Spatial conservation planning under climate change: Using species distribution modeling to assess priority for adaptive management of Fagus crenata in Japan

2013 ◽  
Vol 21 (6) ◽  
pp. 406-413 ◽  
Author(s):  
Katsuhiro Nakao ◽  
Motoki Higa ◽  
Ikutaro Tsuyama ◽  
Tetsuya Matsui ◽  
Masahiro Horikawa ◽  
...  
Keyword(s):  
Climate Change ◽  
Adaptive Management ◽  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Modeling ◽  
Fagus Crenata ◽  
Distribution Modeling ◽  
Spatial Conservation Planning

Species Distribution Modeling of the Threatened Blanding's Turtle's (Emydoidea blandingii) Range Edge as a Tool for Conservation Planning

2016 ◽  
Vol 50 (3) ◽  
pp. 366-373 ◽  
Author(s):  
Kinga M. Stryszowska ◽  
Glenn Johnson ◽  
Lorianny Rivera Mendoza ◽  
Tom A. Langen
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Modeling ◽  
Emydoidea Blandingii ◽  
Range Edge ◽  
Distribution Modeling

Vulnerability of subalpine fir species to climate change: using species distribution modeling to assess the future efficiency of current protected areas in the Korean Peninsula

2018 ◽  
Vol 33 (2) ◽  
pp. 341-350 ◽  
Author(s):  
Jong‐Hak Yun ◽  
Katsuhiro Nakao ◽  
Ikutaro Tsuyama ◽  
Tetsuya Matsui ◽  
Chan‐Ho Park ◽  
...  
Keyword(s):  
Climate Change ◽  
Protected Areas ◽  
Species Distribution ◽  
Korean Peninsula ◽  
Species Distribution Modeling ◽  
Subalpine Fir ◽  
Distribution Modeling ◽  
The Future

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 Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation

2009 ◽  
Vol 2 (3) ◽  
pp. 319-352 ◽  
Author(s):  
L. Cayuela ◽  
D. J. Golicher ◽  
A. C. Newton ◽  
M. Kolb ◽  
F. S. de Alburquerque ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Quality ◽  
Central America ◽  
Species Distribution ◽  
Conservation Planning ◽  
Tree Species ◽  
Species Distribution Modeling ◽  
Tropical Regions ◽  
Distribution Modeling ◽  
The Tropics

In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in ecology and conservation, and examined two tropical case studies in which distribution modeling is currently being applied to support conservation planning. We also analyzed the characteristics of data typically used for fitting models within the specific context of modeling tree species distribution in Central America. The results showed that methodological papers outnumbered reports of SDMs being used in an applied context for setting conservation priorities, particularly in the tropics. Most applications of SDMs were in temperate regions and biased towards certain organisms such as mammals and birds. Studies from tropical regions were less likely to be validated than those from temperate regions. Unpublished data from two major tropical case studies showed that those species that are most in need of conservation actions, namely those that are the rarest or most threatened, are those for which SDM is least likely to be useful. We found that only 15% of the tree species of conservation concern in Central America could be reliably modelled using data from a substantial source (Missouri Botanical Garden VAST database). Lack of data limits model validation in tropical areas, further restricting the value of SDMs. We concluded that SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change. However, for this potential to be fully realized, problems of data quality and availability need to be overcome. Weaknesses in current biological datasets need to be systematically addressed, by increasing collection of field survey data, improving data sharing and increasing structural integration of data sources. This should include use of distributed databases with common standards, referential integrity, and rigorous quality control. Integration of data management with SDMs could significantly add value to existing data resources by improving data quality control and enabling knowledge gaps to be identified.

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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