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A scale-linked conservation planning framework for freshwater ecosystems

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Abstract

Context

Cross-scale analyses are central to understanding patterns and processes in hierarchically structured ecological systems. Systematic conservation planning has progressed in recent years, but the utility of cross-scale planning efforts has received little valuation.

Objectives

Our goal was to develop and evaluate a scale-linked framework to prioritize spatial units for conservation. We sought to compare the spatial configuration and cost-efficiency of a conservation network designed using data collected and analyzed at two spatial scales (e.g., both regional and local) with that produced using a more traditional single-scale approach (e.g., local).

Methods

We sampled macroinvertebrate communities from 48 representative streams within the Congaree Biosphere Region in 2019. We developed random forest models to predict distributions of community-level metrics at regional (subwatershed) and local (local catchment) spatial scales. Finally, we prioritized planning units according to their conservation value, relative to three biotic metrics, under two different scenarios: a traditional ‘single-scale’ and novel ‘scale-linked’ approach.

Results

Spatial differences between our single-scale and scale-linked scenarios were apparent. On average, solutions produced by our scale-linked scenario were 4.96% less costly and required 4.71% fewer planning units than our single-scale scenario. Scale-linked solutions were penalized an average of 15.90% less than single-scale solutions, reflecting a greater capacity to adequately represent the biotic metrics of interest.

Conclusion

Our comparisons suggest that scale-linked approaches can decrease cross-scale disparities and better reflect hierarchical processes without sacrificing planning efficiency. Thus, scale-linked conservation planning may help ease implementation efforts while enhancing the long-term resilience and sustainability of landscapes surrounding protected areas.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  • Abell R, Allan JD, Lehner B (2007) Unlocking the potential of protected areas for freshwaters. Biol Cons 134:48–63

    Article  Google Scholar 

  • Allan JR et al (2022) The minimum land area requiring conservation attention to safeguard biodiversity. Science 376:1094–1101

    Article  CAS  PubMed  Google Scholar 

  • Allen CR, Angeler DG, Garmestani AS, Gunderson LH, Holling CS (2014) Panarchy: theory and application. Ecosystems 17:578–589

    Article  Google Scholar 

  • Arponen A (2012) Prioritizing species for conservation planning. Biodivers Conserv 21:875–893

    Article  Google Scholar 

  • Baldwin RF, Fouch NT (2018) Understanding the biodiversity contributions of small protected areas presents many challenges. Land 7:123

    Article  Google Scholar 

  • Baldwin RF, Trombulak SC, Leonard PB, Noss RF, Hilty JA, Possingham HP, Scarlett L, Anderson MG (2018) The future of landscape conservation. Bioscience 68:60–63

    Article  PubMed  PubMed Central  Google Scholar 

  • Ball IR, Possingham HP, Watts M (2009) MARXAN and relatives: software for spatial conservation prioritisation. In: Moilanen A, Wilson KA, Possingham HP (eds) Spatial conservation prioritisation: quantitative methods and computational tools. Oxford University Press, Oxford

    Google Scholar 

  • Beger M et al (2010a) Conservation planning for connectivity across marine, freshwater, and terrestrial realms. Biol Cons 143:565–575

    Article  Google Scholar 

  • Beger M, Linke S, Watts M, Game E, Treml E, Ball I, Possingham HP (2010b) Incorporating asymmetric connectivity into spatial decision making for conservation. Conserv Lett 3:359–368

    Article  Google Scholar 

  • Bhakti T, Goulart F, de Azevedo CS, Antonini Y (2018) Does scale matter? The influence of three-level spatial scales on forest bird occurrence in a tropical landscape. PLoS ONE 13:e0198732

    Article  PubMed  PubMed Central  Google Scholar 

  • Boyd J, Epanchin-Niell R, Siikamӓki J (2015) Conservation planning: a review of return on investment analysis. Rev Environ Econ Policy 9:23–42

    Article  Google Scholar 

  • Breiman L (2001) Random forests. Mach Learn 45:5–32

    Article  Google Scholar 

  • Brumm KJ, Hanks RD, Baldwin RF, Peoples BK (2021) Accounting for multiple dimensions of biodiversity to assess surrogate performance in a freshwater conservation prioritization. Ecol Ind 122:107320

    Article  Google Scholar 

  • Cadotte MW, Carscadden K, Mirotchnick N (2011) Beyond species: functional diversity and the maintenance of ecological processes and services. J Appl Ecol 48:1079–1087

    Article  Google Scholar 

  • Cheok J, Weeks R, Pressey RL (2019) Identifying the strengths and weaknesses of conservation planning at different scales: the coral triangle as a case study. Ecol Soc 24:24

    Article  Google Scholar 

  • Ciegler JC (2003) Water beetles of South Carolina (Coleoptera: Gyrinidae, Haliplidae, Noteridae, Dytiscidae, Hydrophilidae, Hydraenidae, Scirtidae, Elmidae, Dryopidae, Limnichidae, Heteroceridae, Psephenidae, Ptilodactylidae, and Chelonariidae). Biota of South Carolina. PSA Publishing, Clemson University, Clemson

    Google Scholar 

  • Comte L, Olden JD, Lischka S, Dickson BG (2022) Multi-scale threat assessment of riverine ecosystems in the Colorado River Basin. Ecol Ind 138:108840

    Article  CAS  Google Scholar 

  • Cumming GS et al (2015) Understanding protected area resilience: a multi-scale, social-ecological approach. Ecol Appl 25:299–319

    Article  PubMed  Google Scholar 

  • de Bello F, Lepš J, Lavorel S, Moretti M (2007) Importance of species abundance for assessment of trait composition: an example based on pollinator communities. Community Ecol 8:163–170

    Article  Google Scholar 

  • De’ath G, Fabricius KE (2000) Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81:3178–3192

    Article  Google Scholar 

  • Debastiani VJ, Pillar VD (2012) SYNCSA — R tool for analysis of metacommunities based on functional traits and phylogeny of the community components. Bioinformatics 28:2067–2068

    Article  CAS  PubMed  Google Scholar 

  • Ekroos J et al (2016) Sparing land for biodiversity at multiple spatial scales. Front Ecol Evol 3:145

    Article  Google Scholar 

  • Fei S, Guo Q, Potter K (2016) Macrosystems ecology: novel methods and new understanding of multi-scale patterns and processes. Landscape Ecol 31:1–6

    Article  Google Scholar 

  • Feld CK, Hering D (2007) Community structure or function: effects of environmental stress on benthic macroinvertebrates at different spatial scales. Freshw Biol 52:1380–1399

    Article  Google Scholar 

  • Fick SE, Hijmans RJ (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int J Climatol 37:4302–4315

    Article  Google Scholar 

  • Fournier A, Barbet-Massin M, Rome Q, Courchamp F (2017) Predicting species distribution combining multi-scale drivers. Global Ecol Conserv 12:215–226

    Article  Google Scholar 

  • Frissell CA, Liss WJ, Warren CE, Hurley MD (1986) A hierarchical framework for stream habitat classification: viewing streams in a watershed context. Environ Manage 10:199–214

    Article  Google Scholar 

  • Frye C (2007) About the geometrical interval classification method. https://www.esri.com/arcgis-blog/products/product/mapping/about-the-geometrical-interval-classification-method/?rmedium=redirect&rsource=blogs.esri.com/esri/arcgis/2007/10/18/about-the-geometrical-interval-classification-method. Accessed Aug 2022

  • Groves CR (2003) Drafting a conservation blueprint: a practitioner’s guide to planning for biodiversity. Island Press, Washington DC

    Google Scholar 

  • Groves CR et al (2002) Planning for biodiversity conservation: putting conservation science into practice. Bioscience 52:499–512

    Article  Google Scholar 

  • Guilhaumon F et al (2015) Representing taxonomic, phylogenetic and functional diversity: new challenges for Mediterranean marine-protected areas. Divers Distrib 21:175–187

    Article  Google Scholar 

  • Guisan A, Thuiller W, Zimmermann NE (2017) Habitat suitability and distribution models: with applications in R. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Harris JM, Livingstone T, Lombard AT, Lagabrielle E, Haupt P, Sink K, Schleyer M, Mann BQ (2012) Coastal and marine biodiversity plan for KwaZulu-Natal. Spatial priorities for the conservation of coastal and marine biodiversity in KwaZulu-Natal. Ezemvelo KZN Wildlife Scientific Services Technical Report, Durban

    Google Scholar 

  • Heino J (2011) A macroecological perspective of diversity patterns in the freshwater realm. Freshw Biol 56:1703–1722

    Article  Google Scholar 

  • Heino J, Mykrӓ H, Kotanen J, Muotka T (2007) Ecological filters and variability in stream macroinvertebrate communities: do taxonomic and functional structure follow the same path? Ecography 30:217–230

    Article  Google Scholar 

  • Hermoso V, Linke S, Prenda J, Possingham HP (2011) Addressing longitudinal connectivity in the systematic conservation planning of fresh waters. Freshw Biol 56:57–70

    Article  Google Scholar 

  • Hermoso V, Kennard MJ, Linke S (2012) Integrating multidirectional connectivity requirements in systematic conservation planning for freshwater systems. Divers Distrib 18:448–458

    Article  Google Scholar 

  • Higgins JV, Bryer MT, Khoury ML, Fitzhugh TW (2005) A freshwater classification approach for biodiversity conservation planning. Conserv Biol 19:432–445

    Article  Google Scholar 

  • Huber PR, Greco SE, Thorne JH (2010) Spatial scale effects on conservation network design: trade-offs and omissions in regional versus local scale planning. Landscape Ecol 25:683–695

    Article  Google Scholar 

  • Hutchens JJ Jr, Schuldt JA, Richards C, Johnson LB, Host GE, Breneman DH (2009) Multi-scale mechanistic indicators of Midwestern USA stream macroinvertebrates. Ecol Ind 9:1138–1150

    Article  Google Scholar 

  • Jackson DA, Peres-Neto PR, Olden JD (2001) What controls who is where in freshwater fish communities – the roles of biotic, abiotic, and spatial factors. Can J Fish Aquat Sci 58:157–170

    Google Scholar 

  • Kennedy CM, Oakleaf JR, Theobald DM, Baruch-Mordo S, Kiesecker J (2019) Managing the middle: a shift in conservation priorities based on the global human modification gradient. Glob Change Biol 25:811–826

    Article  Google Scholar 

  • Kerans BL, Karr JR (1994) A benthic index of biotic integrity (B-IBI) for rivers of the Tennessee Valley. Ecol Appl 4:768–785

    Article  Google Scholar 

  • Knight AT, Cowling RM (2007) Embracing opportunism in the selection of priority conservation areas. Conserv Biol 21:1124–1126

    Article  PubMed  Google Scholar 

  • Knight AT, Cowling RM, Rouget M, Balmford A, Lombard AT, Campbell BM (2008) Knowing but not doing: selecting priority conservation areas and the research-implementation gap. Conserv Biol 22:610–617

    Article  PubMed  Google Scholar 

  • Kuhn, M. Contributions from Jed Wing et al (2019) caret: Classification and Regression Training. R package version 6.0-84. https://CRAN.R-project.org/package=caret. Accessed Aug 2022

  • Lagabrielle E, Lombard AT, Harris JM, Livingstone TC (2018) Multi-scale multi-level marine spatial planning: a novel methodological approach applied in South Africa. PLoS ONE 13:1–29

    Article  Google Scholar 

  • Leonard PB, Baldwin RF, Hanks RD (2017) Landscape-scale conservation design across biotic realms: sequential integration of aquatic and terrestrial landscapes. Sci Rep 7:14556

    Article  PubMed  PubMed Central  Google Scholar 

  • Lindborg R et al (2017) How spatial scale shapes the generation and management of multiple ecosystem services. Ecosphere 8:e01741

    Article  Google Scholar 

  • Linke S, Norris RH, Pressey RL (2008) Irreplaceability of river networks: towards catchment-based conservation planning. J Appl Ecol 45:1486–1495

    Article  Google Scholar 

  • Linke S, Turak E, Nel J (2011) Freshwater conservation planning: the case for systematic approaches. Freshw Biol 56:6–20

    Article  Google Scholar 

  • Linke S, Hermoso V, Januchowski-Hartley S (2019) Toward process-based conservation prioritizations for freshwater ecosystems. Aquat Conserv Mar Freshwat Ecosyst 29:1149–1160

    Article  Google Scholar 

  • Maciejewski K, De Vos A, Cumming GS, Moore C, Biggs D (2015) Cross-scale feedbacks and scale mismatches as influences on cultural services and the resilience of protected areas. Ecol Appl 25:11–23

    Article  PubMed  Google Scholar 

  • Margules CR, Pressey RL (2000) Systematic conservation planning. Nature 405:243–253

    Article  CAS  PubMed  Google Scholar 

  • McCluney KE, Poff NL, Palmer MA, Thorp JH, Poole GC, Williams BS, Williams MR, Baron JS (2014) Riverine macrosystems ecology: sensitivity, resistance, and resilience of whole river basins with human alterations. Front Ecol Environ 12:48–58

    Article  Google Scholar 

  • McKay L, Bondelid T, Dewald T, Johnston J, Moore R, Rea A (2012) NHDPlus Version 2: user guide

  • Merovich GT, Petty TJ, Strager MP, Fulton JB (2013) Hierarchical classification of stream condition: a house—neighborhood framework for establishing conservation priorities in complex riverscapes. Freshwater Sci 32:874–891

    Article  Google Scholar 

  • Merritt RW, Cummins KW, Berg MB (2008) An introduction to the aquatic insects of North America, 4th edn. Kendall/Hunt Publishing Company, Dubuque

    Google Scholar 

  • Metcalfe JL (1989) Biological water quality assessment of running waters based on macroinvertebrate communities: history and present status in Europe. Environ Pollut 60:101–139

    Article  CAS  PubMed  Google Scholar 

  • Morse JC, McCafferty WP, Stark BP, Jacobus LM (2016) Larvae of the Southeastern USA mayfly, stonefly, and caddisfly species. Biota of South Carolina, vol 9. PSA Publishing, Clemson University, Clemson

    Google Scholar 

  • Mykrӓ H, Heino J, Muotka T (2007) Scale-related patterns in the spatial and environmental components of stream macroinvertebrate assemblage variation. Glob Ecol Biogeogr 16:149–159

    Article  Google Scholar 

  • Peters DPC, Bestelmeyer BT, Knapp AK (2011) Perspectives on global change theory. In: Scheiner SM, Willig MR (eds) The theory of ecology. University of Chicago Press, Chicago

    Google Scholar 

  • Poff NL (1997) Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. J N Am Benthol Soc 16:391–409

    Article  Google Scholar 

  • Poiani KA, Richter BD, Anderson MG, Richter HE (2000) Biodiversity conservation at multiple scales: functional sites, landscapes, and networks. Bioscience 50:133–146

    Article  Google Scholar 

  • Possingham H, Ball I, Andelman S (2000) Mathematical methods for identifying representative reserve networks. In: Ferson S, Burgman M (eds) Quantitative methods for conservation biology. Springer, New York, pp 291–305

    Chapter  Google Scholar 

  • Potter KM, Cubbage FW, Schaberg RH (2005) Multiple-scale landscape predictors of benthic macroinvertebrate community structure in North Carolina. Landsc Urban Plan 71:77–90

    Article  Google Scholar 

  • Pressey RL, Bottrill MC (2009) Approaches to landscape- and seascape-scale conservation planning: convergence, contrasts and challenges. Oryx 43:464–475

    Article  Google Scholar 

  • Price SJ, Marks DR, Howe RW, Hanowski JM, Niemi GJ (2004) The importance of spatial scale for conservation and assessment of anuran populations in coastal wetlands of the western Great Lakes, USA. Landscape Ecol 20:441–454

    Article  Google Scholar 

  • R Core Team (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  • Rao CR (1982) Diversity and dissimilarity coefficients: a unified approach. Theor Popul Biol 21:24–43

    Article  Google Scholar 

  • Resh VH, Norris RH, Barbour MT (1995) Design and implementation of rapid assessment approaches for water resource monitoring using benthic macroinvertebrates. Aust J Ecol 20:108–121

    Article  Google Scholar 

  • Rivers-Moore NA, Goodman PS, Nel JL (2011) Scale-based freshwater conservation planning: towards protecting freshwater biodiversity in KwaZulu-Natal, South Africa. Freshw Biol 56:125–141

    Article  Google Scholar 

  • Rodríguez JD, Pérez A, Lozano JA (2010) Sensitivity of k-fold cross validation in prediction error estimation. IEEE Trans Pattern Anal Mach Intell 32:569–575

    Article  PubMed  Google Scholar 

  • Saito VS, Siqueira T, Fonseca-Gessner AA (2015) Should phylogenetic and functional diversity metrics compose macroinvertebrate multimetric indices for stream biomonitoring? Hydrobiologia 745:167–179

    Article  Google Scholar 

  • Schmera D, Heino J, Podani J, Erős T, Dolédec S (2017) Functional diversity: a review of methodology and current knowledge in freshwater macroinvertebrate research. Hydrobiologia 787:27–44

    Article  Google Scholar 

  • Segan DB, Game ET, Watts ME, Stewart RR, Possingham HP (2011) An interoperable decision support tool for conservation planning. Environ Model Softw 26:1434–1441

    Article  Google Scholar 

  • Soranno PA et al (2014) Cross-scale interactions: quantifying multi-scaled cause-effect relationships in macroecosystems. Front Ecol Environ 12:65–73

    Article  Google Scholar 

  • South Carolina Department of Health and Environmental Control (2017) Standard operating and quality control procedures for macroinvertebrate sampling. Technical report 0914-17. Bureau of Water, Columbia

    Google Scholar 

  • South Carolina Geological Survey, South Carolina Department of Natural Resources (2006) Statewide DEM for SC. Reston, Virginia, USA. https://www.dnr.sc.gov/geology/digital-data.html. Accessed Aug 2022

  • Sponseller RA, Benfield EF, Valett HM (2001) Relationships between land use, spatial scale and stream macroinvertebrate communities. Freshw Biol 46:1409–1424

    Article  Google Scholar 

  • Strayer DL (2006) Challenges for freshwater invertebrate conservation. J N Am Benthol Soc 25:271–287

    Article  Google Scholar 

  • Tennessen KJ (2019) Dragonfly nymphs of North America: an identification guide. Springer Nature Switzerland AG, Cham

    Book  Google Scholar 

  • Theobald DM (2013) A general model to quantify ecological integrity for landscape assessments and US application. Landscape Ecol 28:1859–1874

    Article  Google Scholar 

  • Theobald DM, Hobbs NT, Bearly T, Zack JA, Shenk T, Riebsame WE (2000) Incorporating biological information in local land-use decision making: designing a system for conservation planning. Landscape Ecol 15:35–45

    Article  Google Scholar 

  • Tyers M (2017) Riverdist: river network distance computation and applications. R package version 0.15.0. https://CRAN.R-project.org/package=riverdist

  • Tylianakis JM, Laliberté E, Nielsen A, Bascompte J (2010) Conservation of species interaction networks. Biol Cons 143:2270–2279

    Article  Google Scholar 

  • Wear DN, Bolstad P (1998) Land-use changes in southern appalachian landscapes: spatial analysis and forecast evaluation. Ecosystems 1:575–594

    Article  Google Scholar 

  • Wiens JA (2002) Riverine landscapes: taking landscape ecology into the water. Freshw Biol 47:501–515

    Article  Google Scholar 

  • Wilson KA, Cabeza M, Klein CJ (2009) Fundamental concepts of spatial conservation prioritization. In: Moilanen A, Wilson KA, Possingham HP (eds) Spatial conservation prioritization. Oxford University Press, New York, pp 16–27

    Google Scholar 

  • Yang L et al (2018) A new generation of the United States National land cover database—requirements, research priorities, design, and implementation strategies. ISPRS J Photogramm Remote Sens 146:108–123

    Article  Google Scholar 

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Acknowledgements

We thank Logan Bodiford and Rachel Moore for their dedicated assistance in the field and laboratory, and John Morse for access to lab space, equipment, and archiving resources at the Clemson University Arthropod Collection. Paul L. Angermeier and Stephen C. Trombulak provided invaluable comments that greatly improved the manuscript. This work was funded, in part, by the Margaret H. Lloyd endowment and by the National Institute of Food and Agriculture/United States Department of Agriculture, under project number SC-1700599. This work represents technical contribution number 7065 of the Clemson Experiment Station.

Funding

This work was funded, in part, by the Margaret H. Lloyd endowment and by the National Institute of Food and Agriculture/United States Department of Agriculture, under project number SC-1700599.

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Authors and Affiliations

  1. Department of Forestry and Environmental Conservation, Clemson University, 261 Lehotsky Hall, Clemson, SC, 29634, USA

    Kyle J. Brumm, R. Daniel Hanks, Robert F. Baldwin & Brandon K. Peoples

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  1. Kyle J. Brumm
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  2. R. Daniel Hanks
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Contributions

All authors contributed to the conception of ideas and design of methodology. KJB collected and analyzed the data; KJB and BKP led the writing of the manuscript; RFB and BKP acquired funding and supervised the project. All authors contributed critically to the revision of drafts and gave final approval for publication.

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Correspondence to Brandon K. Peoples.

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Supplementary Information

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10980_2022_1505_MOESM1_ESM.pdf

Supplementary file1 (PDF 134 kb)—Distribution of local catchment sampling locations with respect to environmental variable principal components (Appendix S1).

Supplementary file2 (PDF 14 kb)—Functional trait descriptions (Appendix S2).

10980_2022_1505_MOESM3_ESM.pdf

Supplementary file3 (PDF 59 kb)—A summary of thresholds used to categorize conservation features (Appendix S3) are available online. The authors are solely responsible for the content and functionality of these materials. Queries (other than absence of the material) should be directed to the corresponding author

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Brumm, K.J., Hanks, R.D., Baldwin, R.F. et al. A scale-linked conservation planning framework for freshwater ecosystems. Landsc Ecol 37, 2589–2605 (2022). https://doi.org/10.1007/s10980-022-01505-w

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