The three phases of the ensemble forecasting of niche models: geographic range and shifts in climatically suitable areas of Utetheisa ornatrix (Lepidoptera, Arctiidae)
Abstract:ABSTRACT. The three phases of the ensemble forecasting of niche models: geographic range and shifts in climatically suitable areas of Utetheisa ornatrix (Lepidoptera, Arctiidae). Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. How… Show more
“…Coefficients of PCA show high similarity between the carbon emission scenarios, as expected. The largest variation is associated to the modeling methods, in agreement with results of other studies that found SDMs as the main source of uncertainty (ARAÚJO et al, 2005a, b;DINIZ-FILHO et al, 2009a, 2010a. Moreover, it is also widely discussed in the literature that the SDMs tend to differ from each other in prediction of species distribution, both in the present and future scenarios (ELITH et al, 2006).…”
Section: Discussionsupporting
confidence: 87%
“…The use of a principal component analysis suggested by some authors (DINIZ-FILHO et al, 2010a;ARAÚJO et al, 2005b) was important to reveal qualitatively the contribution of each source of variation (SDMs, AOGCMs, emission scenarios) in maps resulted from ensemble forecast. Coefficients of PCA show high similarity between the carbon emission scenarios, as expected.…”
Section: Discussionmentioning
confidence: 99%
“…method, scenario, parameters) on assembly data (DINIZ-FILHO et al, 2009) or with only one species (DINIZ-FILHO et al, 2010a, b) have been evaluated and mapped enabling a better assessment of the uncertainties in the predictions. Diniz-Filho et al (2010a) recently proposed tree phases for ensembles forecast studies. Phase I would be the calculation of a consensus map of the distribution range using different models, data and methods.…”
-Different climate models, modeling methods and carbon emission scenarios were used in this paper to evaluate the effects of future climate changes on geographical distribution of species of economic and cultural importance across the Cerrado biome. As the results of several studies have shown, there are still many uncertainties associated with these projections, although bioclimatic models are still widely used and effective method to evaluate the consequences for biodiversity of these climate changes. In this article, it was found that 90% of these uncertainties are related to methods of modeling, although, regardless of the uncertainties, the results revealed that the studied species will reduce about 78% of their geographic distribution in Cerrado. For an effective work on the conservation of these species, many studies still need to be carried out, although it is already possible to observe that climate change will have a strong influence on the pattern of distribution of these species.Keywords: Ensemble forecasting, Bioclimatic envelope, Species distribution models, Modeling uncertainty.
EFEITOS DAS MUDANÇAS CLIMÁTICAS GLOBAIS SOBRE OS PADRÕES DE DISTRIBUIÇÃO GEOGRÁFICA DAS ESPÉCIES DE PLANTAS ECONOMICAMENTE IMPORTANTES NO CERRADO
“…Coefficients of PCA show high similarity between the carbon emission scenarios, as expected. The largest variation is associated to the modeling methods, in agreement with results of other studies that found SDMs as the main source of uncertainty (ARAÚJO et al, 2005a, b;DINIZ-FILHO et al, 2009a, 2010a. Moreover, it is also widely discussed in the literature that the SDMs tend to differ from each other in prediction of species distribution, both in the present and future scenarios (ELITH et al, 2006).…”
Section: Discussionsupporting
confidence: 87%
“…The use of a principal component analysis suggested by some authors (DINIZ-FILHO et al, 2010a;ARAÚJO et al, 2005b) was important to reveal qualitatively the contribution of each source of variation (SDMs, AOGCMs, emission scenarios) in maps resulted from ensemble forecast. Coefficients of PCA show high similarity between the carbon emission scenarios, as expected.…”
Section: Discussionmentioning
confidence: 99%
“…method, scenario, parameters) on assembly data (DINIZ-FILHO et al, 2009) or with only one species (DINIZ-FILHO et al, 2010a, b) have been evaluated and mapped enabling a better assessment of the uncertainties in the predictions. Diniz-Filho et al (2010a) recently proposed tree phases for ensembles forecast studies. Phase I would be the calculation of a consensus map of the distribution range using different models, data and methods.…”
-Different climate models, modeling methods and carbon emission scenarios were used in this paper to evaluate the effects of future climate changes on geographical distribution of species of economic and cultural importance across the Cerrado biome. As the results of several studies have shown, there are still many uncertainties associated with these projections, although bioclimatic models are still widely used and effective method to evaluate the consequences for biodiversity of these climate changes. In this article, it was found that 90% of these uncertainties are related to methods of modeling, although, regardless of the uncertainties, the results revealed that the studied species will reduce about 78% of their geographic distribution in Cerrado. For an effective work on the conservation of these species, many studies still need to be carried out, although it is already possible to observe that climate change will have a strong influence on the pattern of distribution of these species.Keywords: Ensemble forecasting, Bioclimatic envelope, Species distribution models, Modeling uncertainty.
EFEITOS DAS MUDANÇAS CLIMÁTICAS GLOBAIS SOBRE OS PADRÕES DE DISTRIBUIÇÃO GEOGRÁFICA DAS ESPÉCIES DE PLANTAS ECONOMICAMENTE IMPORTANTES NO CERRADO
“…The seed (the nuts) are important for local economies, so understanding population and range dynamics under climate change may be also important for optimizing adaptive strategies for local human communities as well (e.g., Nabout et al, 2011). We used an ensemble forecast approach for obtaining species' range in which multiple SDMs and climatic models were combined (Marmion et al, 2009;Diniz-Filho et al, 2009a, 2010aNabout et al, 2010). We then obtained a series of genetic parameters (number of alleles per locus, expected heterozygosity under Hardy-Weinberg equilibrium (HWE) and mutation-drift equilibrium) for the entire species, which were recalculated assuming that local population in areas of low future environmental suitability will become extinct.…”
ABSTRACT. Many species are expected to suffer strong shifts in their geographic ranges due to climate changes in the next 50 years, with severe consequences for biodiversity patterns and population structure. We used here an ensemble forecast approach for obtaining species' range in which multiple species distribution models and climatic models were combined to model loss of genetic variability in Baru, Dipteryx alata (Fabaceae), an economically important Neotropical tree native to the Cerrado of Brazil. We estimated a series of genetic parameters (number of alleles per locus, expected heterozygosity under
Geographic shifts and genetic variability in Dipteryx alataHardy-Weinberg equilibrium and mutation-drift equilibrium) for this species based on eight microsatellite loci. We then recalculated these parameters assuming that local populations in areas of low future environmental suitability will go extinct. All genetic parameters remained approximately constant up to a 50% threshold of climatic suitability in the future; after this critical threshold there is an abrupt reduction in all parameters, although the magnitude of shift is only about 10% of current values, on average. Thus, despite the shifts in geographic range and climatically suitable areas towards southeastern Brazil, our analyses do not predict a strong loss of genetic diversity in D. alata because of the broad tolerance of this species, which ensures large future ranges, contrasting with other Cerrado species that have been analyzed in a similar manner.
“…Alfred Russell Wallace (1823Wallace ( -1913 Since immemorial times, from Wallace to modern scientists, the study of the geographical distribution of species has fascinated humans. Many studies have focused on the evolution, dynamics, and structure of geographic ranges (Brown et al 1996;Gaston 2003;Diniz Filho et al 2010), but, albeit their theoretical relevance, estimating geographic ranges and species distribution is still a challenging issue for ecologists and biogeographers. Modern scientists have been developing statistical and mathematical models to infer and predict geographic distribution of species by coupling data on species occurrences at different spatial scales with environmental (bioclimatic) data (Pearson & Dawson 2003).…”
The ongoing biodiversity crisis is pushing ecologists and conservation biologists to develop models to foretell the effects of human-induced transformation of natural resources on the distribution of species, although ecology and biogeography still lacks a paradigmatic body of theory to fully understand the drivers of biodiversity patterns. Two decades of research on ecological niche models and species distributions have been characterized by technical development and discussions on a plethora of methods or algorithms to infer and predict species distributions. Here we suggest a metaphorical classification scheme for some of the most popular models based on their complexity, interpretability and suitability for specific applications in ecology and conservation biology. Our purpose is not to compare methods by their capacity to accurately predict the observed distribution of species, nor to criticize how they are commonly used in applied studies. Instead, we believe that a simple classification scheme can potentially highlight how some methods are more suited for specific applications in ecology and conservation biology. Envelope and distance-based models are grouped into the "fish bowl" category, for their transparency and simplicity. Statistical models are classified as "turbine" models, because of their hidden complexity and general applicability. Finally, machine-learning models are classified as "vault" models, for their high complexity and lack of interpretability of fit parameters. We conclude that the diversity of species distribution models used today is expected for a young research field, but the choice of modeling strategy depends on the purpose of the study. We provide some general guidelines for choosing models for studies of conservation planning and climate change mitigation and suggest models of intermediate complexity for conservation planning and forecast of climate change effects on biodiversity as they provide a good balance between interpretability, predictive power and robustness to model over-fit.
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