NicheA: creating virtual species and ecological niches in multivariate environmental scenarios

Qiao, Huijie; Peterson, A. Townsend; Campbell, Lindsay P.; Soberón, Jorge; Ji, Liqiang; Escobar, Luis E.

doi:10.1111/ecog.01961

Cited by 177 publications

(177 citation statements)

References 66 publications

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“…3.0 (Qiao et al 2016), with eight distinct niche centers and two radii (1.5 and 2.0, corresponding to narrow and wide niches, respectively; Supplementary material Appendix 1 Fig. 3.0 (Qiao et al 2016), with eight distinct niche centers and two radii (1.5 and 2.0, corresponding to narrow and wide niches, respectively; Supplementary material Appendix 1 Fig.…”

Section: Virtual Species In a Real Landscapementioning

confidence: 99%

An evaluation of transferability of ecological niche models

et al. 2018

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Ecological niche modeling (ENM) is used widely to study species’ geographic distributions. ENM applications frequently involve transferring models calibrated with environmental data from one region to other regions or times that may include novel environmental conditions. When novel conditions are present, transferability implies extrapolation, whereas, in absence of such conditions, transferability is an interpolation step only. We evaluated transferability of models produced using 11 ENM algorithms from the perspective of interpolation and extrapolation in a virtual species framework. We defined fundamental niches and potential distributions of 16 virtual species distributed across Eurasia. To simulate real situations of incomplete understanding of species’ distribution or existing fundamental niche (environmental conditions suitable for the species contained in the study area; N* F ), we divided Eurasia into six regions and used 1–5 regions for model calibration and the rest for model evaluation. The models produced with the 11 ENM algorithms were evaluated in environmental space, to complement the traditional geographic evaluation of models. None of the algorithms accurately estimated the existing fundamental niche (N* F ) given one region in calibration, and model evaluation scores decreased as the novelty of the environments in the evaluation regions increased. Thus, we recommend quantifying environmental similarity between calibration and transfer regions prior to model transfer, providing an avenue for assessing uncertainty of model transferability. Different algorithms had different sensitivity to completeness of knowledge of N* F , with implications for algorithm selection. If the goal is to reconstruct fundamental niches, users should choose algorithms with limited extrapolation when N* F is well known, or choose algorithms with increased extrapolation when N* F is poorly known. Our assessment can inform applications of ecological niche modeling transference to anticipate species invasions into novel areas, disease emergence in new regions, and forecasts of species distributions under future climate conditions.

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Section: Virtual Species In a Real Landscapementioning

confidence: 99%

An evaluation of transferability of ecological niche models

et al. 2018

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“…To facilitate this process, the workflow of the analyses developed here is included as Supplementary Material S6 to be executed in NicheA (21) and includes data to replicate this workflow (Supplementary Material S6). Step-by-step instructions to estimate N F of any species can also be found in the website of NicheA 2 …”

Section: Discussionmentioning

confidence: 99%

“…First, we highlight the importance of data curation and show a method for outlier removal in environmental dimensions based on a priori assumptions. Also, the ecological niche modeling algorithms proposed require low parameterization as they are based on the position (MVE) and density (Marble) of occurrences in an environmental space (22, 30), but also require a series of biological assumptions to make the outputs interpretable [e.g., Fundamental Niches of an ellipsoidal shape (21)]. We found that exploring algorithms of different analytical nature such as those aiming to fit environmental clusters, climatic envelopes, and logistic regressions (e.g., Marble, MVE, and Maxent) provided different scenarios of the potential distribution of Heterosporosis.…”

Section: Discussionmentioning

confidence: 99%

Novel Methods in Disease Biogeography: A Case Study with Heterosporosis

et al. 2017

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Disease biogeography is currently a promising field to complement epidemiology, and ecological niche modeling theory and methods are a key component. Therefore, applying the concepts and tools from ecological niche modeling to disease biogeography and epidemiology will provide biologically sound and analytically robust descriptive and predictive analyses of disease distributions. As a case study, we explored the ecologically important fish disease Heterosporosis, a relatively poorly understood disease caused by the intracellular microsporidian parasite Heterosporis sutherlandae. We explored two novel ecological niche modeling methods, the minimum-volume ellipsoid (MVE) and the Marble algorithm, which were used to reconstruct the fundamental and the realized ecological niche of H. sutherlandae, respectively. Additionally, we assessed how the management of occurrence reports can impact the output of the models. Ecological niche models were able to reconstruct a proxy of the fundamental and realized niche for this aquatic parasite, identifying specific areas suitable for Heterosporosis. We found that the conceptual and methodological advances in ecological niche modeling provide accessible tools to update the current practices of spatial epidemiology. However, careful data curation and a detailed understanding of the algorithm employed are critical for a clear definition of the assumptions implicit in the modeling process and to ensure biologically sound forecasts. In this paper, we show how sensitive MVE is to the input data, while Marble algorithm may provide detailed forecasts with a minimum of parameters. We showed that exploring algorithms of different natures such as environmental clusters, climatic envelopes, and logistic regressions (e.g., Marble, MVE, and Maxent) provide different scenarios of potential distribution. Thus, no single algorithm should be used for disease mapping. Instead, different algorithms should be employed for a more informed and complete understanding of the pathogen or parasite in question.

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“…Para a visualização da distribuição das espécies em condições climáticas atuais, realizou-se uma análise de componentes principais (PCA) para reduzir a dimensionalidade e colinearidade das variáveis ambientais e utilizou-se poliedros convexos em torno de ocorrências disponíveis para cada espécie de carrapato em um espaço ambiental definido pelos três primeiros componentes gerados a partir da PCA, pois estes continham 92,43% da informação para A. cajennense ss e 88,73% da informação para A. sculptum das sete variáveis bioclimáticas originais (Material Suplementar S1); Ambos os procedimentos foram realizados usando software NicheA versão 3.0 (Qiao et al, 2016). Estes cenários são baseados na via de concentração representativa de 8,5 (RCP 8.5) e exploram o uso demográfico, socioeconômico e da terra para estimar diferentes emissões de gases .…”

Section: Obtenção Dos Dadosunclassified

Febre Maculosa No Brasil: Situação Epidemiológica Atual E a Distribuição Geográfica De Carrapatos Em Cenários De Mudanças Climáticas

Oliveira¹,

Gonçalves²

2017

Rev. baiana de saúde pública

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No Brasil, os quadros clínicos da febre maculosa podem ser resultantes da infecção por duas espécies de riquétsias. Rickettsia rickettsii é registrada na região Sul e Sudeste e está relacionada a casos graves da doença. Rickettsia sp. cepa Mata Atlântica foi identificada no Sul, Sudeste e Nordeste, causando febre maculosa mais branda. Febre maculosa é doença de notificação compulsória ao Ministério da Saúde que promove ações de vigilância epidemiológica e assistência médica com o objetivo de reduzir a morbimortalidade. No entanto, a doença ainda é pouco conhecida. Sabe-se que os carrapatos do gênero Amblyomma atuam como vetores, podendo parasitar hospedeiros silvestres, domésticos e eventualmente o homem. O conhecimento da distribuição geográfica potencial desses vetores torna-se importante nas ações de vigilância epidemiológica. Dessa forma, o presente estudo tem os seguintes objetivos: 1) atualizar o perfil epidemiológico da febre maculosa no Brasil; 2) avaliar preditores de evolução fatal por febre maculosa; 3) analisar a distribuição geográfica potencial de carrapatos do Complexo Amblyomma cajennese em cenário atual e futuro sob influência das mudanças climáticas. Na primeira abordagem, verificamos o crescente número de registros da doença nos últimos anos e observamos a expansão espacial da febre maculosa no país com uma ascendente taxa de letalidade. Por meio desses registros, um estudo do tipo caso-controle avaliou fatores preditores de evolução fatal por febre maculosa. Neste, verificou-se que residir em área urbana, relatar a presença de carrapato e apresentar quadro clínico com presença de linfadenopatia são fatores protetores. Enquanto os sinais de gravidade como hipotensão, choque, estupor, coma e convulsão estão associados as maiores chances de morte. Quando analisamos a distribuição geográfica potencial de carrapatos do Complexo Amblyoma cajenennese utilizando a modelagem de nicho ecológico, verificamos que áreas do Cerrado, Amazônia, Pantanal e Mata Atlântica apresentam ampla adequabilidade para manutenção dessas espécies. No entanto, em cenários de mudanças climáticas, verificamos uma tendência de redução dessas áreas (nos anos de 2050 e 2070). Nossos dados indicam que a presença do vetor pode ser restringida (e consequentemente a doença), se considerarmos a não adaptação dos carrapatos aos novos climas. Os métodos empregados neste estudo buscam, de forma complementar, o entendimento epidemiológico da febre maculosa e poderão ser utilizados para predição, prevenção e, consequentemente, para redução da morbimortalidade desta importante doença no Brasil. Palavras-chave: Epidemiologia. Riquetsiose. Doença transmitida por carrapato. Modelagem de nicho ecológico. Amblyomma.

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NicheA: creating virtual species and ecological niches in multivariate environmental scenarios

Cited by 177 publications

References 66 publications

An evaluation of transferability of ecological niche models

An evaluation of transferability of ecological niche models

Novel Methods in Disease Biogeography: A Case Study with Heterosporosis

Febre Maculosa No Brasil: Situação Epidemiológica Atual E a Distribuição Geográfica De Carrapatos Em Cenários De Mudanças Climáticas

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