Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change

By J. Diniz-Filho, Luis Mauricio Bini, Rafael D. Loyola, Thiago Fernando Rangel, C. Hof. 2009

600 citations recorded by the source corpus.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/a11468d4291911509daf57fd2d4301bcc13ab824

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In Ecological Modeling

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Conserving the Brazilian semiarid (Caatinga) biome under climate change (2012, methodology): “…remnants gaining climatic suitability for species will become climatically appropriate for practices of agriculture, cattle ranches, and urbanization, conservation strategies will compete with socioeconomics interests (sensu Balmford et al. 2001; and discussion on Diniz-Filho et al. 2009b).”
Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming? (2012, methodology): “Overall, three correlative SDM runs (i.e., Bio-ensembles; MaxEnt with substrate; and MaxEnt without substrate) were used to forecast climate suitability in annual time steps (2000– 2100) according to two emission scenarios (LEV1 and WRE750; see above).”
Understanding what controls the spatial distribution of fish populations using a multi-model approach (2011, background): “The identification of the various sources of uncertainties in ensemble modelling remains a major issue for any attempt to forecast species distribution under anticipated future conditions, and is a currently a very active field of research (Diniz-Filho et al., 2009).”
Climate change vulnerability assessment of species (2018, methodology): “Choice of modeling technique is one of the major sources of uncertainty in correlative models (Diniz-Filho et al., 2009; Garcia et al., 2012) but valuable guidance on using and understanding correlative models is available (see e.g., Anderson, 2012, 2013; Franklin, 2009; Pearson, 2007; Peterson et…”
SESAM – a new framework integrating macroecological and species distribution models for predicting spatio‐temporal patterns of species assemblages (2011, methodology): “…and local extent to assess assemblages of c. 300 plant species in the western Swiss Alps (see Dubuis et al., in press), whereas the second uses a dataset at coarse resolution and continental extent to assess assemblages of c. 4000 bird species throughout the New World (Diniz-Filho et al., 2009).”
Can species distribution modelling provide estimates of population densities? A case study with jaguars in the Neotropics (2012, unknown): “…Elith & Graham, 2009; Elith & Leathwick, 2009), it is recommended to apply more than one of these methods and combine them (Araújo & New, 2007; Diniz-Filho et al., 2009; Marmion et al., 2009; Roura-Pascual et al., 2009) or compare the results, testing their performance to evaluate which one…”