Correction to ‘Controlled comparison of species- and community-level models across novel climates and communities’

Maguire, Kaitlin C.; Nieto‐Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.

doi:10.1098/rspb.2016.1705

Cited by 2 publications

(1 citation statement)

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“…This finding calls into question the dependability and utility of using empirical models to project future distributions and communities. Overall, however, our results both reveal a path towards better predictions of future ecological assemblages given the large magnitude of climatic change expected for the future and highlight the need for better approaches given the expected increase in compositional novelty [7,52]. We confirm that CLMs are a similar or modestly superior approach to SDMs for modelling the responses of species diversity and distributions to climate change.…”

Section: Resultssupporting

confidence: 65%

Controlled comparison of species- and community-level models across novel climates and communities

et al. 2016

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Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossilpollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa.

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Section: Resultssupporting

confidence: 65%

Controlled comparison of species- and community-level models across novel climates and communities

et al. 2016

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How complex should models be? Comparing correlative and mechanistic range dynamics models

Fordham

Bertelsmeier

Brook

et al. 2017

Global Change Biology

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Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.

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Correction to ‘Controlled comparison of species- and community-level models across novel climates and communities’

Abstract: One of the six climate variables used to fit the models was listed incorrectly in the Environmental variables section under Material and methods [1]. Mean yearly evapotranspiration ratio was used, not mean yearly potential evapotranspiration.

Cited by 2 publications

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Controlled comparison of species- and community-level models across novel climates and communities

Controlled comparison of species- and community-level models across novel climates and communities

How complex should models be? Comparing correlative and mechanistic range dynamics models

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