The projection of species distribution models and the problem of non-analog climate

By M. Fitzpatrick, William W. Hargrove. Biodiversity and Conservation, 2009

425 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/fa4e337974a8eb9c5be11ac0b97c77ee0e54a6fd

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Citations in the corpus

Selecting predictors to maximize the transferability of species distribution models: lessons from cross‐continental plant invasions (2017, background): “Specific environmental conditions in distinct study areas can vary in their frequency 97 (i.e. different availability between ranges, Broennimann et al., 2012) or can be completely non-98 existent in one of the ranges (i.e. non-analog climate, Fitzpatrick & Hargrove, 2009).”
Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates (2011, background): “…thus reﬂect the current best practice: mapping nonanalogue climates to identify where uncertainties are likely to be higher (Platts et al. , 2008; Fitzpatrick & Hargrove, 2009; Elith et al. , 2010; Arau´jo et al. , 2011; Roberts & Hamann, in press) and using a range of BEMs that make different…”
Global diversity in light of climate change: the case of ants (2011, background): “The future expansion of today’s extreme environments, and the likely emergence of no-analogue climates, is new territory for biodiversity (Williams et al., 2007; Fitzpatrick & Hargrove, 2009).”
Potential range of the invasive fish rotan (Perccottus glenii) in the Holarctic (2011, background): “Extrapolating models outside the range of environmental conditions used for calibration can be problematic (Fitzpatrick and Hargrove 2009).”
Nice weather for bettongs: using weather events, not climate means, in species distribution models (2012, background): “…to project those niches onto geographical space in order to predict species occurrences now or in the future (Guisan and Th uiller 2005, Araújo and Guisan 2006, Hijmans and Graham 2006, Jimenez-Valverde et al. 2008, Th uiller et al. 2008, Elith and Leathwick 2009, Fitzpatrick and Hargrove 2009).”
Here be dragons: a tool for quantifying novelty due to covariate range and correlation change when projecting species distribution models (2014, methodology): “…climate extrapolation issue, it has been suggested that a map indicating projected suitability should be accompanied by some measure of uncertainty: a counterpart map, for example, which indicates regions where the model has been extrapolated (Platts et al., 2008; Fitzpatrick & Hargrove, 2009).”
Use of niche models in invasive species risk assessments (2011, background): “…thus, it is advisable to highlight areas where the niche models are being applied to novel combinations of environmental variables, such that their predictions may have a relatively high degree of uncertainty (Fitzpatrick and Hargrove 2009; Elith et al. 2010; Jiménez-Valverde et al. 2011).”
Beyond climate: disturbance niche shifts in invasive species (2015, methodology): “Despite its potential, it is important to consider possible bias arising from the selection of the variables (Strubbe et al., 2013) and uncertainties such as that associated with extrapolation into non-analogous conditions (Fitzpatrick & Hargrove, 2009).”
Integrating ensemble species distribution modelling and statistical phylogeography to inform projections of climate change impacts on species distributions (2013, background): “While projection of SDMs onto these ‘novel climates’ is discouraged (Fitzpatrick & Hargrove, 2009; Elith et al., 2010), it is usually unavoidable because novel combinations of temperature and precipitation are highly likely over forecast periods (~100 years) on the spatial scale of most SDM studies…”
The role of climate, habitat, and species co‐occurrence as drivers of change in small mammal distributions over the past century (2011, background): “A key weakness of species distribution models is their high prediction error rate when projecting into novel environments and/or non-analog climates (Fitzpatrick & Hargrove, 2009).”
The Tropical Seagrass Halophila stipulacea: Reviewing What We Know From Its Native and Invasive Habitats, Alongside Identifying Knowledge Gaps (2020, background): “These models are developed using the knowledge on the current distribution of the studied species (the realized niche) which can be potentially projected in space or time to forecast the species distributions within the invaded ranges within a time frame (Fitzpatrick and Hargrove, 2009; Gallien et a”