Predicting climate‐induced range shifts: model differences and model reliability

By Joshua J. Lawler, Denis White, R. Neilson, A. Blaustein. 2006

415 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/df71b1d010b654f0571d73edeeb7d7e227fff652

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Citations in the corpus

Assessing the vulnerability of European butterflies to climate change using multiple criteria (2010, methodology): “…vulnerability to climate change have hitherto focused on projected range size changes, based on two assumptions of species ability to migrate into new areas, i.e. full dispersal or no dispersal (e.g. Bakkenes et al. 2002; Peterson et al. 2004; Lawler et al. 2006; Gómez-Mendoza and Arriaga 2007).”
Optimizing resiliency of reserve networks to climate change: multispecies conservation planning in the Pacific Northwest, USA (2010, methodology): “r 2009 Blackwell Publishing Ltd, Global Change Biology, 16, 891–904 lyses (e.g., Lawler et al., 2006, 2009) by using the period 1961–1990 as a standard timeframe to represent ‘current’ climate.”
Predicting species distributions in poorly-studied landscapes (2008, methodology): “We obtained locality records for each endemic bird and mammal species from natural history museums, published literature and reliable observational data (see Acknowledgements for list of contributors).”
Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions (2009, background): “Several authors have suggested projecting species distributions using more than one ENM, allowing uncertainty among models to be addressed (Araújo et al., 2005; Thuiller et al., 2005; Lawler et al., 2006; Araújo & New, 2007).”
Dispersal will limit ability of mammals to track climate change in the Western Hemisphere (2012, methodology): “We investigated the potential for mammals in the Western Hemisphere to keep pace with a changing climate by comparing the velocities of climate change that each of 493 mammals will likely experience with modeled dispersal velocities for these species.”
The BIOKLIM Project: Biodiversity Research between Climate Change and Wilding in a temperate montane forest - The conceptual framework (2009, methodology): “Prediction of the extinction risk for high montane species using habitat modelling techniques (e.g. generalized linear models, for more detail see laWler et al. 2006) is one example of the possible uses for such data.”
Conservation and climate change: Assessing the vulnerability of snow leopard habitat to treeline shift in the Himalaya (2012, neutral): “While bioclimatic models have been used to predict the persistence of species populations and habitats based on climate change-related threats, they are often impractical for conservation planning due to limitations of scale and reliability (Heikkinen et al., 2006; Lawler et al., 2006).”
Niches and distributional areas: Concepts, methods, and assumptions (2009, background): “A number of recent papers have set out to compare the performance of different algorithms (among the dozens available) for estimating ecological niches (15, 59, 60).”
Forecasting the Effects of Global Warming on Biodiversity (2007, methodology): “…then replot the climate for the future from a climate model and, finally, use one-to-one mapping to replot the future distribution of the species, without any validation using independent data (Midgley et al. 2002, Travis 2003, Coulston and Riitters 2005, Hannah et al. 2005, Lawler et al. 2006).”
Contrasted impacts of climate change on stream fish assemblages along an environmental gradient (2009, background): “Recent studies have demonstrated that projections of the future distribution of a single species could be much contrasted depending on the statistical models applied (Thuiller, 2004; Araujo et al. , 2005; Lawler et al. , 2006; Pearson et al. , 2006; Crossman & Bass, 2008).”
The bioclimatic envelope of the wolverine (Gulo gulo): do climatic constraints limit its geographic distribution? (2010, background): “The influence of climate on the natural distribution of many species (Pearson and Dawson 2003) has led to the development of ‘‘bioclimatic envelope’’ models that relate range limits to sets of climatic conditions within which a species can survive and reproduce (Box 1981; Pearson and Dawson 2003; Th”
Where will species go? Incorporating new advances in climate modelling into projections of species distributions (2007, background): “A number of recent studies have focused on assessing the accuracy and reliability of different bioclimatic models (e.g. Thuiller, 2004; Araújo et al., 2005; Elith et al., 2006; Lawler et al., 2006; Pearson et al., 2006).”
Projecting global marine biodiversity impacts under climate change scenarios (2009, background): “Despite its wide application in projecting climate change effects on species distributions, predictions from bioclimate envelope models are often sensitive to model assumptions and uncertainties (Pearson and Dawson 2003; Thuiller 2004; Lawler et al. 2006; Pearson et al. 2006).”
Geographical patterns in prediction errors of species distribution models (2011, background): “The number of prediction errors varies considerably among modelling techniques (Muñoz & Felicísimo, 2004; Segurado & Aráujo, 2004; Lawler et al., 2006; Pearson et al., 2006; Meynard & Quinn, 2007; Dormann et al., 2008), as well as with the degree of equilibrium with environmental conditions (Araújo ”
WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS? (2007, methodology): “RF (random forest; Breiman 2001) is a machine-learning method (as neural networks) A. GUISAN ET AL.624 Ecological Monographs Vol. 77, No. 4 used occasionally in ecology with promising results (Lawler et al. 2006, Schwartz et al. 2006, Broennimann et al. 2007).”