Predicting seasonal habitat suitability for the critically endangered African wild ass in the Danakil, Ethiopia

Kebede, Fanuel; Moehlman, Patricia D.; Bekele, Afework; Evangelista, Paul

doi:10.1111/aje.12159

Cited by 20 publications

(17 citation statements)

References 27 publications

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“…In order to recognize areas susceptible to infestation, the Maxent logistic output was converted to two binary presence/absence climate suitability maps, one with suitable and the other with optimal climatic conditions. These maps were based on two thresholds provided by Maxent, the ‘minimum training presence logistic threshold’ that indicates values above which the climatic conditions are suitable, and the ‘maximum test sensitivity plus specificity logistic threshold’ that indicates values above which the climatic conditions are optimal (Kebede et al , 2014). Both binary maps were superimposed with a map of the actual harvested regions of cassava downloaded from Monfreda et al (2008).…”

Section: Methodsmentioning

confidence: 99%

Predicting the potential invasion suitability of regions to cassava lacebug pests (Heteroptera: Tingidae:Vatigaspp.)

Montemayor

Dellapé

Melo

2014

Bull. Entomol. Res.

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Cassava (Manihot esculenta Crantz) is one of the most important staple crops for small farmers in the tropics, feeding about 800 million people worldwide. It is currently cultivated in South and Central America, Africa and Asia. The genus Vatiga is widespread throughout the Neotropical region. Its species are sympatric and feed exclusively on cassava. The main objectives of this paper are: (1) to assess the potential distribution of Vatiga, one of the most relevant pests of cassava; (2) to project the resulting models onto the world; (3) to recognize areas with suitable and optimal climates (and thus, high probability) for future colonization, and (4) to compare this model with the harvested area of cassava analyzing the climatic variables required by both the host and the pest species. Species distribution models were built using Maxent (v3.3.3k) with bioclimatic variables from the WorldClim database in 2.5 arc min resolution across the globe. Our model shows that Vatiga has the potential to expand its current distribution into other suitable areas, and could invade other regions where cassava is already cultivated, e.g., Central Africa and Asia. Considering the results and the high host specificity of Vatiga, its recent appearance in Réunion Island (Africa) poses a serious threat, as nearby areas are potentially suitable for invasion and could serve as dispersal routes enabling Vatiga to reach the continent. The present work may help prevention or early detection of Vatiga spp. in areas where cassava is grown.

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Section: Methodsmentioning

confidence: 99%

Predicting the potential invasion suitability of regions to cassava lacebug pests (Heteroptera: Tingidae:Vatigaspp.)

Montemayor

Dellapé

Melo

2014

Bull. Entomol. Res.

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“…, Kebede et al. ) and provide refuge for others that were once common across the continent (Durant et al. ).…”

Section: Introductionmentioning

confidence: 99%

Integrating indigenous local knowledge and species distribution modeling to detect wildlife in Somaliland

Evangelista

Mohamed²,

Hussein³

et al. 2018

Ecosphere

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Abstract. With wildlife populations in decline, understanding their distributions across the landscape are needed for management and conservation efforts, particularly in remote or hazardous regions. We used indigenous local knowledge to inform species distribution models (SDMs) to predict the distribution of 38 wildlife species historically documented in Somaliland, one of the most isolated, data-poor regions in Africa. We conducted 195 interviews with agro-pastoral men and women in 2016 and 2017 throughout Somaliland based on the environmental range captured by performing a Multivariate Environmental Similarity Surface (MESS) analysis. Respondents were asked if each species (1) occurred in the vicinity, and if they did, (2) whether it was common, rare, extirpated, or unknown. We tested two commonly used SDMs, Maxent and boosted regression trees (BRTs), to map the potential distribution of wildlife using interview data. We present detailed case studies of two species of high conservation priority: cheetah (Acinonyc jubatus) and African wild ass (Equus africanus somaliensis). More than half of the respondents reported the presence of 25 of the wildlife species in the survey. Additionally, we developed Maxent models for all surveyed wildlife known to develop a species richness map. The least reported species known to have inhabited Somaliland in recent decades were lion (Panthera leo), African wild ass, and Somali wild dog (Lycaon pictus somalicus). Surprisingly, 177 of respondents reported the presence of cheetah, which was presumed by many to be extirpated from Somaliland. Given the high number of reports, coupled with the BRT model results and evaluations, it may be that cheetahs persist throughout Somaliland. Unfortunately, our results also suggest that African wild ass may have been extirpated from Somaliland. Our models carry the uncertainties of the raw data, but provide habitat suitability maps to guide future targeted surveys. Our methods and results demonstrate that integrating indigenous local knowledge with SDMs may be an essential tool for the conservation of wildlife in data-poor regions.

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“…The parameters used for modeling were those displayed by default by MaxEnt version 3.3.3k, except for the "Extrapolate" and "Do clamping" parameters, which were disabled; the data output was logistic. The models obtained were validated using a cut-off threshold value equal to the maximum test sensitivity plus specificity (Liu et al 2005), which maximizes the cases where the model erroneously assigns an unsuitable habitat (true negative) and ignores the suitable habitat (false positive); this approach is very common when using MaxEnt (Ferraz et al 2012;Jorge et al 2013;Kebede et al 2014). In addition, we conducted a preliminary validation by calculating the area under the curve (AUC = Area under a Receiver Operating Characteristic [ROC] Curve).…”

Section: Methodsmentioning

confidence: 99%

Predictive species distribution model of two endemic kangaroo rats from Mexico: Dipodomys ornatus and D. phillipsii (Rodentia: Heteromyidae)

Flores-Zamarripa

Fernández

2018

Therya

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Predictive species distribution models (SDMs) allow identifying suitable areas for the conservation of populations of endangered species. Dipodomys ornatus and D. phillipsii are two Nearctic rodents endemic to Mexico that inhabit arid and semiarid environments. Endemic species have a restricted distribution, making it difficult to monitor their distribution and conservation status. Therefore, it is important to understand the interactions between these species and the environmental/ecological variables in their local habitat. In this study, we constructed SDMs for these two rodents using MaxEnt (Maximum Entropy model). Also, we defined the areas with the suitable ecological characteristics for the preservation of the species. In order to construct an SDM for each species, we used MaxEnt at a national scale (Mexico), with a resolution of 30 arc-sec (1 km 2 ). To this end, 91 presence data (63 for D. ornatus and 28 for D. phillipsii) reported in the literature and data bases were used, along with 27 climatic and ecological variables. Maps with a high predictive capability (Area under a Receiver Operating Characteristic [ROC] Curve = AUC > 0.9) were obtained for both species. Principal Component Analyses were carried out, resulting in 11 PCs that accounted for 95% of variability of the original environmental variables. The D. ornatus SDM is defined mainly by PC2, PC11 and PC1. PC4, PC2 and PC6 are the most influential variables in predicting the SDM of D. phillipsii. Sites with suitable environmental conditions for D. ornatus are located in the States of Durango, Zacatecas, Aguascalientes, San Luis Potosí, and Guanajuato, whereas the best environmental conditions for D. phillipsii were found in Puebla, Tlaxcala, Veracruz, and Hidalgo. As these species have a restricted distribution and field sampling is difficult, determining their conservation status is a complex issue; however, SDMs are a useful tool to identify areas with ideal characteristics to conduct surveys aimed at determining their conservation status or that could be used as future natural protected areas.Los modelos predictivos de distribución de especies (MDE), permiten identificar áreas con condiciones adecuadas para la conservación de especies en peligro de extinción. Dipodomys ornatus y D. phillipsii, son dos roedores neárticos, endémicos de México, que habitan principalmente en regiones áridas y semiáridas. Las especies endémicas poseen una distribución restringida, lo que dificulta monitorear su distribución y estado de conservación. Por lo tanto, es importante comprender las interacciones que existen entre las especies y las variables ambientales/ ecológicas de los sitios donde estas habitan. En este estudio, se realizó un MDE de estos dos roedores utilizando MaxEnt (Modelo de máxima entropía). También se definieron áreas con las características ecológicas necesarias para la sobrevivencia de las especies que pueden ser utilizadas en programas futuros de conservación. Para construir el MDE, se utilizó el modelo MaxEnt a una escala nacional (México)...

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Predicting seasonal habitat suitability for the critically endangered African wild ass in the Danakil, Ethiopia

Cited by 20 publications

References 27 publications

Predicting the potential invasion suitability of regions to cassava lacebug pests (Heteroptera: Tingidae:Vatigaspp.)

Predicting the potential invasion suitability of regions to cassava lacebug pests (Heteroptera: Tingidae:Vatigaspp.)

Integrating indigenous local knowledge and species distribution modeling to detect wildlife in Somaliland

Predictive species distribution model of two endemic kangaroo rats from Mexico: Dipodomys ornatus and D. phillipsii (Rodentia: Heteromyidae)

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