scholarly journals Testing effects of Pleistocene climate change on the altitudinal and horizontal distributions of frogs from the Colombian Andes: a species distribution modeling approach

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrea Paz ◽  
Angélica González ◽  
Andrew J. Crawford
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Species Distribution Modeling ◽  
Testing Effects ◽  
Modeling Approach ◽  
Colombian Andes ◽  
Distribution Modeling ◽  
Pleistocene Climate ◽  
Pleistocene Climate Change

scholarly journals Is the future already here? The impact of climate change on the distribution of the eastern coral snake (Micrurus fulvius)

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4647 ◽  
Author(s):  
Jennifer N. Archis ◽  
Christopher Akcali ◽  
Bryan L. Stuart ◽  
David Kikuchi ◽  
Amanda J. Chunco
Keyword(s):  
Climate Change ◽  
United States ◽  
Species Distribution ◽  
Southeastern United States ◽  
Species Distribution Modeling ◽  
Future Climate ◽  
Range Shifts ◽  
Climate Data ◽  
Coral Snake ◽  
Distribution Modeling

Anthropogenic climate change is a significant global driver of species distribution change. Although many species have undergone range expansion at their poleward limits, data on several taxonomic groups are still lacking. A common method for studying range shifts is using species distribution models to evaluate current, and predict future, distributions. Notably, many sources of ‘current’ climate data used in species distribution modeling use the years 1950–2000 to calculate climatic averages. However, this does not account for recent (post 2000) climate change. This study examines the influence of climate change on the eastern coral snake (Micrurus fulvius). Specifically, we: (1) identified the current range and suitable environment of M. fulvius in the Southeastern United States, (2) investigated the potential impacts of climate change on the distribution of M. fulvius, and (3) evaluated the utility of future models in predicting recent (2001–2015) records. We used the species distribution modeling program Maxent and compared both current (1950–2000) and future (2050) climate conditions. Future climate models showed a shift in the distribution of suitable habitat across a significant portion of the range; however, results also suggest that much of the Southeastern United States will be outside the range of current conditions, suggesting that there may be no-analog environments in the future. Most strikingly, future models were more effective than the current models at predicting recent records, suggesting that range shifts may already be occurring. These results have implications for both M. fulvius and its Batesian mimics. More broadly, we recommend future Maxent studies consider using future climate data along with current data to better estimate the current distribution.

scholarly journals Better providers of habitat for Javan slow loris (Nycticebus javanicus E. Geoffroy 1812): A species distribution modeling approach in Central Java, Indonesia

2020 ◽  
Vol 21 (5) ◽  
Author(s):  
Mahfut Sodik ◽  
Satyawan Pudyatmoko ◽  
Pujo Semedi Hargo Yuwono ◽  
Muhammad Tafrichan ◽  
Muhammad Ali Imron
Keyword(s):  
Species Distribution ◽  
Species Distribution Modeling ◽  
Distribution Model ◽  
Suitable Habitat ◽  
Conservation Areas ◽  
Slow Loris ◽  
Modeling Approach ◽  
Central Java ◽  
Distribution Modeling ◽  
Central Java Province

Abstract. Sodik M, Pudyatmoko S, Yuwono PSH, Tafrichan M, Imron MA. 2020. Better providers of habitat for Javan slow loris (Nycticebus javanicus E. Geoffroy 1812): A species distribution modeling approach in Central Java, Indonesia. Biodiversitas 21: 1890-1900. The Javan slow loris is an arboreal and nocturnal primate endemic to Java, which is known to inhabit primary and secondary forest habitats, such as swamps, plantations, and bamboo forest. The population of the Javan slow loris continues to decline significantly due to forest degradation, habitat loss/fragmentation, and illegal trade. Conservation of this small primate in Java has been hampered by a paucity of local data on how conservation areas support this species. This study aims to build a spatial distribution model of the Javan slow loris and analyzing the role of each stakeholder plays on land use type to support the conservation of N. javanicus. By utilizing Species Distribution Modeling (SDM) with Maximum Entropy species distribution modeling approach, the researchers were able to highlight the importance of which conservation areas in Central Java that play crucial role to conserve the N. javanicus population. Data on the presence of the Javan slow loris was obtained from the result of a survey undertaken in 2017 and communication with researchers. Elevation, slope, landcover, rainfall, distance to road, distance to settlement, distance to river (water source), and NDVI were used as environmental variables. Results showed that 0.76% (25,715.4 ha) of the total area of the Central Java Province is suitable for their habitat. In addition, results revealed that 2.2% of suitable habitat is present within conservation areas, 4.6% in protected forest areas, and 93.2% outside of protected areas. The Javan slow loris is predicted to be mostly scattered in the northern part of Central Java Province. The Javan slow loris is widely distributed in plantations, their most dominant habitat. The findings of this study show that the small percentage of suitable habitat presents within protected forest and conservation areas cannot sustainably maintain the extant Javan slow loris population. Thus, it is important for the Indonesian government and other key related stakeholders to work together in combination with educating local communities to preserve the habitat and population of N. javanicus.

Computational Techniques for Biologic Species Distribution Modeling

2011 ◽  
pp. 308-325
Author(s):  
Pedro Corrêa ◽  
Mariana Carvalhaes ◽  
Antonio Saraiva ◽  
Fabrício Rodrigues ◽  
Elisângela Rodrigues ◽  
...  
Keyword(s):  
Climate Change ◽  
Maximum Entropy ◽  
Species Distribution ◽  
Potential Distribution ◽  
Species Distribution Modeling ◽  
Computational Techniques ◽  
Distribution Modeling ◽  
Occurrence Pattern ◽  
Conservation Of Biodiversity

Computational modeling techniques for species geographic distribution are critical to support the task of identifying areas with high risk of loss of Biodiversity. These tools can assist in the conservation of Biodiversity, in planning the use of non-inhabited regions, in estimating the risk of invasive species, in the proposed reintroduction programs for species and even in planning the protecting endangered species. Furthermore, such techniques can help to understand the effects of climate change and other changes in the geographical distribution of species. This chapter presents concepts related to the species distribution modeling and algorithms based on Neural Networks and Maximum Entropy as alternatives for modeling of species distribution. The algorithms were integrated into the open source tool called openModeller used by biologists and other researchers in this area. A case study of modeling the distribution of babaçu (Orbignya phalerata) in the Piauí State – Brazil is presented, evaluating the potential distribution of this species used to produce bioenergy. Fifty models were generated and merged the ten models with best accuracy for each algorithm. The results show that the models obtained by both are consistent. The models obtained with Maximum Entropy seem to reflect best the reality, considering the occurrence pattern of babaçu as a secondary species.

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