Should species distribution models use only native or exotic records of existence or both?

Shabani, Farzin; Kumar, Lalit

doi:10.1016/j.ecoinf.2015.07.006

Cited by 22 publications

(6 citation statements)

References 47 publications

(50 reference statements)

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“…Furthermore, the low and moderate success of the AIWs in projections based on the native and invasive ranges, respectively, indicated that the AIWs are likely to expand more extensively into China than in their native ranges owing to more favorable habitat suitability in China (Collingham et al., ; Hoffmann & Sgrò, ; Warren & Seifert, ; Beaumont et al., ). Our results, together with those of previous studies (Gallien et al., ; Mainali et al., ; Shabani & Kumar, ), suggest that the occurrence records of both native and invasive ranges should be used in applying ENMs for the assessment of plant invasion.…”

Section: Discussionsupporting

confidence: 83%

“…Furthermore, the values of overlap between the native and invasive niches were extremely low, and the niche expansion of some species was large, for example, for A. retroflexus and C. Canadensis . This highlights the partial niche overlap between the native and invasive ranges and the difficulty of pre‐introduction weed risk assessment (Gallien et al., ; Hulme, ; Early & Sax, ; Shabani & Kumar, ; Table ). It is not sensible to predict the spread risk of AIWs in the invade regions based on the occurrence records of either native ranges or invasive ranges (Early & Sax, ).…”

Section: Discussionmentioning

confidence: 99%

“…Maxent (ver.3.3.3k; http://www.cs.princeton.edu/~schapire/maxent/) was used to model spatial distributions and produce habitat suitability maps of the AIWs for the present‐day scenarios based on bioclimatic variables and occurrence records (Merow et al., ). For the modeling, we accounted for occurrence records in both the invasive and native ranges because it improves the performance of ecological niche modeling (Merow et al., ; Mainali et al., ; Shabani & Kumar, ; Figure ). In our study, three models were built using the occurrence records of native, invasive, and both native and invasive ranges, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

Wan

Wang

Tan

et al. 2017

Ecology and Evolution

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Testing climatic niche divergence and modeling habitat suitability under conditions of climate change are important for developing strategies to limit the introduction and expansion of alien invasive weeds ( AIW s) and providing important ecological and evolutionary insights. We assessed climatic niches in both native and invasive ranges as well as habitat suitability under climate change for eight representative Chinese AIW s from the American continent. We used climatic variables associated with occurrence records and developed ecological niche models with Maxent. Interestingly, the climatic niches of all eight AIW s diverged significantly between the native and invasive ranges (the American continent and China). Furthermore, the AIW s showed larger climatic niche breadths in the invasive ranges than in the native ranges. Our results suggest that climatic niche shifts between native and invasive ranges occurred. Thus, the occurrence records of both native and invasive regions must be considered when modeling and predicting the spatial distributions of AIW s under current and future climate scenarios. Owing to high habitat suitability, AIW s were more likely to expand into regions of low latitude, and future climate change was predicted to result in a shift in the AIW s in Qinghai and Tibet (regions of higher altitude) as well as Heilongjiang, Jilin, Liaoning, Inner Mongolia, and Gansu (regions of higher latitude). Our results suggest that we need measures to prevent and control AIW expansion at the country‐wide level.

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Section: Discussionsupporting

confidence: 83%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

Wan

Wang

Tan

et al. 2017

Ecology and Evolution

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“…The global, Australian, and the modified distribution records of all eight species are summarized in Table . The dataset includes the total of both native and exotic distribution records (Shabani and Kumar ), as it was beyond the study scope to differentiate the effect of including only native, exotic, or both, on the abilities of techniques to project climate suitability.…”

Section: Methodsmentioning

confidence: 99%

A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area

Shabani

Kumar

Ahmadi

2016

Ecology and Evolution

Self Cite

223

170

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To investigate the comparative abilities of six different bioclimatic models in an independent area, utilizing the distribution of eight different species available at a global scale and in Australia. Global scale and Australia. We tested a variety of bioclimatic models for eight different plant species employing five discriminatory correlative species distribution models (SDMs) including Generalized Linear Model (GLM), MaxEnt, Random Forest (RF), Boosted Regression Tree (BRT), Bioclim, together with CLIMEX (CL) as a mechanistic niche model. These models were fitted using a training dataset of available global data, but with the exclusion of Australian locations. The capabilities of these techniques in projecting suitable climate, based on independent records for these species in Australia, were compared. Thus, Australia is not used to calibrate the models and therefore it is as an independent area regarding geographic locations. To assess and compare performance, we utilized the area under the receiver operating characteristic (ROC) curves (AUC), true skill statistic (TSS), and fractional predicted areas for all SDMs. In addition, we assessed satisfactory agreements between the outputs of the six different bioclimatic models, for all eight species in Australia. The modeling method impacted on potential distribution predictions under current climate. However, the utilization of sensitivity and the fractional predicted areas showed that GLM, MaxEnt, Bioclim, and CL had the highest sensitivity for Australian climate conditions. Bioclim calculated the highest fractional predicted area of an independent area, while RF and BRT were poor. For many applications, it is difficult to decide which bioclimatic model to use. This research shows that variable results are obtained using different SDMs in an independent area. This research also shows that the SDMs produce different results for different species; for example, Bioclim may not be good for one species but works better for other species. Also, when projecting a “large” number of species into novel environments or in an independent area, the selection of the “best” model/technique is often less reliable than an ensemble modeling approach. In addition, it is vital to understand the accuracy of SDMs' predictions. Further, while TSS, together with fractional predicted areas, are appropriate tools for the measurement of accuracy between model results, particularly when undertaking projections on an independent area, AUC has been proved not to be. Our study highlights that each one of these models (CL, Bioclim, GLM, MaxEnt, BRT, and RF) provides slightly different results on projections and that it may be safer to use an ensemble of models.

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“…Species distribution models (SDMs) are frequently used to predict the current and future geographic distribution of IAVPs [11,12,20] due to their ability to be applied to species that cannot be directly detected because they are small, elusive or inhabit remote locations. Typically, correlative SDMs apply an algorithm, such as maximum entropy, boosted regression trees or random forest, that combines empirical occurrence data on the species with relevant environmental data (e.g., average temperature and precipitation) to predict the spatial and temporal distributions of a species [21,22]. Mechanistic models, such as compartmental or agent-based models have also been developed, alone or in combination with correlative models, to characterize potential species distributions [23,24].…”

Section: Linking Environmental Earth Data and Iavpsmentioning

confidence: 99%

A Lack of “Environmental Earth Data” at the Microhabitat Scale Impacts Efforts to Control Invasive Arthropods That Vector Pathogens

Pascoe

Pareeth

Rocchini

et al. 2019

Data

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We currently live in an era of major global change that has led to the introduction and range expansion of numerous invasive species worldwide. In addition to the ecological and economic consequences associated with most invasive species, invasive arthropods that vector pathogens (IAVPs) to humans and animals pose substantial health risks. Species distribution models that are informed using environmental Earth data are frequently employed to predict the distribution of invasive species, and to advise targeted mitigation strategies. However, there are currently substantial mismatches in the temporal and spatial resolution of these data and the environmental contexts which affect IAVPs. Consequently, targeted actions to control invasive species or to prepare the population for possible disease outbreaks may lack efficacy. Here, we identify and discuss how the currently available environmental Earth data are lacking with respect to their applications in species distribution modeling, particularly when predicting the potential distribution of IAVPs at meaningful space-time scales. For example, we examine the issues related to interpolation of weather station data and the lack of microclimatic data relevant to the environment experienced by IAVPs. In addition, we suggest how these data gaps can be filled, including through the possible development of a dedicated open access database, where data from both remotely- and proximally-sensed sources can be stored, shared, and accessed.

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Should species distribution models use only native or exotic records of existence or both?

Cited by 22 publications

References 47 publications

Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

Climatic niche divergence and habitat suitability of eight alien invasive weeds in China under climate change

A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area

A Lack of “Environmental Earth Data” at the Microhabitat Scale Impacts Efforts to Control Invasive Arthropods That Vector Pathogens

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