Ensemble forecasting of species distributions

Araújo, Miguel B.; New, Mark

doi:10.1016/j.tree.2006.09.010

Cited by 2,600 publications

(2,219 citation statements)

References 51 publications

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“…all the binary maps. This conjugation allowed us to reduce the uncertainty that would have resulted from to the output of a single method (Pearson et al, 2006), which is similar what has been proposed by Araújo and New (2006) concerning uncertainty reduction for projecting species distributions in future climate scenarios. Figure 2 shows the resulting model amounting to the agreement between the three binary models.…”

Section: Calibration Calculationsmentioning

confidence: 79%

Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal

Capinha

Gomes²,

Reis

et al. 2009

Geospat Health

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Abstract. Malaria was a major health problem in the first half of the 20th Century in mainland Portugal. Nowadays, although the disease is no longer endemic, there is still the risk of future endemic infections due to the continuous occurrence of imported cases and the possibility of transmission in the country by Anopheles atroparvus Van Thiel, 1927. Since vector abundance constitute one of the foremost factors in malaria transmission, we have created several habitat suitability models to describe this vector species' current distribution. Three different correlative models; namely (i) a multilayer perceptron artificial neural network (MLP-ANN); (ii) binary logistic regression (BLR); and (iii) Mahalanobis distance were used to combine the species records with a set of five environmental predictors. Kappa coefficient values from k-fold cross-validation records showed that binary logistic regression produced the best predictions, while the other two models also produced acceptable results. Therefore, in order to reduce uncertainty, the three suitability models were combined. The resulting model identified high suitability for An. atroparvus in the majority of the country with exception of the northern and central coastal areas. Malaria distribution during the last endemic period in the country was also compared with the combined suitability model, and a high degree of spatial agreement was obtained (kappa = 0.62). It was concluded that habitat suitability for malaria vectors can constitute valuable information on the assessment of several spatial attributes of the disease. In addition, the results suggest that the spatial distribution of An. atroparvus in the country remains very similar to the one known about seven decades ago.

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Section: Calibration Calculationsmentioning

confidence: 79%

Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal

Capinha

Gomes²,

Reis

et al. 2009

Geospat Health

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“…The ensemble modeling approach consists of producing multiple realizations of predictions (usually by combining multiple model classes with multiple sets of initial conditions, parameterizations, and scenarios), from which a consensus can be derived (e.g., average trend), and, most importantly, uncertainties can be quantified (Araújo & New, 2007). The rationale behind ensemble modeling is that identifying the best model in a given situation (e.g., current data) gives no certainty that this model will adequately represent new observations (e.g., future projections), which is specifically the case for extrapolations to novel environments.…”

Section: Resultsmentioning

confidence: 99%

Insights from modeling studies on how climate change affects invasive alien species geography

Bellard

Jeschke

Leroy

et al. 2018

Ecology and Evolution

133

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Climate change and biological invasions are threatening biodiversity and ecosystem services worldwide. It has now been widely acknowledged that climate change will affect biological invasions. A large number of studies have investigated predicted shifts and other changes in the geographic ranges of invasive alien species related to climate change using modeling approaches. Yet these studies have provided contradictory evidence, and no consensus has been reached. We conducted a systematic review of 423 modeling case studies included in 71 publications that have examined the predicted effects of climate change on those species. We differentiate the approaches used in these studies and synthesize their main results. Our results reaffirm the major role of climate change as a driver of invasive alien species distribution in the future. We found biases in the literature both regarding the taxa, toward plants and invertebrates, and the areas of the planet investigated. Despite these biases, we found for the plants and vertebrates studied that climate change will more frequently contribute to a decrease in species range size than an increase in the overall area occupied. This is largely due to oceans preventing terrestrial invaders from spreading poleward. In contrast, we found that the ranges of invertebrates and pathogens studied are more likely to increase following climate change. An important caveat to these findings is that researchers have rarely considered the effects of climate change on transport, introduction success, or the resulting impacts. We recommend closing these research gaps, and propose additional avenues for future investigations, as well as opportunities and challenges for managing invasions under climate change.

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“…Data here are presented as mean±standard deviation based on multi-replicates. We used the ensemble-forecasting approach to reach a consensus scenario (Araújo and New 2007) and obtained one final predicted distribution from the average output of the 10 cross-validated replicates for each species. We used the 10th percentile training presence threshold, which is considered as a highly conservative estimate of a species' tolerance to each environmental variable and can therefore provide more ecologically significant results (Svenning et al 2008).…”

Section: Model Evaluation Comparison and Interpredictivity Assessmentmentioning

confidence: 99%

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

Jiang

2012

Naturwissenschaften

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Species distribution modeling (SDM) is increasingly used to reveal biogeographical relationships, for example the sympatric range for species coexistence, and fundamental questions about niche evolution between related species. We explored the sympatric ranges between three Procapra species (Procapra przewalskii, Procapra Picticaudata, and Procapra gutturosa) via two methods of defining the study region (method 1, in which models were developed in a larger region including the whole geographic range of Procapra, and method 2 in which a smaller region surrounding focal species' localities was used and then projected to the larger region). We also quantified environmental niche divergence between gazelles across the whole range in Procapra. Models for gazelles generally performed well. Compared with method 2, method 1 led to larger predicted areas with high suitability and was less concentrated around known localities. Clamping, which deals with variables outside the training range, varied between gazelles and occurred primarily in regions unsuitable for respective species. For all gazelle pairs, models revealed an overlap zone where more than one species should occur, while the estimates varied between the two methods. Moreover, we found that the niche overlap was closely associated with geographic distance but not with phylogenetic distance among gazelles. Our findings indicate that SDM is a useful tool for testing whether related species tend to be in sympatry at large scales, with method 1 leading to more realistic predictions for Procapra. This study provides evidence of a distinct niche divergence among related species and supports the theory that ecological speciation plays a significant role in lineage generation.

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Ensemble forecasting of species distributions

Cited by 2,600 publications

References 51 publications

Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal

Present habitat suitability for Anopheles atroparvus (Diptera, Culicidae) and its coincidence with former malaria areas in mainland Portugal

Insights from modeling studies on how climate change affects invasive alien species geography

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

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