Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models

Vaart, Elske van der; Johnston, Alice S. A.; Sibly, Richard M.

doi:10.1016/j.ecolmodel.2015.08.012

Cited by 48 publications

(36 citation statements)

References 55 publications

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“…ODD protocol; Grimm et al, 2010) will also increase model accessibility. There is growing interest in calibration, verification and sensitivity analysis for processexplicit models (Augusiak et al 2014;van der Vaart et al 2016). Methods for running sensitivity analyses and propagating key sources of uncertainty are now commonly applied to some model classes (e.g.…”

Section: Cause For Optimismmentioning

confidence: 99%

Forecasting species range dynamics with process‐explicit models: matching methods to applications

et al. 2019

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Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process–explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process–explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs – regulatory planning, extinction risk, climate refugia and invasive species – we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process‐explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.

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Section: Cause For Optimismmentioning

confidence: 99%

Forecasting species range dynamics with process‐explicit models: matching methods to applications

et al. 2019

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“…As the management landscapes do not represent typical fragmentation patterns as closely as baseline landscapes, it might be expected that "less typical" dispersal ranges are observed. Furthermore, empirical measurement of dispersal kernels is often confounded by logistics, particularly study area size (Hassall and Thompson 2012) making the quantification of long distance movements particularly difficult (Trakhtenbrot et al 2005). Empirical studies have demonstrated that measured dispersal distances are to some degree determined by levels of habitat fragmentation (Mayer et al 2009).…”

Section: Discussionmentioning

confidence: 99%

An empirical, cross-taxon evaluation of landscape-scale connectivity

Hunter‐Ayad

Hassall

2020

Biodivers Conserv

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Connectivity is vital for the maintenance of spatially structured ecosystems, but is threatened by anthropogenic processes that degrade habitat networks. Thus, connectivity enhancement has become a conservation priority, with resources dedicated to enhancing habitat networks. However, much effort may be wasted on ineffective management, as conservation theory and practice can be poorly linked. Here we evaluate the success of landscape management designed to restore connectivity in the Humberhead wetlands (UK). Hybrid pattern-process models were created for six species, representing key taxa in the wetland ecosystem. Habitat suitability models were used to provide the spatial context for individual-based models that predicted metapopulation dynamics, including functional connectivity. To create models representing post-management conditions, landscape structure was modified to represent local improvements in habitat quality achieved through management. Models indicate that management had limited success in enhancing connectivity. Interventions have buffered existing connectivity in several species' habitat networks, with inter-patch movement increasing for modelled species by up to 22% (for water vole, Arvicola amphibius), but have not reconnected isolated habitat fragments. Field surveys provided provisional support for the accuracy of baseline models, but could not identify predicted benefits from management interventions, likely due to time-lags following these interventions. Despite lacking clear empirical support as yet, models suggest the management of the Humberhead wetlands has successfully enhanced the landscape-scale ecological network, achieving management targets. However we identify key limitations to this success and provide specific recommendations for improvement of future landscapescale management. Our developments in model application and integration can be developed further and be usefully applied to studies of species and/or community dynamics in a range of contexts.

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“…Technologically, the quantity and quality of data available have been revolutionized with major breakthroughs in animal tracking and remote-sensing [25], the omics [26] and the processing of Big Data [27]. Methodologically, innovative approaches to modelling and analysis include new developments in agentbased modelling (ABM) [28], social network analysis (SNA) [29][30][31], metapopulation modelling [32,33], landscape genetics [34] and other spatially explicit landscape-based models.…”

Section: A Framework Linking Animal Behaviour To Community Level Procmentioning

confidence: 99%

Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation

Bro‐Jørgensen

Franks

Meise

2019

Phil. Trans. R. Soc. B

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The impact of environmental change on the reproduction and survival of wildlife is often behaviourally mediated, placing behavioural ecology in a central position to quantify population- and community-level consequences of anthropogenic threats to biodiversity. This theme issue demonstrates how recent conceptual and methodological advances in the discipline are applied to inform conservation. The issue highlights how the focus in behavioural ecology on understanding variation in behaviour between individuals, rather than just measuring the population mean, is critical to explaining demographic stochasticity and thereby reducing fuzziness of population models. The contributions also show the importance of knowing the mechanisms by which behaviour is achieved, i.e. the role of learning, reasoning and instincts, in order to understand how behaviours change in human-modified environments, where their function is less likely to be adaptive. More recent work has thus abandoned the ‘adaptationist’ paradigm of early behavioural ecology and increasingly measures evolutionary processes directly by quantifying selection gradients and phenotypic plasticity. To support quantitative predictions at the population and community levels, a rich arsenal of modelling techniques has developed, and interdisciplinary approaches show promising prospects for predicting the effectiveness of alternative management options, with the social sciences, movement ecology and epidemiology particularly pertinent. The theme issue furthermore explores the relevance of behaviour for global threat assessment, and practical advice is given as to how behavioural ecologists can augment their conservation impact by carefully selecting and promoting their study systems, and increasing their engagement with local communities, natural resource managers and policy-makers. Its aim to uncover the nuts and bolts of how natural systems work positions behavioural ecology squarely in the heart of conservation biology, where its perspective offers an all-important complement to more descriptive ‘big-picture’ approaches to priority setting. This article is part of the theme issue ‘Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation’.

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Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models

Cited by 48 publications

References 55 publications

Forecasting species range dynamics with process‐explicit models: matching methods to applications

Forecasting species range dynamics with process‐explicit models: matching methods to applications

An empirical, cross-taxon evaluation of landscape-scale connectivity

Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation

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