

You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
How complex should models be? Comparing correlative and mechanistic range dynamics models

AbstractCriticism 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.
570, Take urgent action to combat climate change and its impacts, 550, Climate Change, Population Dynamics, 910, Models, Biological, 333, metapopulation and dispersal dynamics, Birds, hybrid ecological niche model, Metapopulation and dispersal dynamics, Species Specificity, Climate change, Animals, Species distribution models, Ecosystem, mechanistic model, species distribution model, transferability, land use, //metadata.un.org/sdg/13 [http], Species distribution model, independent model validation, Independent model validation, climate change, Transferability, Hybrid ecological niche model, Land use, Mechanistic model, Animal Distribution, Forecasting
570, Take urgent action to combat climate change and its impacts, 550, Climate Change, Population Dynamics, 910, Models, Biological, 333, metapopulation and dispersal dynamics, Birds, hybrid ecological niche model, Metapopulation and dispersal dynamics, Species Specificity, Climate change, Animals, Species distribution models, Ecosystem, mechanistic model, species distribution model, transferability, land use, //metadata.un.org/sdg/13 [http], Species distribution model, independent model validation, Independent model validation, climate change, Transferability, Hybrid ecological niche model, Land use, Mechanistic model, Animal Distribution, Forecasting
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).85 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1% visibility views 37 download downloads 13 - 37views13downloads
Data source Views Downloads DIGITAL.CSIC 37 13


