Abstract
Context
Landscape patterns have been measured as a fundamental part of landscape ecology, especially with increasing computational power and availability of landcover data. Among the challenges associated with landscape measurement is identifying the appropriate scale of application, both temporal and spatial. Measurement of landscape patterns in highly-dynamic landscapes is especially challenged by temporal scale selection.
Objectives
This short communication focuses on how landscape pattern measurements vary in response to normal variability in a highly-dynamic landscape
Methods
For a small agricultural landscape with known crop rotation dynamism sequences, a simulation model provided 30 years of crop rotations. These 30 different landscapes were measured with landscape pattern measurements and the variability of the measurements was assessed.
Results
Almost half of the measurement values were outliers, and 12 of the 30 years had at least one outlier landscape pattern measurement value, even though the basis of landscape change was a normative agricultural practice. For a consistent but dynamic landscape, some landscape measurements or simulation years had high variability, demonstrating that inferences from highly-dynamic landscapes need to be based on fine-resolution time steps.
Conclusions
The application of landscape pattern measurements continues to be a common method in landscape ecology, and temporal dimensions are key to detecting change and what might be causing or responding to that change. The temporal resolution of change implies that highly-dynamic landscapes require more-frequent sampling, and that comparisons for agricultural landscapes over long time periods requires more than a single temporal endpoint.
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References
Asbjornsen H, Hernandez-Santana V, Liebman M, Bayala J, Chen J, Helmers M, Ong CK (2013) Targeting perennial vegetation in agricultural landscapes for enhancing ecosystem services. Renew Agric Food Syst 29(02):101–125
Bormann FH, Likens GE (1979) Pattern and process in a forested ecosystem. Springer-Verlag, New York
Castellazzi MS, Matthews J, Angevin F, Sausse C, Wood G, Burgess PJ, Brown I, Conrad KF, Perry JN (2010) Simulation scenarios of spatio-temporal arrangement of crops at the landscape scale. Environ Model Softw 25:1881–1889
Clark JS, Grimm EC, Donovan JJ, Fritz SC, Engstrom DR, Almendinger JE (2002) Drought cycles and landscape responses to past aridity on prairies of the Northern Great Plains, USA. Ecology 83(3):595–601
Corry RC (2013) Landscapes of Intersecting trade and environmental policies: intensive Canadian and American farmlands. Landsc Res 39(2):107–122
Corry RC (2016) Global and local policy forces for landscape perennialization in central North American agriculture. Geogr Tidsskr-Dan J Geogr 116(1):5–13
Corry RC (2018a) Extending the string-of-lights metaphor to describe dynamism in agricultural landscapes. Landscape Ecol 33(7):1013–1022
Corry RC (2018b) Recent losses of perennial cover in a Great Lakes agricultural region. Can Geogr 62(2):178–187
Corry RC, Nassauer JI (2002) Managing for Small Patch Patterns in Human-dominated Landscapes: cultural factors and corn belt agriculture. In: Liu J, Taylor W (eds) Integrating landscape ecology into natural resource management. Cambridge University Press, Cambridge, pp 92–113
Franzluebbers AJ, Paine LK, Winsten JR, Krome M, Sanderson MA, Ogles K, Thompson D (2012) Well-managed grazing systems: a forgotten hero of conservation. J Soil Water Conserv 67(4):100a–104a
Gustafson EJ (1998) Quantifying landscape spatial pattern: what is the state of the art? Ecosystems 1:143–156
Hart JF (1998) The Rural Landscape. Johns Hopkins University Press, Baltimore
Iglewicz B, Hoaglin DC (1993) How to detect and handle outliers. In: Mykytka EF (ed) The ASQC basic references in quality control: statistical techniques. ASQC Quality Press, Wisconsin, p 87
Leys C, Ley C, Klein O, Bernard P, Licata L (2013) Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J Exp Soc Psychol 49(4):764–766
Lin BB (2011) Resilience in agriculture through crop diversification: adaptive management for environmental change. Bioscience 61(3):183–193
Lockwood JA, Debrey LD (1990) A solution for the sudden and unexplained extinction of the rocky mountain grasshopper (Orthoptera: Acrididae). Environ Entomol 19(5):1194–1205
Loucks OL (1970) Evolution of diversity, efficiency, and community stability. Am Zool 10:17–25
McDonald JH (2014) Handbook of biological statistics. Sparky House Publishing, Baltimore
McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. USDA Forest Service Pacific Northwest Research Station, Portland, p 122
McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. University of Massachusetts, Amherst
Munkholm LJ, Heck RJ, Deen B (2013) Long-term rotation and tillage effects on soil structure and crop yield. Soil Tillage Res 127:85–91
Ontario Ministry of Agriculture Food and Rural Affairs (2009) Agronomy guide for field crops. Ministry of Agriculture, Food and Rural Affairs, Ontario
Ramankutty N, Evan AT, Monfreda C, Foley JA (2008) Farming the planet: 1 Geographical distribution of global agricultural lands in the year 2000. Glob Biogeochem Cycles. https://doi.org/10.1029/2007GB002952
Schulte LA, Liebman M, Asbjornsen H, Crow TR (2006) Agroecosystem restoration through strategic integration of perennials. J Soil Water Conserv 61(6):165A–169A
Tilman D, Fargione J, Wolff B, D’antonio C, Dobson A, Howarth R, Schindler D, Schlesinger WH, Simberloff D, Swackhamer D (2001) Forecasting agriculturally driven global environmental change. Science 292(5515):281–284
Turner MG (1990) Spatial and temporal analysis of landscape patterns. Landscape Ecol 4(1):21–30
Turner MG, Romme WH, Gardner RH, O’Neill RV, Kratz TK (1993) A revised concept of landscape equilibrium: disturbance and stability on scaled landscapes. Landscape Ecol 8(3):213–227
Turner BL, Wuellner M, Malo DD, Herrick JE, Dunn BH, Gates R (2018) Ecosystem functions in mixed cropland–grassland systems influenced by soil legacies of past crop cultivation decisions. Ecosphere 9(12):e02521
Weaver WF (1962) Crown surveys in Ontario. Department of Lands and Forests, Toronto, p 26
Wright CK, Wimberly MC (2013) Recent land use change in the Western Corn Belt threatens grasslands and wetlands. Proc Natl Acad Sci USA 110(10):4134–4139
Wu JG, Hobbs R (2002) Key issues and research priorities in landscape ecology: an idiosyncratic synthesis. Landscape Ecol 17(4):355–365
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This research work was supported by a grant from the Landscape Architecture Canada Foundation.
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Corry, R.C. How measures of agricultural landscape patterns are affected by crop rotation dynamics. Landscape Ecol 34, 2159–2167 (2019). https://doi.org/10.1007/s10980-019-00823-w
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DOI: https://doi.org/10.1007/s10980-019-00823-w