDMCA between 1983, 2002, and 2007 indicate a fairly consistent rise in elevation in 2002, with an average of 15 cm over 19 years, equaling a 0.8 cm rise per year. Between 2002 and 2007, the marsh raised another 6 cm. Overall, there was an average 21 cm rise in the marsh elevation over 24 years or 0.9 cm year–1 (Table 10.1). Comparatively, soil accumulation rates in the Everglades ranged from 0.14 cm year–1 in unenriched areas to 1.13 cm year–1 in highly enriched areas just downstream of inflow structures (Table 10.1). Another study conducted in the USJRB reported accretion rates of 0.33 cm year–1 until the 1920s and more recent rates of 0.53 cm year–1 (Table 10.1; Brenner et al. 2001). The accumulation rate in FDMCA from 1983 to 2007 (0.9 cm year–1) is nearly three times greater than historical rates in the USJRB system, prior to the 1920s.
Table 10.1

Comparative soil accumulation rates for similar wetlands in Florida

Location

Source

Condition

Time period

Accumulation rate (cm year–1)

FDMCA

SJRWMD, unpublished data

Extended inundation

1983–2002

0.80

1983–2007

0.90

Everglades

Craft and Richardson (1993a, b)

Extended inundation

1964–1989

0.28–0.32

Nutrient enriched

0.40

Everglades

WCA-2A

Reddy et al. (1993)

Unenriched

1964–1990

0.52

Nutrient enriched

1.13

Craft and Richardson (1998)

Unenriched

1998

0.14–0.17

Nutrient enriched

0.58–0.67

USJRB

Brenner et al. (2001)

Nutrient enriched

1920

0.33

All sites

1963–1994

0.53

Comparative topographic maps for 1983 and 2007 show an increase in elevation of approximately 24 cm, which closely aligns with coincident point-by-point calculation of 21 cm. Assuming there was an average 21 cm increase in ground elevation over the entire marsh in FDMCA from 1983 to 2007, this totals nearly 6 million m3 of soil gain over 24 years. FDMCA had a net soil elevation gain of 35,875 m3 year–1, as compared to a net loss of soil elevation in SJMCA of 30,555 m3 year–1. The rise in elevation in FDMCA means that the contemporary water depth is not as deep as was originally calculated. If the rise in elevation is depicted as a stairstep, rather than the more realistic gradual change that most likely occurred, the contemporary water depth is an average of 25 cm deep, as compared to the historical average water depth of 20 cm (Fig. 10.6). Therefore, the District should update topographic data to manage for the proper water levels to meet hydrologic goals.

The nature of the rise in elevation in FDMCA was investigated by collecting soil cores and measuring the above- and belowground biomass in May 2009. Interestingly, the belowground biomass in FDMCA marsh was 12–40 times greater than the belowground biomass measured in unimpacted areas in BCMCA (Phelps et al. 2015). Apparently, the marsh plant communities in FDMCA responded to the stress of longer hydroperiods and deeper inundation by maximizing their belowground productivity, which resulted in the significant rise in surface elevation observed. While peaty soils typified cores in BCMCA, those from FDMCA were characterized by massive root systems and minimally developed soil material.

To summarize, deeper and more prolonged inundation did not result in the expected shift of vegetation communities to open water and floating-leaved plant communities but, instead, to shrubby communities that are adapted to extended hydroperiods through floating mat formation. Because the increase in water depth and duration was so protracted (22 years), plants were not stressed to the point of mortality and were able to keep pace with rising water levels. The incredible resiliency of the plants to increase belowground productivity resulted in raising the marsh surface on the order of 0.9 cm year–1 and “soil” accumulation over the 24 years. However, if flooding in FDMCA is reduced by continued operation of the S252D structure, marsh subsidence may occur as a result of decomposition of the large belowground rootstocks and compaction of the spongy, supersaturated soils.

10.5.4 Blue Cypress Marsh Conservation Area

The BCMCA is the least impacted and most pristine marsh occurring in the USJRB, which includes the 6500-acre Blue Cypress Lake. Hydrologic alterations that occurred in BCMCA started with the construction of the Fellsmere Grade (now known as the L-74W levee) on the northern end in the 1920s, then the construction of SR60 along the southern end in the 1930s, and finally the construction of the L-77 flood control levee to the east in 1992. Currently water levels in BCMCA are managed primarily by a large, gated structure (S96-C) that discharges downstream into SJMCA. In 1996, a set of long-term Environmental Hydrologic Criteria (EHC), which outline quantifiable targets intended to reproduce the natural, historic hydrologic regime, was created for BCMCA (Miller et al. 1996). The EHC define optimal flooding depths and durations, timing and intensity of annual water level fluctuations, return frequencies of extreme flooding and drying events, and water level recession rates. Based on hydrologic modeling, it was determined that all the EHC could best be met by allowing continuous low-flow discharges through S-96C, when it was not being operated for flood control. Therefore, a continuous 212 cms–1 discharge through the S-96C structure was implemented in 1996. However, water level monitoring, along with revised hydrologic model results obtained in 2009, revealed that the 212 cms–1 discharge was likely excessive and was potentially over-draining the marsh. Therefore, in 2010, the continuous discharge was reduced, and, in 2012, it was eliminated entirely. Eliminating the low-flow discharge did not change the average water levels but did slightly reduce the number of days the marsh was exposed. Much of the problem with low-flow discharges occurred because of the inability to make minimal discharges through a structure that was designed to make major flood control releases. Specifically, low-flow discharges were much higher than the S-96C structure rating curve predicted.

Prior to the implementation of low-flow discharges, the marsh was dry an average of 43 days per water year (October 1–September 30). However, after discharges began, the average dry-down dramatically increased from 43 to 182 days, with the longest dry periods occurring during drought years in 2001 (280 days), 2007 (338 days), and 2013 (319 days). Reducing and eventually eliminating discharges from BCMCA only resulted in a slight reduction in annual dry-down to 173 days, on average, during 2010–2014. However, if the areal extent of exposure across the entire marsh is considered, the magnitude of exposure was much greater during the discharge period—average marsh exposure (hectare-days) was 32 ha-days prior to discharges, 701 ha-days during discharges, and 484 ha-days following the reduction and eventual cessation of discharges.

As seen in SJMCA, shortened hydroperiods can cause plant community changes and oxidation of peat soils, which could subsequently lead to undesirable water quality changes. To assess these possible impacts, changes in plant communities, length of marsh soil exposure, and water quality trends in the adjacent Blue Cypress Lake were examined. From 2001 to 2008, lower water levels resulted in water lily (slough) habitat conversion to emergent marsh, shrub expansion at the expense of herbaceous and sawgrass communities, and the beginning of succession to forested, hardwood swamp at higher elevations. These are all lines of evidence of that the marsh was drier than historically.

When marsh soils are exposed and oxidize, nutrients are released upon reflooding, and nutrient-laden water can then be transported from the marsh to the lake through surface and subsurface flows. While low-flow discharges from BCMCA were occurring, there were concomitant increases in total phosphorus (TP), total Kjeldahl nitrogen (TKN), and total organic carbon (TOC) concentrations in Blue Cypress Lake (SJRWMD, unpub. data). TP concentrations averaged less than 0.09 mg l–1 prior to discharges but increased afterward, with peaks as high as 0.22 mg l–1, and did not improve even after discharges were discontinued. There was also a marked increase in TKN. However, in contrast to TP trends, once discharges were stopped, there was a significant and rapid decline of TKN to values lower than in the 1980–1990s. Though average TOC was low (20 mg l–1) prior to discharges, annual peaks in TOC increased with marsh exposure up to 32 mg l–1, with a marked decline in TOC after dry season discharges were stopped in 2012. There was an increasing trend in the trophic state index (TSI; an index to classify the trophic level of lakes based on chlorophyll levels and nitrogen and phosphorus concentrations) for the period of record (SJRWMD, unpub. data). The US Environmental Protection Agency (2010) and the Florida Department of Environmental Protection (2016) indicated that Blue Cypress Lake was considered an impaired water body due to high TSI in 2010 and continued to be listed as such in 2016.

Prior to discharges, based on the TSI, Blue Cypress Lake was considered to be of good quality. This shifted to fair quality after low-flow discharges were initiated. With a change in hydrologic schedules in 2010, there was some improvement in TSI, but the lake has not yet returned to good quality. Other improvements in water quality (TKN and TOC) have been realized since 2012, when dry season discharges were eliminated, suggesting that decreasing low-flow water releases from BCMCA marsh was beneficial to lake water quality. However, the District recently became aware that local farms were permitted to apply biosolids (high nutrient by-product of treated wastewater) to agricultural fields adjacent to Blue Cypress Lake beginning in 2006. This complicates our analyses in attributing water quality decline in the lake solely to an increase in marsh exposure.

10.5.5 Future Hydrologic Management

Wetland managers face many challenges in getting the hydrology “right” since it is a critical element in maintaining wetlands and managing for resiliency in the face of climate changes and threats to water availability. Although we have learned several lessons about how wetlands respond to hydrologic alteration, we need to continue efforts to develop tools that predict ecosystem responses to hydrology. In the USJRB, the District will continue to strive to meet long-term EHC in each of the conservation areas by using a number of strategies: installing strategically placed plugs in the C-40 canal in SJMCA to rehydrate the marsh; operating the S252D structure in FDMCA to alleviate flooding and monitoring soil subsidence and accretion to ensure protection of carbon banks and acceleration of carbon sequestration; and determining the relative contribution of marsh dry-down and biosolids application to water quality in Blue Cypress Lake. Finally, it is important to realize the USJRB is vastly different than it was historically. Therefore, it is critical to monitor and develop tools that allow prediction of ecological responses to future changes in hydrology, as a result of human water demand and climate change, and to predict how these changes impact restoration trajectories. Ultimately, the use of these tools will help wetland managers to consider how climate change, with extreme weather variations, will affect the resiliency of USJRB and other wetlands worldwide.

10.6 Assessing Wetland Restoration Using Phosphorus Compound Classes as an Indicator of Biogeochemical Function2

  • K. M. Chowanski
  • L. A. Kunza
  • P. V. Sundareshwar
  • P. J. Pellechia
  • R. A. Gleason
  • C. Sandvik

10.6.1 Introduction

Services provided by managed and natural ecosystems contribute directly or indirectly to human welfare. Ecosystem services have been valued at trillions of dollars (Costanza et al. 1997), with wetland ecosystem services providing one of the highest net global values. While humanity is becoming increasingly dependent on these services, accelerated changes in land use continue to alter the sustainability of these services (Bridges 1978; Foley et al. 2005), resulting in marked reductions in their net output/value (Balmford et al. 2002). Consequently, the global community is increasingly concerned about the condition of these ecosystems and the services they provide (Daily 1997; Millennium Ecosystem Assessment 2003). Since the loss of nonmarketed services usually outweighs the marginal benefits of conversion of these ecosystems (Balmford et al. 2002), compensatory strategies have been implemented to encourage restoration of degraded ecosystems. The goal of wetland restoration is to restore depauperated wetlands to emulate conditions that prevailed prior to their degradation, thus facilitating the recovery of ecosystem services, such as nutrient cycling (Mitsch et al. 1995) and primary production (Mitsch and Gosselink 1993).

While there are various strategic approaches to restore natural ecosystem structure and function, evaluating the relationship between structure and function, or the success of the restoration efforts, has been challenging. Several wetland monitoring and assessment tools have been developed (Brinson 1993; Brinson and Rheinhardt 1996; Rheinhardt et al. 1997; Rheinhardt et al. 1999; Larsen et al. 1994; Karr and Chu 1999; Stevens and Olsen 1999, 2000; Lopez and Fennessy 2002); however, integrating the observed wetland condition data to ecosystem services remains challenging, with metrics exhibiting significant spatial and temporal variability. Development of a single unified picture of wetland ecosystem condition is particularly challenging because biogeochemical functions such as nutrient transformation, energy metabolism, and structural biodiversity features operate at different temporal and spatial scales.

To understand how ecosystems respond to natural or induced change, it is vital to develop indicators of ecosystem function. Approaches in community and ecosystem ecology have focused on assessing the role of species diversity as modulator of ecosystem processes, with mutual interactions among biodiversity changes, ecosystem function, and abiotic factors (Loreau et al. 2001). For example, work in grasslands has suggested that greater plant species richness leads to more efficient uptake of nutrients and greater productivity (Tilman et al. 1996; Hector et al. 1999). In wetland ecosystems, simply measuring extractable nutrients is clearly inadequate, given the complexity of nutrient cycling and forms that can be utilized by a diverse biota. The distribution of phosphorus (P) into various organic and inorganic forms presents a time-integrated snapshot of the history, present structure and functioning of the natural ecosystems, and may represent a unified index capable of assessing wetland condition and effectiveness of restoration efforts.

Several investigators have examined the long-term dynamics of soil organic matter and P in natural or managed ecosystems, including in temperate environments (Anderson et al. 1981; Bowman et al. 1990; Guggenberger et al. 1996), in tropical ecosystems (Solomon and Lehman 2000; Solomon et al. 2002), in pasture soils (Turner et al. 2003; McDowell et al. 2005), in forests (Cade-Menun et al. 2000), as well as in estuarine wetland ecosystems (Sundareshwar et al. 2001). Nitrogen (N) and carbon (C) levels are adjusted through inputs and outputs to the atmosphere; in contrast, P has limited solubility in most soils and is retained in the biotic and abiotic pools, with relatively small losses (Brye et al. 2002; Toor et al. 2005; Richardson 1999). 31P nuclear magnetic resonance (NMR) spectroscopy of soil samples and soil extracts allows visualization of the diverse chemical forms of P (Newman and Tate 1980; Cade-Menun 2005) and has been used to investigate P-forms in forests (Cade-Menun et al. 2000), temperate pastures (Turner et al. 2003), steppe (Amelung et al. 2001), marine lacustrine sediments (Carman et al. 2000), estuaries (Sundareshwar et al. 2001), oceans (Clark et al. 1998), as well as managed agroecosystems (Mahieu et al. 2000; Cade-Menun 2005). Land use and agricultural management practices can alter the form and distribution of soil P (Tiessen et al. 1983; Condron et al. 1990; Guggenberger et al. 1996; Turrión et al. 2000). Retention of P in soils, its tight coupling to C and N cycles (Tate and Salcedo 1988; Gressel et al. 1996; Sundareshwar et al. 2003), and sensitivity of chemical speciation of P to land use changes (Rubæk et al. 1999; Sundareshwar et al. 2001; Solomon et al. 2002; Turner et al. 2003; Cade-Menun 2005; Cade-Menun et al. 2006) suggest that the chemical speciation of P across a restoration gradient can provide insights into the restoration of biogeochemical functions in an ecosystem.

We investigated the trends in P compound classes and changes in vegetation metrics in a network of prairie wetland ecosystems under varying land use as a time-integrated index of wetland ecological condition and ecosystem services delivery. This study is an initial investigation into relationships between P compound classes, biogeochemistry, and plant diversity. Our analytical approach of comparative evaluation of P-forms and vegetation metrics across land uses, to our knowledge, has not been applied in similar systems and constitutes a novel perspective on functional status assessment.

10.6.2 Objectives

This study examined P compound classes across Northern Prairie wetland ecosystems that are under different management regimes. While other studies have compared P-speciation under varying land management, this study explored if changes in P compound classes can serve as a time-integrated index of ecosystem status by comparing fields with similar soil types and climatic conditions in different stages of land use, including undisturbed reference sites. Links between P compound classes and plant community structure across management practices are expected because the chemical nature of soil P-forms and their distribution is primarily governed by biotic and abiotic interactions in the soil matrix over time. Land use change alters ecosystem structure and function, including plant community composition (crop cover, native plants), microbial community, soil organic matter, and nutrient availability. Specifically, we sought to answer the following questions: (1) What is the distribution of compound classes of P in Northern Prairie wetland soils? (2) How does the distribution of P compound classes differ across land use management regimes? (3) Do the changes in P compound classes observed across the land uses mirror changes in plant species diversity?

10.6.3 Approach

Soil samples (0–15 cm deep) were collected from 30 wetlands from the Prairie Pothole Region (PPR) (Fig. 10.7) across three land use categories (reference, restored, and agricultural) located in South Dakota, Iowa, and Montana between July 22 and September 3, 2009. Reference wetlands had no history of drainage or tillage in the wetland or upland zones of catchments and were in native prairie grass. In contrast, agricultural sites had a history of tillage and cropping in the wetland and surrounding uplands. Restored sites were farmed or drained wetlands that were restored by plugging any drains and planting uplands to perennial grassland (Gleason et al. 2008). The restored wetlands in Iowa and Montana had been enrolled in the US Department of Agriculture Conservation Reserve Program (CRP) for 15–20 years. Three of the South Dakota restored wetlands had been under CRP protection for 15–20 years (long-term restoration) and three for less than 5 years (short-term restoration). Of the 30 wetlands, 12 were located in South Dakota and 9 each in Iowa and Montana. Based on their hydroperiods, all the wetlands were classified as seasonal (Stewart and Kantrud 1971).
Fig. 10.7

The Prairie Pothole Region of the United States is outlined in black, with the four black circles indicating the areas of our selected wetlands in Iowa, Montana, North Dakota, and South Dakota

To gauge the effect of hydrologic function, an additional six reference wetlands were sampled from North Dakota that were classified as semipermanent, seasonal, or temporary based on their hydroperiod and as recharge, discharge, or flow through based on their hydrologic function (Euliss et al. 2014). Within each wetland, we collected six to eight samples across three topographic zones based on soil moisture from the marsh at the wetland center to the shoulder slope at the upland edge of the wetland catchment (Fig. 10.8), with a minimum of two samples in each topographic zone. For the wetlands in North Dakota, three cores from the shoulder slope location were collected from each wetland. After collection, soils were packed in ice, shipped to South Dakota School of Mines and Technology, and frozen within 7 days of sampling.
Fig. 10.8

Sample locations within a topographic transect of a wetland. Samples were grouped into the topographic zones based on soil moisture. Soil moisture values are means ± standard deviation, with the letter indicating significant difference at p < 0.05

31P nuclear magnetic resonance (NMR) spectroscopy of soil samples and soil extracts allows us to “visualize” the diverse chemical forms of P (Newman and Tate 1980; Cade-Menun 2005). 31P NMR has been used to investigate phosphorus forms in forests (Cade-Menun et al. 2000), temperate pastures (Turner et al. 2003), steppe (Amelung et al. 2001), marine lacustrine sediments (Carman et al. 2000), estuaries (Sundareshwar et al. 2001), oceans (Clark et al. 1998), as well as managed agroecosystems (Mahieu et al. 2000; Cade-Menun 2005). Soil P diversity provides a time-integrated index of restoration and may occur over realistic length of times needed for restoration of ecosystem condition and services. P compound classes in soil extracts were measured using solution 31P NMR spectroscopy (Sundareshwar et al. 2009). Due to the presence of high concentrations of calcium in some of the soil samples, all samples were pre-treated with 2% HCl for 2 h, prior to extraction with 50 mL 1 M NaOH+0.2 M Na2 EDTA for 24 h and pH adjusted to >12. Classes of phosphorus compounds (or P-forms) identified included inorganic orthophosphate (Ortho P), pyrophosphate (Pyro P), and polyphosphate (Poly P) and organic P-forms orthophosphate monoester (monoester P), orthophosphate diester (diester P), and phosphonate. The number of P-forms present in the extract was counted to obtain P-form richness and the relative abundance of each P-form estimated using peak area and total P in the soil extract. While it is possible to identify individual P-species that are NMR visible in a soil extract, our intent here was to explore the distribution of broad classes of P compounds primarily due to expected redundancies in biogeochemical processes that may be responsible for the production or consumption of these classes of compounds and the practicality of identifying individual species in every sample especially given the number of samples processed for this study. The analytical approach of comparative evaluation of P-forms and vegetation metrics across a chronosequence of cultivated land converted to CRP land uses, to our knowledge, has not been applied in similar systems and constitutes a novel perspective on functional status assessment.

We measured total P in soils and in the extract for solution 31P NMR analysis, soil C, soil N, and soil moisture on homogenized soil samples sieved through 1 mm mesh. Relative abundance of P-forms in soil extracts were calculated by measuring the area under the curve for each compound class and the total P in the extract. Total soil P and total P in the extract for solution 31P NMR analysis were measured colorimetrically with a Lachat QuikChem® 8500 Series 2 FIA Automated Ion Analyzer method 10-115-01-1-E. Soil moisture was measured gravimetrically by drying the soil samples to a constant weight, while soil nitrogen and soil carbon was measured using a Thermo Scientific* FLASH 2000 Series CHNS/O Analyzer.

Vegetation data was collected from the 12 South Dakota wetlands between July 13 and 27, 2008, within a 1 m2 plot centered on the soil sample location. The vegetation data was used to calculate additional metrics such as species richness, native species richness, mean coefficients of conservatism (C Score; Northern Great Plains Floristic Quality Assessment Panel 2001), and Floristic Quality Index (FQI). Species richness is the number of individual species present in the plot, while native species richness counts only the native species, and C values represent the sensitivity of plants to disturbance (e.g., higher values assigned to plants less tolerant of disturbance). The mean C Score and the FQI were computed using Eqs. (10.1) and (10.2), respectively.

$$ \mathrm{Mean}\ C\ \mathrm{Score}=\frac{\sum C\ \mathrm{Score}}{\mathrm{species}\ \mathrm{richness}} $$
(10.1)
$$ \mathrm{FQI}=\mathrm{Mean}\ C\ \mathrm{Score}\times \sqrt{\mathrm{native}\ \mathrm{species}\ \mathrm{richness}} $$
(10.2)

These metrics of plant community structure were compared to the relative abundance of Ortho P and P-form richness. Data were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s honestly significant difference test on all metrics to compare land use, topographic gradient, and land use within topographic zones using the R statistical analysis package (R Core Team 2012).

10.6.4 Key Findings

  1. 1.

    P diversity varied along a topographic gradient within wetland catchments.

     
Across the topographic zones from the marsh to the shoulder slope, total P and Ortho P decreased, while monoester P, diester P, phosphonate, and overall P-form richness increased (Fig. 10.9). Soil C and N were highest in the marsh (5.1% and 0.5 %, respectively) and were 20% and 40% less in the shoulder slope, respectively. Total soil P and the relative abundance of Ortho P and monoester P were distinct for each topographic zone (Fig. 10.9). Mean P-form richness increased from 3.7 in the marsh to 4.3 in the shoulder slope (Fig. 10.9B). From the marsh to the wet meadow and shoulder slope, monoester P increased by 20 and 35%, total P decreased by 24 and 51 %, and Ortho P (Fig. 10.9D) decreased by 22 and 50%, respectively. Extraction efficiencies ranged from 38% in the shoulder slope to 57% in the marsh and were comparable to other studies (Cade-Menun 2005).
Fig. 10.9

Soil P concentration (A), P-form richness (B), relative abundance of Ortho P (C), and relative abundance of monoester P (D). Topographic zones are on the x axes: marsh (M), wet meadow (WM), and shoulder slope (SS). The black line represents the median, the edges of the box are the first and third quartiles, the whiskers extend beyond the quartiles by 1.5 times the inner quartile range, and circles are outliers. Different letters indicate significant difference at p < 0.05

Across a topographic gradient, plant species diversity showed statistically significant differences across land use categories in the shoulder slope topographic zone, with greatest diversity in reference wetlands, intermediate richness in restored sites, and lowest in wetlands under agriculture (data not shown). Native plant richness showed a similar trend; however the long-term restored site showed lower native plant species richness than the short-term restored site and was not significantly different from the agricultural sites. We found that while soil total P declined across a topographic gradient from the center of the wetland (marsh) through middle (wet meadow) to the edge (shoulder slope), P-species diversity was significantly greater in the shoulder slope region. This suggests that the optimal location for sampling wetlands for a comparative evaluation of the status of the soil biogeochemical function is the shoulder slope.
  1. 2.

    Soil P diversity and vegetation metrics varied along a land use gradient.

     
Total soil P and P-form richness varied across the land use categories for samples from the shoulder slope topographic zone (Fig. 10.10). The mean total soil P values were similar in reference and short-term restored wetlands but were significantly lower than that observed in agricultural wetlands. While the long-term restored sites supported intermediate mean total soil P value, they were not significantly different from other land uses. In contrast, mean P-form richness was highest in the reference and long-term restored wetlands (5.1 and 4.7, respectively) and lowest in the short-term restored and agricultural wetlands (3.4 for both) (Fig. 10.10). Most of the reference (95%) and long-term restored (90%) wetlands had measureable amounts of polyphosphate, pyrophosphate, and/or phosphonate, while only a third of the short-term restored and agricultural wetlands contained any of these P-forms.
Fig. 10.10

Left: total soil P differed significantly across land uses, with reference and short-term restored wetlands harboring the lowest abundance of total soil P, while the agricultural lands had the highest. In contrast, P-form richness (right) was greatest in the reference and long-term restored sites, with similar values for agricultural and short-term restored wetlands

The soil C and N values also differed significantly among land uses. The reference wetlands had significantly greater amounts of soil C and N at 5.2 ± 1 % and 0.4 ± 0.1 % (p < 0.05), respectively, when compared to all other land use categories, which shared similar values (data not shown). The mean C:N:P ratio ranged from 162:12:1 for the reference wetlands to 67:6:1 in the agricultural wetlands.

Across the land use gradient, the mean C Score and FQI followed a similar trend as the species richness (Fig. 10.11). The relative contribution of monoester P to total P (expressed as % monoester P) in the soils was positively correlated with the plant species richness across the land use gradient (Pearson correlation = 0.85; linear regression r2 = 0.71; p < 0.0001), with reference wetlands harboring greatest plant species diversity and % monoester P, while the agricultural sites had the lowest diversity and lowest % monoester P. The restored sites support intermediate values (data not shown). Similarly, the relative contribution of orthophosphate to total soil P (expressed as % orthophosphate) was negatively correlated with coefficient of conservation (mean C Score) (r2 = 0.44; p = 0.00023). These findings indicate a link between plant diversity and soil P diversity, suggesting a coupling between the structural restoration and the restoration of soil biogeochemical functions.
Fig. 10.11

Species richness, mean C Score, and FQI across the land use categories for the SD vegetation samples. Plant species richness significantly differs across land use gradient. Restored sites harbor intermediate plant species richness. Native plant species richness was also greatest in reference wetlands and lowest in agricultural land use. However, the trend in restored sites is counterintuitive with short-term resorted wetlands which did not differ significantly from the reference wetlands sites, while values for long-term restored wetlands and agricultural lands were similar. Plant species richness (A), native plant species richness (B), mean C score (C), and FQI (D) for shoulder slope samples. Land use categories are on the x axes: reference (RF), long-term restored (LT), short-term restored (ST), and agricultural (AG). The black line represents the median, the edges of the box are the first and third quartiles, the whiskers extend beyond the quartiles by 1.5 times the inner quartile range, and circles are outliers. Different letters indicate significant difference at p < 0.05

10.6.5 Management Implications

One of the key objectives of this study was to evaluate if soil P-forms can be used as a tool for evaluating the status of soil biogeochemical conditions across wetlands under various land uses. Soil carbon and soil nitrogen status are often used as indicators for evaluating the restoration status of wetlands. Our analyses show that although soil carbon and soil nitrogen values were significantly greater in reference wetlands than in restored or agricultural land uses, they were not sufficient to discern changes among the chronosequence of restored wetlands (i.e., restoration age). Soil carbon and soil nitrogen often take upward of 30 years to show discernible trends in restored wetlands. In contrast, P-form richness across the land uses was greatest in the reference wetlands and long-term restored wetlands and lower in short-term restored and agricultural lands. Soil P-form diversity provides a time-integrated index of restoration over time periods appropriate for evaluating success of restoration of ecosystem condition and services.

The results show that restoration also alters the partitioning of soil P-forms, with P being partitioned into more diverse forms in reference wetlands. When evaluated on the basis of the relative contribution of orthophosphate to total soil P versus contribution of all-other P-forms (% orthophosphate vs. % all-other P-forms), the reference wetlands harbor the lowest proportion of orthophosphate while supporting the greatest proportion of all-other forms of P. The relative distribution analyses yield a linear relation with a negative slope with reference wetlands and agricultural lands clustered at opposite ends with the restored wetlands in the middle (Fig. 10.12). A similar relationship was observed for land uses across all South Dakota, Iowa, and Montana wetlands. It is likely that the spread observed in this analysis is influenced by history of the land use as well as the availability of reliable reference conditions (Fig. 10.12). Nevertheless, our results indicate that soil P NMR analysis is a robust tool to evaluate the status of the soil biogeochemical restoration in wetlands. This technique, however, is only suitable for evaluating the restoration efforts in wetlands where there has been a direct disturbance to soil as a result of conversion to agriculture. The applicability of this technique in wetlands, where the wetland soil is not disturbed or differ in their basin classification, remains to be evaluated. For example, similar analyses on soil samples from North Dakota wetlands that were all categorized as reference wetlands, but which differed in their hydrologic conditions, did not yield a discernible trend (data not shown).
Fig. 10.12

Relative abundance of Ortho P versus all-other P-forms for shoulder slope samples from South Dakota wetlands (left) and from Iowa and Montana wetlands (right). Land use categories are represented by point shape: circles are reference wetlands, upward pointing triangles are long-term restored wetlands, downward pointing triangles are short-term restored wetlands, and squares are agricultural wetlands. For samples from Iowa and Montana wetlands, all restored wetland samples were from long-term restored wetlands. Note that for samples from the three states all reference wetlands shared similar relative proportion of orthophosphate versus all other forms of P with orthophosphate comprising <25% and all other forms comprising >75%. The larger spread in agricultural samples across the sampled states may reflect differences in land use history as well as in the quality of the reference wetlands available in the region

Since chemical speciation of P is a function of biotic and abiotic processes which are affected by land use, we expect that restoration of these conditions in wetlands will result in re-establishment of soil P diversity. Hence, soil P diversity will progressively increase with the age of restoration to asymptote to the forms observed in native or reference wetlands. This will provide a measure of ecosystem condition and help evaluate the trajectory of ecosystem restoration. Greater P diversity implies partitioning of P into various pools, which differ in their bioavailability and turnover. For example, whereas P-forms such as inorganic orthophosphate or pyrophosphate are readily bioavailable (Condron et al. 1985), other forms such as phosphonates and diesters may be of limited bioavailability as their turnover is controlled by the activity of specific microbial communities (Kononova and Nesmeyanova 2002; Dyhrman et al. 2006) and prevailing environmental conditions such as temperature, precipitation, and pH (Sumann et al. 1998). Thus, greater P diversity in native ecosystems likely contributes to the measured increase in nutrient retention in undisturbed ecosystems compared to cultivated lands (Bruland et al. 2003). Therefore, our findings provide a tool to evaluate the restoration of such ecosystem services.

It is plausible that differences in environmental conditions and microbial communities among cultivated, restored, and native wetlands contribute to the observed differences in P-forms. For instance, while organic phosphorus compounds (e.g., phosphonates) occur naturally (Rosenberg 1964; Benitez-Nelson et al. 2004; Koukol et al. 2008) and are found in commonly used weed killers, the presence of phosphonates in our study sites indicates that production of these compounds is outpacing their turnover. While the native and restored wetlands have been shown to share similar microbial community composition, unlike farmland (Potthoff et al. 2005; Hartman et al. 2008), soil microbial diversity was greatest in the farmland and lowest in the native wetland (Hartman et al. 2008). Such an inverse trend between soil P diversity (greatest in native wetlands) and microbial diversity (lowest in native wetlands) implies that soil P diversity is likely not a function of greater bacterial diversity per se and instead is a result of restored biological communities leading to recovery of specific biogeochemical functions. Since soil microbes can be important regulators of plant productivity and diversity (van der Heijden et al. 2008), and, vice versa, it could be postulated that P-form diversity likely corresponds to trends in plant community composition as well. Simply put, re-establishment of soil P-forms also indicates restoration of biological community and abiotic conditions and thus may serve as a unified measure of ecosystem condition. Similar patterns in soil P diversity across land use among wetlands from multiple ecoregions implies that this approach may serve as a unified metric for assessing wetland conditions nationally and can complement existing methods of assessing restoration of ecosystem function.

10.6.6 Acknowledgments

This work was supported US Department of Agriculture, Natural Resources Conservation Service, and Great Plains Cooperative Ecosystem Studies Unit contract number 58-7482-9-522. The US Geological Survey Northern Prairie Wildlife Research Center collected soil samples for this project. Sushil Guatam, Trisha Michael, Kishore Machani, and Ashley Trennepohl assisted with laboratory analyses. P. V. Sundareshwar was not at the US Agency for International Development when the research for the current paper was conducted. The views and opinions expressed in this paper are those of the authors and not necessarily the views and opinions of the US Agency for International Development. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government.

10.7 Summary and Conclusions

In this chapter, we summarized and synthesized the content of a session at the 10th INTECOL International Wetlands Conference, held in September of 2016 in Changshu China, entitled “Building Resiliency to Changing Conditions in Wetland Management and Restoration Projects on Multiple Temporal and Spatial Scales.” We provided an overview of five of the seven presentations that address considerations for building resiliency in wetlands to changing climatic conditions using a variety of management and restoration approaches. Multiple temporal and spatial scales were considered, beginning with a comprehensive global overview of wetlands and climate change and an examination of the interaction between climate and wetlands through geologic time, followed by project- and site-specific case studies that focus on the development of resiliency to global climate change and how to evaluate associated stressors.

Resiliency of wetland ecosystems to climatic and anthropogenic stressors has come to the forefront of current research and management consideration in recent years. Because wetlands have a disproportionately large role in the global carbon cycle, in comparison to their worldwide areal coverage, alterations to wetlands from climate change or other anthropogenic activities are of significant concern. The ability of wetlands to store significant amounts of organic carbon is due, to a large degree, to high primary productivity coupled with low respiration created by anaerobic conditions often found in these ecosystems. When we disrupt natural carbon sequestration processes by disturbing or converting functioning wetlands to developed landscapes, we are often reducing carbon removal potential and increasing carbon emissions to the atmosphere. Likewise, changes to climate, such as increasing temperatures and alterations to rainfall patterns may also have a similarly important effect. The understanding of how wetlands function in the global carbon cycle highlights the importance of protecting existing wetlands as significant soil carbon banks and preventing their conversion, either by climate or land use changes, to disturbed systems that function as net carbon emitters. Wetlands are particularly sensitive to the impacts of climate change because they exist at the transition between dry land and aquatic ecosystems. Even small changes in hydrologic cycles can result in significant changes to wetland hydrology, soils, vegetation, and fauna. Hence, it is important to identify Best Management Practices that will promote ecosystem resilience and maintenance of ecosystem services in the face of climate change stressors. Understanding the history of climate change can aid us in preparing for the potential impacts to the current landscape and how we might prioritize wetland conservation.

One way to predict the future response to climate change is to examine ancient ecosystems that existed when our planet was significantly warmer than it is today. We utilized the 100-million-year history of polar wetlands as an example of a mechanism to predict or envision what the future may look like under a changing global climate. Information contained in the polar fossil record may allow us to glean useful information on the evolutionary processes associated with changing vegetation communities, which then allows us to better predict the eventual structure and composition of polar ecosystems that we might expect to see in the future. Predicting the effects of innumerable biotic (mycorrhizal associations, plant species composition) and abiotic (temperature, methane, light) relationships and complexities makes it challenging to determine what a green Arctic might look like. However, it appears that climate change will create negative feedbacks, in the form of additional primary productivity and carbon sequestration in polar areas. As global climate continues to warm, the treeless, polar regions will experience the greatest change in the shortest time, and greenhouse conditions will encourage vegetative growth in these new, ice-free regions. In an ice-free world, the total wetland area could more than double in areal extent, giving wetlands an even more prominent role in the evolution of future climate and environment. As global mean temperature increases, vegetation zones and species ranges will initially migrate both altitudinally and latitudinally. This results in existing herbaceous vegetation of glacial and tundra areas giving way to encroaching boreal shrubs and trees, thus providing a negative feedback to increased climate change via increased carbon sequestration in this area of the world.

To illustrate the local effects of global climate change, we discussed how both coastal and inland wetlands could be affected, either directly or indirectly, in their resiliency and ecological functioning. In coastal ecosystems, sea level rise (SLR) is a significant driving force shaping wetlands today and will continue to be so in the foreseeable future. Rising water levels are forcing landward migration of coastal wetland ecosystems globally as hydrologic changes increase the inundation of terrestrial habitat. Unfortunately, a majority of the human population around the world lives close to the coast, and, as such, little room for coastal wetland expansion exists in many places due to human development of the coastline and adjacent lands. The Florida Coastal Everglades and Florida Gulf Coast both present exceptional opportunities to visualize this landward migration of wetlands and aid in helping us to anticipate future management needs. In the Everglades National Park, where fresh water flows into Florida Bay, there is natural encroachment of mangroves (woody species) into the emergent freshwater, herbaceous marshes upstream. As SLR continues, it is estimated that mangroves may take over large portions of what is now freshwater wetlands. Unfortunately, the immense stores of organic carbon in the soils of these marshes are at risk as “peat collapse” is a widespread observation in this transition zone. However, mangroves are predicted to replace soil carbon stores over time as they become the dominant vegetation. This negative feedback to climate change will not be present in areas where coastal marshes are lost to SLR. In South Florida, king tides currently flood downtown Miami annually creating significant damage to infrastructure and private property. While municipalities look for engineering solutions to this problem, there is currently little provision of lands for wetland habitat in the future. An anthropogenic gradient of coastal development density exists on Florida’s east coast that enables assessment of the ecological implications of restricted landward migration of wetlands in response to SLR. Investigation of this gradient suggests that Central Florida has significantly more potential for development of coastal wetlands in the face of SLR and North Florida has the highest due to lower density of coastal armoring and urban development. Proper planning in low to moderately developed landscapes should take SLR into consideration (via ecosystem services evaluation) and incorporate areas for wetland expansion/migration wherever possible. Failure to do so will cause long-term loss of coastal wetlands in Florida and will result in loss of large-scale carbon sequestration along the coast and thus create a positive feedback (i.e., further increase warming) potential for climate change.

While climate change effects in coastal, tidal ecosystems are more obvious and direct (i.e., as a result of SLR and salinization), those in fresh water, inland systems may be more subtle. Inland systems may be variably impacted through changes in species distribution and phenology, increased productivity due to higher temperatures, longer growing seasons, and increased CO2 supply and by changes in weather patterns and water availability. Because Central Florida is projected to have an extreme risk for water shortages by 2050 due to increased human water demand, increased evapotranspiration, and rainfall deficits, it is extremely important to manage water resources in a way that sustains wetlands while providing flood control and water supply for human needs. We utilized examples of three freshwater marshes located at the headwaters of Florida’s largest river, the St. Johns, to illustrate potential effects of altered hydrology due to climate change. Because hydrology is a major driving force of ecological function in freshwater wetlands, as well, alterations to the natural hydro-pattern can change ecosystem structure and function by changing plant distributions, water quality, carbon sequestration, and soil accretion and loss. In the St. Johns Marsh Conservation Area (SJMCA), drained conditions have resulted in a tremendous loss of soil (30 cm over 9 years), a shift in the plant community from herbaceous to woody, increased nutrient loading for phosphorus and nitrogen, increased CO2 flux to the atmosphere, and increased evapotranspiration. In the Fort Drum Marsh Conservation Area (FDMCA), deeper and prolonged inundation did not result in the expected shift of vegetation communities to open water and floating-leaved plant communities. Instead, the extant plant communities adapted by increasing belowground productivity up to 12–40 times, which likely accounted for the observed 21 cm rise in surface elevation over a 24-year period. In Blue Cypress Marsh Conservation Area (BCMCA), dry season discharges increased the annual exposure of marsh soils from 43 to 182 days. Lower water levels resulted in slough habitat conversion to emergent marsh, shrub expansion at the expense of herbaceous and sawgrass communities, and the beginning of succession to forested, hardwood swamp at higher elevations. Following seasonal reflooding, water quality in the adjacent Blue Cypress Lake declined due to increased concentrations of phosphorus, nitrogen, and organic carbon, potentially reflecting nutrient releases from organic soil oxidation in the surrounding marsh. With these examples, we contend that continued efforts are needed to develop tools that predict ecosystem responses to hydrology and, ultimately, help wetland managers to consider how climate change, with extreme weather variations, will affect the resiliency of the Upper St. Johns River Basin and other wetlands worldwide. Further, nutrient pollution associated with soil subsidence may be a significant issue as excessive nutrient availability can degrade ecosystem health.

With respect to nutrient cycling, often phosphorus (P) is considered the most significant limiting nutrient in freshwater wetlands. When utilizing nutrients such as P as indicators of ecosystem health and recovery, there can be significant difficulty in evaluating the soil biogeochemical functions that are critical for restoration of ecosystem services. In this last example, we demonstrated that 31P nuclear magnetic resonance spectroscopy is an excellent tool to evaluate changes in soil biogeochemical functions as a result of management actions. By examining the chemical forms of P, we documented a decrease in soil P diversity (a functional attribute) upon conversion to agriculture but recovery following restoration activities. P-form richness varies with landscape position, with significantly greater richness observed at the drier marsh shoulder than in the wetter marsh center. When disaggregated by land use categories, the relative contribution of orthophosphate to the visible P pool progressively decreases from the cultivated to restored to reference wetlands. Re-establishment of soil P-forms after restoration likely reflects the biogeochemical partitioning of the soil P. Relative changes in the soil P-forms reflect the extent of re-establishment of soil biogeochemical functions and native plant communities and provide a uniform metric to assess the condition of restored wetlands. We contend that use of tools such as this will enable managers to address issues of eutrophication and re-establishment of ecosystem function after restoration efforts have been enacted. Perhaps more importantly, managers will be able to utilize this technique to indicate significant nutrient cycling changes in wetlands exposed to climate-induced changes and restoration efforts.

The case studies presented here, while diverse in nature, were selected to provide background and historical perspective on changes in wetlands associated with climate change, thereby illustrating why understanding this process is important. Additionally, these examples highlight potential changes to wetland vegetation communities and carbon storage in soils and, in some cases, predict future changes that may occur due to climate change in the form of SLR and altered hydrology. The final case study provides advanced tools for monitoring changes at the biogeochemical scale, which is likely to be one of the first indicators of change to be detected. Overall, the case studies presented here enable us to learn techniques and approaches to address the current and future stresses (both natural and anthropogenic) on wetland ecosystems around the world, with the common theme of carbon sequestration and biogeochemical cycling that is often a noted ecosystem service associated with coastal and freshwater wetland systems. We believe that these studies have significant utility in providing guidance to resource managers and wetland researchers alike in addressing wetland issues in a changing climate. Furthermore, we must plan for and anticipate how our ecosystems and wetlands are changing and look for ways to maximize ecosystem/wetland and human community health, as well as delivery of ecosystem services in the face of these synergistic challenges.

Footnotes

  1. 1.

    Development of climate change scenarios requires the selection of emission scenarios that are based on plausible projections of future emission of greenhouse gases and aerosols. The Arctic Climate Impact Assessment (2005) used the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES), which consisted of the A2 and B2 emission scenarios. The A2 emission scenario emphasized economic development and continuous population growth, whereas the B2 scenario focused more on environmental concerns, intermediate levels of economic growth, and population growth that is slower than the A2 scenario.

  2. 2.

    P. V. Sundareshwar is the corresponding author for this section.

References

  1. Adamus PR (2007) Best available science for wetlands of Island County, Washington: review of published literature a report prepared in response to critical areas ordinance updating requirements for wetlands Island County Department of Planning and Community Development. http://people.oregonstate.edu/~adamusp/Puget Sound BAS & Critical Areas/IslandCountyWA/Adamus2006_IslandCoBAS.pdf. Accessed 21 Jan 2018
  2. Adler A, Karacic A, Weih M (2008) Biomass allocation and nutrient use in fast-growing woody and herbaceous perennials used for phytoremediation. Plant Soil 305:189–206CrossRefGoogle Scholar
  3. Agerer R (1987) Colour atlas of ectomycorrhizae. Einhorn, Schwäbisch GmündGoogle Scholar
  4. AMAP (2017) Snow, water, ice and permafrost in the Arctic (SWIPA) 2017. Arctic Monitoring and Assessment Programme (AMAP), Oslo, NorwayGoogle Scholar
  5. Amelung W, Rodionov A, Urusevskaja IS, Haumaier L, Zech W (2001) Forms of organic phosphorus in zonal steppe soils of Russia assessed by 31P NMR. Geoderma 103:335–350CrossRefGoogle Scholar
  6. Anderson DW, Saggar S, Bettany JR, Stewart JWB (1981) Particle size fractions and their use in studies of soil organic matter: I. The nature and distribution of forms of carbon, nitrogen and sulfur. Soil Sci Soc Am J 45:767–772CrossRefGoogle Scholar
  7. Anderson MG, Barnett A, Clark M, Sheldon AO, Prince J, Vickery B (2016a) Resilient and connected landscapes for terrestrial conservation. The Nature Conservancy, Eastern Conservation Science, Boston, MA. http://nwblcc.org/wp-content/uploads/2016/08/Anderson-et-al.-2016-Resilient_and_Connected_Landscapes_For_Terrestial_Conservation.pdf. Accessed 21 Jan 2018Google Scholar
  8. Anderson MG, Barnett A, Clark M, Ferree C, Sheldon AO, Prince J (2016b) Resilient sites for terrestrial conservation in Eastern North America 2016 Edition. The Nature Conservancy, Eastern Conservation Science, Boston, MA. http://climatechange.lta.org/wp-content/uploads/cct/2016/07/Resilient_Sites_for_Terrestrial_Conservation.pdf. Accessed 21 Jan 2018Google Scholar
  9. Anisimov OA, Vaughan DG, Callaghan TV, Furgal C, Marchant H, Prowse TD, Vilhjálmsson H, Walsh JE (2007) Polar regions (Arctic and Antarctic). In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Cambridge University Press, Cambridge, pp 653–685Google Scholar
  10. Arbuzov SI, Volostnov AV, Rikhvanov LP, Mezhibor AM, Ilenok SS (2011) Geochemistry of radioactive elements (U, Th) in coal and peat of northern Asia (Siberia, Russian Far East, Kazakhstan, and Mongolia). Int J Coal Geol 86:318–328CrossRefGoogle Scholar
  11. Arctic Climate Impact Assessment (2005) Arctic climate impact assessment. ACIA overview report. Cambridge University Press, CambridgeGoogle Scholar
  12. Balmford A, Bruner A, Cooper P, Costanza R, Farber S, Green RE, Jenkins M, Jefferiss P, Jessamy V, Madden J, Munro K, Myers N, Naeem S, Paavola J, Rayment M, Rosendo S, Roughgarden J, Trumper K, Turner RK (2002) Economic reasons for conserving wild nature. Science 297:950–953PubMedCrossRefGoogle Scholar
  13. Barbier EB, Hacker SD, Kennedy C, Koch EW, Stier AC, Silliman BR (2011) The value of estuarine and coastal ecosystem services. Ecol Monogr 81:169–193CrossRefGoogle Scholar
  14. Beauregard F, de Blois S (2014) Beyond a climate centric view of plant distribution: edaphic variables add value to distribution models. PLoS One 9(3):e92642.  https://doi.org/10.1371/journal.pone.0092642 PubMedPubMedCentralCrossRefGoogle Scholar
  15. Benitez-Nelson CR, O’Neill L, Kolowith LC, Pellechia PJ, Thunell R (2004) Phosphonates and particulate organic phosphorus cycling in an anoxic marine basin. Limnol Oceanogr 49:1593–1604CrossRefGoogle Scholar
  16. Bochnak AMK, Osborne TZ, Ponzio KJ (2015) Balancing water supply and flood control management with the protection of peat-based subtropical wetlands in Florida. Paper presented at the annual conference of the Society of Wetland Scientists, Providence, RI, USA, 3 June 2015Google Scholar
  17. Boisvert-Marsh L, Périé C, de Blois S (2014) Shifting with climate? Evidence for recent changes in tree species distribution at high latitudes. Ecosphere 5:83.  https://doi.org/10.1890/ES14-00111.1 CrossRefGoogle Scholar
  18. Boucek RE, Rehage JS (2015) A tale of two fishes: using recreational angler records to examine the link between fish catches and floodplain connections in a subtropical river. Estuar Coast 38(S1):124–135CrossRefGoogle Scholar
  19. Bowman RA, Reeder JD, Lober RW (1990) Changes in soil properties in a central plains rangeland soil after 3, 20 and 60 years of cultivation. Soil Sci 150:851–857CrossRefGoogle Scholar
  20. Brenner M, Schelske CL, Keenan LW (2001) Historical rates of sediment and nutrient accumulation in marshes of the Upper St. Johns River, Florida, USA. J Paleolimnol 26:241–257CrossRefGoogle Scholar
  21. Bridges EM (1978) Interactions of soil and mankind in Britain. J Soil Sci 29:125–139CrossRefGoogle Scholar
  22. Bridgham SD, Megonigal JP, Keller JK, Bliss NB, Trettin C (2006) The carbon balance of North American wetlands. Wetlands 26(4):889–916.  https://doi.org/10.1672/0277-5212(2006)26[889:TCBONA]2.0.CO;2 CrossRefGoogle Scholar
  23. Bridgham SD, Moore TR, Richardson CJ, Roulet NT (2014) Errors in greenhouse forcing and soil carbon sequestration estimates in freshwater wetlands: a comment on Mitsch et al. 2013. Landscape Ecol 29(9):1481–1485.  https://doi.org/10.1007/s10980-014-0067-2 CrossRefGoogle Scholar
  24. Brinson MM (1993) A hydrogeomorphic classification for wetlands. Wetlands Research Program Technical Report WRP-DE-4, U.S. Army Corps of Engineers, Vicksburg, MSGoogle Scholar
  25. Brinson MM, Rheinhardt RD (1996) The role of reference wetlands in functional assessment and mitigation. Ecol Appl 6:69–76CrossRefGoogle Scholar
  26. Bruland GL, Hanchey MF, Richardson CJ (2003) Effects of agriculture and wetland restoration on hydrology, soils, and water quality of a Carolina bay complex. Wetl Ecol Manag 11:141–156CrossRefGoogle Scholar
  27. Brye KR, Andraski TW, Jarrell WM, Bundy LG, Norman JM (2002) Phosphorus leaching under a restored tallgrass prairie and corn agroecosystems. J Environ Qual 31:769–781PubMedCrossRefGoogle Scholar
  28. Budny ML, Benscoter BW (2016) Shrub encroachment increases transpiration water loss from a subtropical wetland. Wetlands 36:631–638CrossRefGoogle Scholar
  29. Cade-Menun BJ (2005) Characterizing phosphorus in environmental and agricultural samples by 31P nuclear magnetic resonance spectroscopy. Talanta 66:359–371PubMedCrossRefGoogle Scholar
  30. Cade-Menun BJ, Berch SM, Preston CM, Lavkulich LM (2000) Phosphorus forms and related soil chemistry of Podzolic soils on northern Vancouver Island. I. A comparison of two forest types. Can J Forest Res 30:1714–1725CrossRefGoogle Scholar
  31. Cade-Menun BJ, Navaratnam JA, Walbridge MR (2006) Characterizing dissolved and particulate phosphorus in water with 31P nuclear magnetic resonance spectroscopy. Environ Sci Technol 40:7874–7880PubMedCrossRefGoogle Scholar
  32. Cao M, Gregson K, Marshall SJ (1998) Global methane emission from wetlands and its sensitivity to climate change. Atmos Environ 32:3293–3299CrossRefGoogle Scholar
  33. Carman R, Edlund G, Damberg C (2000) Distribution of organic and inorganic phosphorus compounds in marine and lacustrine sediments: a 31P NMR study. Chem Geol 163:101–114CrossRefGoogle Scholar
  34. Chambers LG, Reddy KR, Osborne TZ (2011) Short-term response of carbon cycling to salinity pulses in a freshwater wetland. Soil Sci Soc Am J 75:2000–2007CrossRefGoogle Scholar
  35. Chambers LG, Osborne TZ, Reddy KR (2013) Effect of salinity pulsing events on soil organic carbon loss across an intertidal wetland gradient: a laboratory experiment. Biogeochemistry 115:363–383CrossRefGoogle Scholar
  36. Chambers LG, Davis SE, Troxler T, Boyer JN, Downey-Wall A, Scinto LJ (2014) Biogeochemical effects of simulated sea level rise on carbon loss in an Everglades mangrove peat soil. Hydrobiologia 726:195–211CrossRefGoogle Scholar
  37. Chmura GL, Anisfeld SC, Cahoon DR, Lynch JC (2003) Global carbon sequestration in tidal, saline wetland soils. Global Biogeochem Cy 17(4):1–11.  https://doi.org/10.1029/2002GB001917 CrossRefGoogle Scholar
  38. Christie J, Kusler J (2009) Recommendations for a national wetlands and climate change initiative. https://www.aswm.org/pdf_lib/recommendations_2008_112008.pdf. Accessed 21 Jan 2018
  39. Clark LL, Ingall ED, Benner R (1998) Marine phosphorus is selectively remineralized. Nature 393:426CrossRefGoogle Scholar
  40. Condron LM, Goh KM, Newman RH (1985) Nature and distribution of soil phosphorus as revealed by a sequential extraction method followed by 31P-NMR analysis. J Soil Sci 36(2):199–207CrossRefGoogle Scholar
  41. Condron LM, Frossard E, Tiessen H, Newman RH, Stewart JWB (1990) Chemical nature of organic phosphorus in cultivated and uncultivated soils under different environmental conditions. J Soil Sci 41(1):41–50CrossRefGoogle Scholar
  42. Costanza R, d’Arge R, de Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill RV, Paruelo J, Raskin RG, Sutton P, van den Belt M (1997) The value of world’s ecosystem services and natural capital. Nature 397:253–260CrossRefGoogle Scholar
  43. Cox DT, Vosatka ED, Moody HL, Conner LL (1982) D-J F-25 St. Johns River fisheries resources completion report. Florida Game and Fresh Water Fish Commission, Tallahassee, FLGoogle Scholar
  44. Craft CB, Richardson CJ (1993a) Peat accretion and N, P, and organic C accumulation in nutrient-enriched and unenriched Everglades peatlands. Ecol Appl 3:446–458PubMedCrossRefGoogle Scholar
  45. Craft CB, Richardson CJ (1993b) Peat accretion and phosphorus accumulation along a eutrophication gradient in the northern Everglades. Biogeochemistry 22:133–156CrossRefGoogle Scholar
  46. Craft CB, Richardson CJ (1998) Recent and long-term organic soil accretion and nutrient accumulation in the Everglades. Soil Sci Soc Am J 62:834–843CrossRefGoogle Scholar
  47. Craft CB, Clough J, Ehman J, Joye S, Park R, Pennings S, Gou H, Machmuller M (2008) Forecasting the effects of accelerated sea-level rise on tidal marsh ecosystem services. Front Ecol Environ 7:73–78CrossRefGoogle Scholar
  48. Daily GC (1997) Nature’s services: societal dependence on natural ecosystems. Island Press, Washington, DCGoogle Scholar
  49. DeLaune RD, White JR (2012) Will coastal wetlands continue to sequester carbon in response to an increase in global seal level?: a case study of the rapidly subsiding Mississippi River deltaic plain. Climatic Change 110:297–314CrossRefGoogle Scholar
  50. Downs RJ (1962) Photocontrol of growth and dormancy in woody plants. In: Kozlowski TZ (ed) Tree growth. Ronald, New York, pp 133–148Google Scholar
  51. Dyhrman ST, Chappell PD, Haley ST, Moffett JW, Orchard ED, Waterbury JB, Webb EA (2006) Phosphonate utilization by the globally important marine diazotroph Trichodesmium. Nature 439:68–71PubMedCrossRefGoogle Scholar
  52. Erwin KL (2009) Wetlands and global climate change: the role of wetland restoration in a changing world. Wetl Ecol Manag 17(1):71–84.  https://doi.org/10.1007/s11273-008-9119-1 CrossRefGoogle Scholar
  53. Euliss NH Jr, Mushet DM, Newton WE, Otto CRV, Nelson RD, LaBaugh JW, Scherff EJ, Rosenberry DO (2014) Placing prairie pothole wetlands along spatial and temporal continua to improve integration of wetland function in ecological investigations. J Hydrol 513:490–503CrossRefGoogle Scholar
  54. Fagherazzi S, Kirwan ML, Mudd SM, Guntenspergen GR, Temmerman S, D’Alpaos A, van de Koppel J, Rybczyk JM, Reyes E, Craft CB, Clough J (2012) Numerical models of salt marsh evolution: ecological, geomorphic, and climate factors. Rev Geophys 50:28CrossRefGoogle Scholar
  55. Fall C (1982) Water quality monitoring annual report, 1979-1981. Technical report no. 17, St. Johns River Water Management District, Palatka, FLGoogle Scholar
  56. Fauth JE, Quintana-Ascencio PF, Hinkle CR, Wang D, Woodberry O, Chee YE (2016) Transpiration by Carolina willow (Salix caroliniana): environmental effects and cost-efficient management. Final report. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  57. Finlayson CM, D’Cruz R, Davidson N, Alder J, Steve C, de Groot R, Taylor D (2005) Millennium ecosystem assessment, 2005. Ecosystems and human well-being: wetlands and water synthesis. World Resources Institute, Washington, DC.  https://doi.org/10.1007/BF02987493, accessed 21 Jan 2018PubMedCrossRefGoogle Scholar
  58. Florida Department of Environmental Protection (2016) Final integrated water quality assessment for Florida: 2016 Sections 303(d), 305(b) and 314 report and listing. Florida Department of Environmental Protection. https://floridadep.gov/sites/default/files/2016-Integrated-Report.pdf. Accessed 12 Dec 2017
  59. Foley JA, DeFries R, Asner GP, Barford C, Bonan G, Carpenter SR, Chapin FS, Coe MT, Daily GC, Gibbs HK, Helkowski JH, Holloway T, Howard EA, Kucharik CJ, Monfreda C, Patz JA, Prentice IC, Ramankutty N, Snyder PK (2005) Global consequences of land use. Science 309:570–574PubMedCrossRefGoogle Scholar
  60. Fox S, Bochnak A, Osborne T, Keenan L, Speaks S, Dobberfuhl D (2014) Modeling wetland subsidence and elevation change in a headwater system: interpolation, model validation and implications for downstream water quality. Paper presented at AWRA GIS and water resources VIII: data to decisions, Snowbird, UT, 12–14 May 2014. http://www.awra.org/meetings/SnowBird2014/doc/final-program.pdf
  61. Gaiser EE, Zafiris A, Ruiz PL, Tobias FAC, Ross MS (2006) Tracking rates of ecotone migration due to salt-water encroachment using fossil mollusks in coastal South Florida. Hydrobiologia 569:237–257CrossRefGoogle Scholar
  62. Geselbracht L, Freeman K, Kelly E, Gordon DR, Putz FE (2011) Retrospective and prospective model simulations of sea level rise impacts on Gulf of Mexico coastal marshes and forests in Waccasassa Bay, Florida. Clim Change 107:35–57CrossRefGoogle Scholar
  63. Gleason RA, Laubhan MK, Euliss NH Jr (eds) (2008) Ecosystem services derived from wetland conservation practices in the United States prairie pothole region with an emphasis on the U.S. Department of Agriculture Conservation Reserve and Wetlands Reserve Programs. Professional Paper 1745, U.S. Geological Survey, Reston, VAGoogle Scholar
  64. Gressel N, McColl JG, Preston CM, Newman RH, Powers RF (1996) Linkages between phosphorus transformations and carbon decomposition in a forest soil. Biogeochemistry 33:97–123CrossRefGoogle Scholar
  65. Guggenberger G, Christensen BT, Rubæk GH, Zech W (1996) Land use and fertilization effects on P forms in two European soils: resin extraction and [31]P-NMR analysis. Eur J Soil Sci 47:605–614CrossRefGoogle Scholar
  66. Hall GB (1987) Establishment of minimum surface water requirements for the greater Lake Washington Basin. Technical Publication SJ87–3. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  67. Hall DL, Ponzio KJ, Miller JB, Bowen PJ, Curtis DL (2017) Ecology and management of Carolina willow (Salix caroliniana): a compendium of knowledge. Technical Publication SJ2017-01. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  68. Harland WB, Pickton CAG, Wright NJR, Croxton CA, Smith DG, Cutbill JL, Henderson WG (1976) Some coal-bearing strata in Svalbard. Norsk Polarinstitutt Skrifter 164:1–89Google Scholar
  69. Hartman WH, Richardson CJ, Vilgalys R, Bruland GL (2008) Environmental and anthropogenic controls over bacterial communities in wetland soils. Proc Natl Acad Sci USA 105(46):17842–17847PubMedCrossRefGoogle Scholar
  70. Hector A, Schmid B, Beierkuhnlein C, Caldeira MC, Diemer M, Dimitrakopoulos PG, Finn JA, Freitas H, Giller PS, Good J, Harris R, Hogberg P, Huss-Danell K, Joshi J, Jumpponen A, Korner C, Leadley PW, Loreau M, Minns A, Mulder CPH, O’Donovan G, Otway SJ, Pereira JS, Prinz S, Read DJ, Scherer-Lorenzen M, Schulze ED, Siamantziouras ASD, Spehn AM, Terry AC, Troumbis AY, Woodward FY, Yachi S, Lawton JH (1999) Plant diversity and productivity experiments in European grasslands. Science 286:1123–1127CrossRefGoogle Scholar
  71. Heer O (1868–1883) Flora Fossilis Arctica, volumes 1–7. Druck and Verlag von Friedrich Schulthess and Verlag von J. Wurster and Comp, Winterthur and ZürichGoogle Scholar
  72. Herman AB (2013) Albian-Paleocene flora of the North Pacific: systematic composition, palaeofloristics and phytostratigraphy. Stratigr Geol Correl 21:689–747CrossRefGoogle Scholar
  73. Huber M, Caballero R (2011) The early Eocene equable climate problem revisited. Clim Past 7:603–633CrossRefGoogle Scholar
  74. Intergovernmental Panel on Climate Change (2013) Climate change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of Working Group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, New YorkGoogle Scholar
  75. Intergovernmental Panel on Climate Change (2014) Climate change 2014: synthesis report summary for policymakers, 7–16. https://www.ipcc.ch/pdf/assessment-report/ar5/syr/AR5_SYR_FINAL_SPM.pdf. Accessed 21 Jan 2018
  76. Johnston CA, Caretti ON (2017) Mangrove expansion into temperate marshes alters habitat quality for recruiting Callinectes spp. Mar Ecol Prog Ser 573:1–14CrossRefGoogle Scholar
  77. Junk WJ, An S, Finlayson CM, Gopal B, Květ J, Mitchell SA, Robarts RD (2013) Current state of knowledge regarding the world’s wetlands and their future under global climate change: a synthesis. Aquat Sci 75(1):151–167.  https://doi.org/10.1007/s00027-012-0278-z CrossRefGoogle Scholar
  78. Karr JR, Chu EW (1999) Restoring life in running waters: better biological monitoring. Island Press, Washington, DCGoogle Scholar
  79. Keddy PA (2010) Wetland ecology: principles and conservation. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  80. Keddy PA, Fraser LH (2003) The management of wetlands for biological diversity: four principles. In: Ambasht RS, Ambasht NK (eds) Modern trends in applied aquatic ecology. Springer, Boston, MA, pp 21–42CrossRefGoogle Scholar
  81. Kirwan ML, Megonigal JP (2013) Tidal wetland stability in the face of human impacts and sea-level rise. Nature 504(7478):53–60CrossRefGoogle Scholar
  82. Kirwan ML, Guntenspergen GR, D’Alpaos A, Morris JT, Mudd SM, Temmerman S (2010) Limits on the adaptability of coastal marshes to rising sea level. Geophys Res Lett 37:5CrossRefGoogle Scholar
  83. Kononova SV, Nesmeyanova MA (2002) Phosphonates and their degradation by microorganisms. Biochemistry (Moscow) 67:184–195CrossRefGoogle Scholar
  84. Kornis MS, Breitburg D, Balouskus R, Bilkovic DM, Davias LA, Giordano S, Heggie K, Hines AH, Jacobs JM, Jordan TE, King RS, Patrick CJ, Seitz RD, Soulen H, Targett TE, Weller DE, Whigham DF, Uphoff J (2017) Linking the abundance of estuarine fish and crustaceans in nearshore waters to shoreline hardening and land cover. Estuar Coast 40(5):1464–1486CrossRefGoogle Scholar
  85. Koukol O, Novak F, Hrabal R (2008) Composition of the organic phosphorus fraction in basidiocarps of saprotrophic and mycorrhizal fungi. Soil Biol Biochem 40:2464–2467CrossRefGoogle Scholar
  86. Kryshtofovich AN (1928) New data on the upper Tertiary flora of north-western Siberia. Proc Geol Comm 46:751–757Google Scholar
  87. Kusler J (2006) Common questions: wetland, climate change, and carbon sequestering. http://www.aswm.org/propub/wetlandsandclimate.pdf. Accessed 21 Jan 2018
  88. Larsen DP, Thornton KW, Urquhart NS, Paulsen SG (1994) The role of sample surveys for monitoring the condition of the Nation’s lakes. Environ Monit Assess 32:101–134PubMedCrossRefGoogle Scholar
  89. Lawler JJ (2009) Climate change adaptation strategies for resource management and conservation planning. Ann NY Acad Sci 1162:79–98.  https://doi.org/10.1111/j.1749-6632.2009.04147.x CrossRefPubMedGoogle Scholar
  90. LePage BA (2007) The taxonomy and biogeographic history of Glyptostrobus Endlicher (Cupressaceae). Spec Publ Peabody Mus Nat Hist Yale Univ 48:359–426CrossRefGoogle Scholar
  91. LePage BA (2009) Earliest occurrence of Taiwania (Cupressaceae) from the Early Cretaceous of Alaska: evolution, biogeography, and paleoecology. Proc Acad Nat Sci Phila 158:129–158CrossRefGoogle Scholar
  92. LePage BA, Yang H, Matsumoto M (2005) The evolution and biogeographic history of Metasequoia. In: LePage BA, Williams CJ, Yang H (eds) The geobiology and ecology of Metasequoia. Springer, Dordrecht, pp 3–114CrossRefGoogle Scholar
  93. Lovejoy TE, Hannah L (2006) Climate change and biodiversity. Yale University Press, New Haven and LondonGoogle Scholar
  94. Lopez RD, Fennessy MS (2002) Testing the floristic quality assessment index as an indicator of wetland condition. Ecol Appl 12:487–497CrossRefGoogle Scholar
  95. Loreau M, Naeem S, Inchausti P, Bengtsson J, Grime JP, Hector A, Hooper DU, Huston MA, Raffaelli D, Schmid B, Tillman D, Wardle DA (2001) Biodiversity and ecosystem functioning: current knowledge and future challenges. Science 294:804–808PubMedCrossRefGoogle Scholar
  96. Lowe EF (1983) Distribution and structure of floodplain plant communities in the Upper Basin of the St. Johns River, Florida. Technical Publication 83-8, St. Johns River Water Management District, Palatka, FLGoogle Scholar
  97. Lowe EF, Brooks JE, Fall CJ, Gerry LR, Hall GB (1984) U.S. EPA Clean Lakes Program, Phase I. Diagnostic-feasibility study of the Upper St. Johns River chain of lakes. Vol. 1 – Diagnostic study. Tech. Pub. SJ 84-15. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  98. Lusby FE, Gibbs MM, Cooper AB, Thompson K (1998) The fate of groundwater ammonium in a lake edge wetland. J Environ Qual 27:459–466CrossRefGoogle Scholar
  99. MacDonald GM, Kremenetski KV, Beilman DW (2008) Climate change and the northern Russian treeline zone. Philos Trans R Soc B Biol Sci 363:2285–2299CrossRefGoogle Scholar
  100. Mahieu N, Olk DC, Randall EW (2000) Analysis of phosphorus in two humic acid fractions of intensively cropped lowland rice soil by 31P-NMR. Eur J Soil Sci 51:391–402CrossRefGoogle Scholar
  101. Maltby E, Acreman MC (2011) Ecosystem services of wetlands: pathfinder for a new paradigm. Hydrol Sci J 56(568):1341–1359.  https://doi.org/10.1080/02626667.2011.631014 CrossRefGoogle Scholar
  102. Mård, J, Box JE, Brown R, Mack M, Mernild SH, Walker D, Walsh J, Bhatt US, Epstein HE, Myers-Smith IH, Raynolds MK, Schuur EAG (2017) Cross-cutting scientific issues. In: Snow, water, ice and permafrost in the Arctic (SWIPA). Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway. pp 231–256Google Scholar
  103. Martin AC, Jeffers ES, Petrokofsky G, Myers-Smith I, Macias-Fauria M (2017) Shrub growth and expansion in the Arctic tundra: an assessment of controlling factors using an evidence-based approach. Environ Res Lett 12.  https://doi.org/10.1088/1748-9326/aa7989 CrossRefGoogle Scholar
  104. McDowell RW, Condron LM, Stewart I, Cave V (2005) Chemical nature and diversity of phosphorus in New Zealand pasture soils using 31P nuclear magnetic resonance spectroscopy and sequential fractionation. Nutr Cycl Agroecos 72:241–254CrossRefGoogle Scholar
  105. McGuire KL, Allison SD, Fierer N, Tresede KK (2013) Ectomycorrhizal-dominated boreal and tropical forests have distinct fungal communities, but analogous spatial patterns across soil horizons. PLoS One 8(7):e68278.  https://doi.org/10.1371/journal.pone.0068278 PubMedPubMedCentralCrossRefGoogle Scholar
  106. McIver EE, Basinger JF (1999) Early Tertiary floral evolution in the Canadian High Arctic. Ann Mo Bot Gard 86:523–545CrossRefGoogle Scholar
  107. Millennium Ecosystem Assessment (2003) Ecosystems and human well being: a framework for assessment. Island Press, Washington, DCGoogle Scholar
  108. Miller SJ, Borah AK, Lee MA, Lowe EF, Rao DV (1996) Technical memorandum no. 13—Environmental water management plan for the Blue Cypress Water Management Area: Upper St. Johns River Basin Project. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  109. Miller SJ, Lee MA, Lowe EF (1998) The Upper St. Johns River Basin Project: merging flood control with aquatic ecosystem restoration and preservation. In: Transactions of the 63rd North American wildlife and natural resources conference, vol 63, pp 156–170Google Scholar
  110. Mitsch WJ, Gosselink JG (1993) Wetlands, 2nd edn. Van Nostrand Reinhold, New YorkGoogle Scholar
  111. Mitsch WJ, Gosselink JG (2007) Wetlands, 4th edn. Wiley, New YorkGoogle Scholar
  112. Mitsch WJ, Gosselink JG (2015) Wetlands, 5th edn. Wiley, Hoboken, NJGoogle Scholar
  113. Mitsch WJ, Cronk JK, Wu X, Nairn RW, Hey DL (1995) Phosphorus retention in constructed freshwater riparian marshes. Ecol Appl 5:830–845CrossRefGoogle Scholar
  114. Moomaw WR, Chmura GL, Davies GT, Finlayson CM, Middleton BA, Natali SM, Perry JE, Roulet N, Sutton-Grier AE (2018) Wetlands in a changing climate: science, policy and management. Wetlands 38(2):183–205CrossRefGoogle Scholar
  115. Moseman-Valtierra S, Abdul-Aziz OI, Tang J, Ishtiaq KS, Morkeski K, Mora J, Kroeger KD (2016) Carbon dioxide fluxes reflect plant zonation and belowground biomass in a coastal marsh. Ecosphere 7(11):1–48.  https://doi.org/10.1002/ecs2.1560 CrossRefGoogle Scholar
  116. Nahlik AM, Fennessy MS (2016) Carbon storage in US wetlands. Nat Commun 7:13835.  https://doi.org/10.1038/ncomms13835 CrossRefPubMedPubMedCentralGoogle Scholar
  117. Narayan S, Beck MW, Wilson P, Thomas CJ, Guerrero A, Shepard CC, Trespalacios D (2016) Coastal wetlands and flood damage reduction: using risk industry-based models to assess natural defenses in the Northeastern USA. Lloyd’s Tercentenary Research Foundation, London. Sci Rep 7(1):1–23. https://conservationgateway.org/ConservationPractices/Marine/crr/library/Documents/CoastalWetlandsandFloodDamageReductionReport.pdf. Accessed 21 Jan 2018Google Scholar
  118. National Ice and Snow Data Center (2018) Advancing knowledge of Earth’s frozen regions. https://nsidc.org/cryosphere/glaciers/quickfacts.html. Accessed 30 July 2018
  119. Natural Resources Defense Council (2010) Climate change, water, and risk: current water demands are not sustainable. https://www.nrdc.org/sites/default/files/WaterRisk.pdf. Accessed 29 Jan 2018
  120. Neubauer SC (2014) On the challenges of modeling the net radiative forcing of wetlands: reconsidering Mitsch et al. 2013. Landsc Ecol 29(4):571–577.  https://doi.org/10.1007/s10980-014-9986-1 CrossRefGoogle Scholar
  121. Neubauer SC, Megonigal JP (2015) Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18(6):1000–1013.  https://doi.org/10.1007/s10021-015-9879-4 CrossRefGoogle Scholar
  122. Newman RH, Tate KR (1980) Soil phosphorus characterization by 31P-nuclear magnetic resonance. Commun Soil Sci Plant Anal 11:835–842CrossRefGoogle Scholar
  123. Nicholls RJ (2004) Coastal flooding and wetland loss in the 21st century: changes under the SRES climate and socio-economic scenarios. Global Environ Chang 14(1):69–86.  https://doi.org/10.1016/j.gloenvcha.2003.10.007 CrossRefGoogle Scholar
  124. Northern Great Plains Floristic Quality Assessment Panel (2001) Coefficients of conservatism for the vascular flora of the Dakotas and adjacent grasslands. U.S. Geological Survey, Biological Resources Division, Information and Technology Report USGS/BRD/ITR-2001-0001Google Scholar
  125. Osborne TZ, Newman S, Kalla P, Scheidt DJ, Bruland GL, Cohen MJ, Scinto LJ, Ellis LR (2011) Landscape patterns of significant soil nutrients and contaminants in the Greater Everglades Ecosystem: past, present, and future. Crit Rev Environ Sci Technol 41(6):121–148CrossRefGoogle Scholar
  126. Osborne TZ, Bochnak AMK, Vandam B, Duffy S, Keenan L, Inglett KS, Inglett PW, Sihi D (2014) Hydrologic effects on soil stability—loss, formation, and nutrient fluxes. Final report. St. Johns River Water Management District, Palatka, FLGoogle Scholar
  127. Osborne TZ, Fitz HC, Davis S (2017) Restoring the foundation of the Everglades: assessment of edaphic responses to hydrologic restoration scenarios. Restor Ecol 25(S1):59–71CrossRefGoogle Scholar
  128. Payette S (1993) The range limit of boreal tree species in Québec-Labrador: an ecological and palaeoecological interpretation. Rev Pal Pal 79:7–30CrossRefGoogle Scholar
  129. Pedersen GK, Andersen LA, Lundsteen EB, Petersen HI, Bojesen-Koefoed JA, Nytoft HP (2006) Depositional environments, organic maturity and petroleum potential of the Cretaceous coal-bearing Atane Formation at Qullisat, Nuussuaq Basin, West Greenland. J Petrol Geol 29:3–26CrossRefGoogle Scholar
  130. Phelps SA, Bochnak AMK, Ponzio KJ (2015) Vegetation response and elevation change in a perturbed hydrologic regime: the subsidy-stress gradient in a peat-based floodplain marsh. Paper presented at the annual conference of the Society of Wetland Scientists, Providence, RI, USA, 3 June 2015Google Scholar
  131. Potthoff M, Steenwerth K, Jackson L, Drenovsky R, Scow K, Joergensen R (2005) Soil microbial community composition as affected by restoration practices in California grassland. Soil Biol Biochem 38:1851–1860CrossRefGoogle Scholar
  132. Qu L, Makoto K, Choi DS, Quoreshi AM, Koike T (2009) The role of ectomycorrhiza in boreal forest ecosystem. In: Osawa A, Zyryanova OA, Matsuura Y, Kajimoto T, Wein RW (eds) Permafrost ecosystems: Siberian larch forests, Ecological studies, vol 209. Springer, Dordrecht, pp 413–425CrossRefGoogle Scholar
  133. Raabe EA, Stumpf RP (2016) Expansion of tidal marsh in response to sea-level rise on the Gulf Coast of Florida, USA. Estuar Coast 39:145–157CrossRefGoogle Scholar
  134. R Core Team (2012) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  135. Read DJ (1984) The structure and function of the vegetative mycelium of mycorrhizal roots. In: Jennings DH, Rayner ADM (eds) The ecology and physiology of the fungal mycelium. Cambridge University Press, Cambridge, pp 215–240Google Scholar
  136. Reddy KR, DeLaune RD (2008) Biogeochemistry of wetlands: science and applications. CRC, Boca Raton, FLCrossRefGoogle Scholar
  137. Reddy KR, DeLaune RD, DeBusk WF, Koch MS (1993) Long-term nutrient accumulation rates in the Everglades. Soil Sci Soc Am J 57:1147–1155CrossRefGoogle Scholar
  138. Rheinhardt RD, Brinson MM, Farley PM (1997) Applying wetland reference data to functional assessment, mitigation, and restoration. Wetlands 17:195–215CrossRefGoogle Scholar
  139. Rheinhardt RD, Rheinhardt MC, Brinson MM, Faser KE Jr (1999) Application of reference data for assessing and restoring headwater ecosystems. Restor Ecol 7:241–251CrossRefGoogle Scholar
  140. Richardson CJ (1999) The role of wetlands in storage, release and cycling of phosphorus on the landscape: a 25 year retrospective. In: Reddy KR (ed) Phosphorus biogeochemistry in sub-tropical ecosystems. CRC/Lewis, Boca Raton, FL, pp 47–68Google Scholar
  141. Ricketts BD, Embry AF (1984) Summary of geology and resource potential of coal deposits in the Canadian Arctic Archipelago. Bull Can Petrol Geol 32:359–371Google Scholar
  142. Rosenberg H (1964) Distribution and fate of 2-aminoethylphosphonic acid in Tetrahymena. Nature 203:299–300PubMedCrossRefGoogle Scholar
  143. Rubæk GH, Guggenberger G, Zech W, Christensen BT (1999) Organic phosphorous in soil size separates characterized by phosphorous-31 nuclear magnetic resonance and resin extraction. Soil Sci Soc Am J 63:1123–1132CrossRefGoogle Scholar
  144. Saha AK, Saha S, Sadle J, Jiang J, Ross MS, Price RM, Sternberg L, Wendelberger KS (2011) Sea level rise and South Florida coastal forests. Climatic Change 107:81–108CrossRefGoogle Scholar
  145. Sakai A (1971) Freezing resistance of relicts from the Arcto-Tertiary flora. New Phytol 70:1199–1205CrossRefGoogle Scholar
  146. Sakai A, Larcher W (1987) Frost survival of plants: responses and adaptation to freezing stress. Springer, New YorkCrossRefGoogle Scholar
  147. Schloemer-Jäger A (1958) Alttertiäre pflanzen aus flözen der brögger-halbinsel spitzbergens. Palaeontogr Abt B 104:39–103Google Scholar
  148. Schuyt K, Brander L (2004) Living waters: conserving the source of life: the economic values of the world’s wetlands. World Wildlife Fund, Gland. https://www.cbd.int/financial/doc/wwf-wetlandsvalues2004.pdf. Accessed 29 Jan 2018Google Scholar
  149. Simpson LT, Osborne TZ, Duckett LJ, Feller IC (2017) Carbon storages along a climate induced coastal wetland gradient. Wetlands 37(6):1023–1035.  https://doi.org/10.1007/s13157-017-0937-x CrossRefGoogle Scholar
  150. Sloan LC (1998) Polar stratospheric clouds: a high-latitude warming mechanism in an ancient polat greenhouse world. Geophys Res Let 25:3517–3520CrossRefGoogle Scholar
  151. Sloan LC, Huber M, Ewing A (1999) Polar stratospheric cloud forcing in a greenhouse world. In: Abrantes F, Mix AC (eds) Reconstructing ocean history: a window into the future. Kluwer Academic/Plenum, New York, pp 272–293Google Scholar
  152. Smith SE, Read DJ (2008) Mycorrhizal symbioses, 3rd edn. Academic, LondonGoogle Scholar
  153. Solomon D, Lehman J (2000) Loss of phosphorous from soil in semi-arid northern Tanzania as a result of cropping: evidence from sequential extraction and 31P-NMR spectroscopy. Eur J Soil Sci 51:699–708CrossRefGoogle Scholar
  154. Solomon D, Lehmann J, Mamo T, Fritzsche F, Zech W (2002) Phosphorus forms and dynamics as influenced by land use changes in the sub-humid Ethiopian highlands. Geoderma 105:21–48CrossRefGoogle Scholar
  155. Sterling M, Padera C (1998) The Upper St. Johns River Basin Project: the environmental transformation of a public flood control project. Professional Paper SJ97-PP1, St. John River Water Management District, Palatka, FLGoogle Scholar
  156. Stevens DL Jr, Olsen AR (1999) Spatially restricted surveys over time for aquatic resources. J Agr Biol Environ Stat 4:415–428CrossRefGoogle Scholar
  157. Stevens DL Jr, Olsen AR (2000) Spatially restricted random sampling designs for design-based and model-based estimation. In: Accuracy 2000: Proceedings of the 4th international symposium on spatial accuracy assessment in natural resources and environmental sciences, Delft University Press, The Netherlands, pp 609–616Google Scholar
  158. Stewart RE, Kantrud HA (1971) Classification of natural ponds and lakes in the Glaciated Prairie Region. Resource Publication 92, U.S. Department of the Interior, Fish and Wildlife Service, Washington, DCGoogle Scholar
  159. Sumann M, Amelung W, Haumaier L, Zech W (1998) Climatic effects on soil organic phosphorus in the North American Great Plains identified by phosphorus-31 nuclear magnetic resonance. Soil Sci Soc Am J 62:1580–1586CrossRefGoogle Scholar
  160. Sundareshwar PV, Morris JT, Pellechia PJ, Cohen H, Porter DE, Jones BC (2001) Occurrence and ecological significance of pyrophosphate in estuaries. Limnol Oceanogr 46:1570–1577CrossRefGoogle Scholar
  161. Sundareshwar PV, Morris JT, Koepfler EK, Fornwalt B (2003) Phosphorus limitation of coastal ecosystem processes. Science 299:563–565PubMedCrossRefGoogle Scholar
  162. Sundareshwar PV, Richardson CJ, Gleason RA, Pellechia PJ, Honomichl S (2009) Nature versus nurture: functional assessment of restoration effects on wetland services using nuclear magnetic resonance spectroscopy. Geophys Res Lett 36:L03402.  https://doi.org/10.1029/2008GL036385 CrossRefGoogle Scholar
  163. Sveshnikova IN, Budantsev LY (1969) Florulae fossiles arcticae, vol 1. Nauka, LeningradGoogle Scholar
  164. Tate KR, Salcedo I (1988) Phosphorus control of soil organic matter accumulation and cycling. Biogeochemistry 5:99–107CrossRefGoogle Scholar
  165. Tiessen H, Stewart JWB, Moir JO (1983) Changes in organic and inorganic phosphorus composition of two grassland soils and their particle size fractions during 60-90 years of cultivation. J Soil Sci 34:815–823CrossRefGoogle Scholar
  166. Tilman D, Wedin D, Knops J (1996) Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379:718–720CrossRefGoogle Scholar
  167. Toor GS, Condron LM, Cade-Menun BJ, Di HJ, Cameron KC (2005) Preferential phosphorus leaching from an irrigated grassland soil. Eur J Soil Sci 56:155–167CrossRefGoogle Scholar
  168. Torio DD, Chmura GL (2013) Assessing coastal squeeze of tidal wetlands. J Coast Res 29(5):1049–1061.  https://doi.org/10.2112/JCOASTRES-D-12-00162.1 CrossRefGoogle Scholar
  169. Troxler TG, Childers DL, Madden CJ (2014) Drivers of decadal-scale change in southern Everglades wetland macrophyte communities of the coastal ecotone. Wetlands 34:81–90CrossRefGoogle Scholar
  170. Turner BL, Mahieu N, Condron LN (2003) The phosphorus composition of temperate pasture soils determined by NaOH–EDTA extraction and solution 31P NMR spectroscopy. Org Geochem 34:1199–1210CrossRefGoogle Scholar
  171. Turrión MB, Glaser B, Solomon D, Ni A, Zech W (2000) Effects of deforestation on phosphorus pools in mountain soils of the Allay range, Khyrgyzia. Biol Fertil Soils 31:134–142CrossRefGoogle Scholar
  172. United States Environmental Protection Agency (2010) Florida water quality assessment report: 303(d) listed waters for 2010. United States Environmental Protection Agency, Washington, DC. https://ofmpub.epa.gov/waters10/attains_waterbody.control?p_list_id=FL2893V&p_state=FL&p_cycle=2010#attainments, accessed 12 Dec 2017
  173. van der Heijden MGA, Bardgett RD, van Straalen NM (2008) The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol Lett 11:296–310PubMedCrossRefGoogle Scholar
  174. van der Heijden MGA, Martin FM, Selosse MA, Sanders IR (2015) Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytol 205:1406–1423.  https://doi.org/10.1111/nph.13288 CrossRefPubMedGoogle Scholar
  175. Williams CJ, Johnson AH, LePage BA, Vann DR, Sweda T (2003) Reconstruction of Tertiary Metasequoia forests II. Structure, biomass and productivity of Eocene floodplain forests in the Canadian Arctic. Paleobiology 29:271–292CrossRefGoogle Scholar
  176. Williams CJ, LePage BA, Johnson AH, Vann DR (2009) Structure, biomass, and productivity of a late Paleocene Arctic forest. Proc Acad Nat Sci Phila 158:107–127CrossRefGoogle Scholar
  177. Williams CJ, Trostle KD, Sunderland D (2010) Fossil wood in coal-forming environments of the late Paleocene-early Eocene Chickaloon Formation. Palaeogeogr Palaeoclimatol Palaeoecol 295:363–375CrossRefGoogle Scholar
  178. Wingard GL, Lorenz JL (2014) Integrated conceptual model and habitat indices for the southwest Florida coastal wetlands. Ecol Indicat 44(S1):92–107CrossRefGoogle Scholar
  179. Woodward RT, Wui YS (2001) The economic value of wetland services: a meta-analysis. Ecol Econ 37(2):257–270.  https://doi.org/10.1016/S0921-8009(00)00276-7 CrossRefGoogle Scholar
  180. Zhu Q, Peng C, Liu J, Jiang H, Fang X, Chen H, He JS (2016) Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades. Sci Rep 6(1):38020.  https://doi.org/10.1038/srep38020 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kimberli J. Ponzio
    • 1
    Email author
  • Todd Z. Osborne
    • 2
    • 3
  • Gillian T. Davies
    • 4
    • 5
  • Ben LePage
    • 6
    • 7
  • Pallaoor V. Sundareshwar
    • 8
    • 9
  • S. J. Miller
    • 1
  • A. M. K. Bochnak
    • 10
  • S. A. Phelps
    • 3
  • M. Q. Guyette
    • 1
  • K. M. Chowanski
    • 8
  • L. A. Kunza
    • 8
  • P. J. Pellechia
    • 11
  • R. A. Gleason
    • 12
  • C. Sandvik
    • 8
  1. 1.St. Johns River Water Management DistrictPalatkaUSA
  2. 2.Estuarine Biogeochemistry Laboratory, Whitney Laboratory for Marine BioscienceUniversity of FloridaSt. AugustineUSA
  3. 3.Wetland Biogeochemistry Laboratory, Soil and Water Sciences DepartmentUniversity of FloridaGainesvilleUSA
  4. 4.BSC Group, Inc.WorcesterUSA
  5. 5.Global Development and Environment Institute, Tufts UniversityMedfordUSA
  6. 6.Pacific Gas and Electric CompanySan RamonUSA
  7. 7.Academy of Natural SciencesPhiladelphiaUSA
  8. 8.Department of Atmospheric SciencesSouth Dakota School of Mines and TechnologyRapid CityUSA
  9. 9.United States Agency for International DevelopmentWashingtonUSA
  10. 10.Environmental Consulting & Technology, Inc.GainesvilleUSA
  11. 11.Department of Chemistry and BiochemistryUniversity of South CarolinaColumbiaUSA
  12. 12.Northern Prairie Wildlife Research CenterU.S. Geological SurveyJamestownUSA

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