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Prediction and scale in savanna ecosystems
Author(s) -
Staver A. Carla
Publication year - 2018
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.14829
Subject(s) - biosphere , vegetation (pathology) , spatial ecology , scale (ratio) , environmental change , ecosystem , ecology , spatial heterogeneity , global change , tree (set theory) , physical geography , variable (mathematics) , environmental science , geography , temporal scales , resource (disambiguation) , climate change , biology , computer science , cartography , mathematics , medicine , mathematical analysis , pathology , computer network
ContentsSummary 52 I. Introduction 52 II. Determinants of savanna vegetation structure 53 III. Are trees in savannas really more heterogeneous? 53 IV. Are trees in savannas a ‘slow’ variable? 54 V. Are trees in savannas spatially patterned? 55 VI. Conclusions 55Acknowledgements 55References 56Summary Savannas are highly variable systems, and predicting variation, especially in the tree layer, represents a major unresolved challenge for forecasting biosphere responses to global change. Prediction to date has focused on disentangling interactions between resource limitation and chronic disturbances to identify what determines local savanna vegetation heterogeneity. By focusing at too fine a scale, this approach overlooks: sample size limitation arising from sparse tree distributions; stochasticity in demographic and environmental processes that is preserved as heterogeneity among tree populations with slow dynamics; and spatial self‐organization. Renewed focus on large (1–50 ha) permanent plots and on spatial patterns of tree‐layer variability at even larger landscape spatial scales (≥1000s of ha) promises to resolve these limitations, consistent with the goal of predicting large‐scale biosphere responses to global change.