Bridging the scale gap: predicting large-scale population dynamics from small-scale variation in strongly heterogeneous landscapes

Cobbold, C. A. , Lutscher, F. and Yurk, B. (2022) Bridging the scale gap: predicting large-scale population dynamics from small-scale variation in strongly heterogeneous landscapes. Methods in Ecology and Evolution, 13(4), pp. 866-879. (doi: 10.1111/2041-210X.13799)

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1. Often, ecologists are challenged with a mismatch of scales: how do we upscale from local variation and available data to landscape-level models and predictions? 2. We present a general recipe for coarse-graining from local- to landscape-scale reaction–diffusion equations when spatial heterogeneity is small in extent compared to dispersal of organisms. Our homogenization approach uses the fundamental ecological concepts of Turchin's residence index and Skellam's dynamic level. 3. Our approach opens avenues to new ecological theory that connects different scales, which we illustrate using predator–prey interactions. It also presents opportunities for using the increasingly available small-scale data for landscapelevel predictions, such as range expansion rates. 4. We find several unexpected nonlinear relationships between the movement behaviour on the local level and the spatially implicit and explicit outcomes at the landscape level, for example, predator spread rate may increase or decrease when predators move faster locally. Our method provides a mechanistic link for population dynamics and data integration across spatial and temporal scales, addressing a fundamental goal of landscape ecology

Item Type:Articles
Additional Information:Funding information: Natural Sciences and Engineering Research Council of Canada, Grant/ Award Number: RGPAS-2016-492872 and RGPIN-2016-04795; Leverhulme Research Fellowship, Grant/Award Number: RF-2018-577\9
Glasgow Author(s) Enlighten ID:Cobbold, Professor Christina
Authors: Cobbold, C. A., Lutscher, F., and Yurk, B.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Mathematics
Journal Name:Methods in Ecology and Evolution
ISSN (Online):2041-210X
Published Online:26 December 2021
Copyright Holders:Copyright © 2022 British Ecological Society
First Published:First published in Methods in Ecology and Evolution 13(4): 86-879
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
302369Insect abundance and climate variability: Novel insights from homogenisationChristina CobboldLeverhulme Trust (LEVERHUL)RF-2018-577\9M&S - Mathematics