Predicting invasions of Wedelia trilobata (L.) Hitchc. with Maxent and GARP models

Qin, Zhong; Zhang, Jiaen; DiTommaso, Antonio; Wang, Rui-long; Wu, Rui-shan

doi:10.1007/s10265-015-0738-3

Cited by 58 publications

(41 citation statements)

References 40 publications

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“…For example, Padalia et al (2014) examined the use of GARP and Maxent and reported that Maxent had a greater predicting power than GARP. However, Qin et al (2015) concluded the opposite; for large sample sizes (n > 150) like ours, which used 634 GARP training points, Terribile and Diniz-Filho (2010) reported that Maxent and GARP were similar in their predicted areas. One of the commonly stated weaknesses of GARP is its potential to overestimate the geographic range and generate false positives (Elith andGraham 2009, Sobek-Swant et al 2012).…”

Section: Discussionmentioning

confidence: 62%

“…Studies of roost selection by tree bats found that a closed canopy is an important variable for eastern red bats (Menzel et al 1998, Kalcounis-Rüppell et al 2005), so we included percent tree cover as a variable. Throughout different studies, elevation is used as a variable in some GARP models (Peterson et al 2002, McNyset 2005, Qin et al 2015 but not by others (Kostelnick et al 2007, Sobek-Swant et al 2012, Padalia et al 2014. These studies span a wide range of species and spatial scales that can affect whether to include elevation as a variable.…”

Section: Modeling Summer Rangesmentioning

confidence: 99%

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Red bat fatality: Geographic extents through deuterium and niche models

et al. 2019

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Bat fatality at wind energy facilities is a conservation issue, but its effect on bat populations is difficult to estimate. We have little understanding of wind turbine effects on bat population persistence, in part because we have poor knowledge of bat migration pathways and hence the source populations for individual fatalities. We used deuterium ratio analysis combined with genetic algorithm for rule‐set prediction and the web‐based isoscapes modeling, analysis, and prediction in a geographic information system environment as a novel approach. Our objectives were to explore the utility of these methods together and map the geographic extents of eastern red bat (Lasiurus borealis) specimens salvaged in 2008–2010 from a single, 92‐km2 wind energy facility in Illinois, USA. Results indicate that combining these methods can be successful and support their use with species where ranges may be less well defined. Because of the migratory nature of this species and the range of deuterium values of pixels in our isotope model, we predicted that 18% and 82% of the specimens would have isotope results inside and outside of the wind facility's isocline respectively. We concluded that 71.4% of the specimens had isotope signatures placing them outside the wind facility's isocline. It could be argued that the wide distribution of bat fatalities dilutes the overall effect of those fatalities on the bat species; however, if other facilities show a similar pattern, each facility could have cumulative and far reaching population‐level effects. © 2019 The Wildlife Society.

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Section: Discussionmentioning

confidence: 62%

Section: Modeling Summer Rangesmentioning

confidence: 99%

Red bat fatality: Geographic extents through deuterium and niche models

et al. 2019

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“…Maxent is a general-purpose machine learning method with a simple and precise mathematical formulation, and it has a number of aspects that make it well-suited for modeling species distribution [31]. We selected this software for the following reasons: (1) MaxEnt Models are widely used in species distribution predictions [47]; (2) it is better at predicting the effect of climate change on species distribution and suitable area division compared to other ENMs, such as GARP and BLOCLIM [48]; (3) Maxent model results are more conservative [49]; and (4) Maxent estimates the distribution (geographic range) of a species by finding the distribution that has maximum entropy (i.e., is closest to geographically uniform), and this can be constrained based on the environmental conditions at recorded occurrence locations [50,51].…”

Section: Environmental Niche Modelsmentioning

confidence: 99%

The Potential Global Distribution of the White Peach Scale Pseudaulacaspis pentagona (Targioni Tozzetti) under Climate Change

Zhao

Cheng

et al. 2020

Forests

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The white peach scale Pseudaulacaspis pentagona (Hemiptera: Diaspididae) is a pest that causes significant damage to more than 221 genera of host plants in more than 112 countries. P. pentagona primarily feeds on mulberry, peach, and tea, and this leads to the loosening of the epidermis of trees, which damages nutrient and water transportation in the branches, leading to branch death. P. pentagona is native to China and Japan, and has become an invasive species all over the world. However, the potential distribution of P. pentagona remains unclear. In this study, a potential distribution map of P. pentagona was developed using current and future climate information using MaxEnt. The model indicates that Asia, Europe, South America and North America are a highly suitable habitat range for this species. The MaxEnt models for the potential distribution of P. pentagona for the 2050s and 2070s suggest that in the case of no significant increase or even decrease in the highly suitable area, the suitable area increased significantly on any future climatic scenarios. The predicted area gain in the suitable habitat is 2.82 × 10 7 km 2 , including more of Asia, such as China, Japan, and Mongolia, and also including India, in Europe, which shows an increase of 24.5% over the current habitat on RCP8.5 emission scenarios for the 2070s. With the warming of the climate, significant expansions are predicted in the suitable area, especially in Europe and East Asia. Under RCP8.5 for the 2050s, the model-predicted that the area of suitable habitat in China and the Korean Peninsula gains an increase of 18.8% over the current suitable habitat area. Under other climate scenarios, RCP8.5-2070s, the suitable areas were the largest, compared to projection for the current climate scenario (ca. 24.1% increase) which increased to 7.89 × 10 6 km 2 . In Europe, under RCP8.5 for the 2070s, the highly suitable areas were the largest, compared to the projection for the current climate scenario (ca. 46.2% increase), which increased to 8.64 × 10 5 km 2 , the area of suitable habitat suitability increased to 4.99 × 10 6 km 2 (29.2% increase of the current condition). Potential increases or decreases in distribution ranges were modeled under future climatic scenarios. This study suggests that the most important factor that influenced current distribution of this pest was temperature, and BIO3 (isothermality) was the most important factor that contributed to 48.6% of the potential distribution map. Given the rapid spread of P. pentagona and the serious risk this species poses to local ecosystems, warning modelling and practical strategies to prevent the establishment and expansion of this species should be sought. This distribution map will help governments to identify areas that are suitable for current and future infestations, and to optimize pest management strategies.

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“…From the conservation point of view, predicting geographical distribution of such hybrids is a first step in controlling their further spreading. Various modeling methods (heavily based on climatic data) have been used to predict distribution areas of naturalized or invasive plant species (e.g., Pattison and Mack, 2008;Qin et al, 2015;Wang and Xu, 2016). Unfortunately, there is a lack of study on modeling potential geographical distribution for hybrids between alien and native plant species that have the ability to produce their own offspring and become established.…”

Section: Introductionmentioning

confidence: 99%