scholarly journals Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning

Ecosphere ◽  
2013 ◽  
Vol 4 (3) ◽  
pp. art42 ◽  
Author(s):  
S. L. Farrell ◽  
B. A. Collier ◽  
K. L. Skow ◽  
A. M. Long ◽  
A. J. Campomizzi ◽  
...  
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models

Very high resolution environmental predictors in species distribution models

2013 ◽  
Vol 38 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Jean-Nicolas Pradervand ◽  
Anne Dubuis ◽  
Loïc Pellissier ◽  
Antoine Guisan ◽  
Christophe Randin
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Environmental Data ◽  
Swiss Alps ◽  
Fine Scale ◽  
Distribution Models ◽  
Model Quality ◽  
Vegetation Height ◽  
Very High

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species’ micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions – and therefore local management – compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.

Overprediction of species distribution models in conservation planning: A still neglected issue with strong effects

2020 ◽  
Vol 252 ◽  
pp. 108822 ◽  
Author(s):  
Santiago José Elías Velazco ◽  
Bruno R. Ribeiro ◽  
Livia Maira Orlandi Laureto ◽  
Paulo De Marco Júnior
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models

Avoiding Pitfalls of Using Species Distribution Models in Conservation Planning

2003 ◽  
Vol 17 (6) ◽  
pp. 1591-1600 ◽  
Author(s):  
BETTE A. LOISELLE ◽  
CHRISTINE A. HOWELL ◽  
CATHERINE H. GRAHAM ◽  
JAQUELINE M. GOERCK ◽  
THOMAS BROOKS ◽  
...  
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models

scholarly journals Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e113749 ◽  
Author(s):  
Luciana L. Porfirio ◽  
Rebecca M. B. Harris ◽  
Edward C. Lefroy ◽  
Sonia Hugh ◽  
Susan F. Gould ◽  
...  
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models ◽  
Planning And Management

scholarly journals The explicit integration of Species Conceptual Models and Species Distribution Models as a best practice for systematic conservation planning in California

2021 ◽  
pp. 41-60
Author(s):  
Monica D. Parisi ◽  
Steven E. Greco
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Conceptual Models ◽  
Conservation Strategy ◽  
Systematic Conservation Planning ◽  
Community Conservation ◽  
Natural Community ◽  
Distribution Models ◽  
Conservation Plans

Natural Community Conservation Plans (NCCPs) represent the most powerful tool in statute for regional and systematic conservation planning for species at risk in California. This study examines the use of species conceptual models (SCMs) and species distribution models (SDMs) in such planning. Eighteen Natural Community Conservation Plans (NCCPs) were analyzed to determine if or how explicit connections were made between both types of models for a covered species and key components of its conservation strategy. Results indicate plans were strong in the use of SDMs, however, each deferred preparing or using SCMs to later management and monitoring phases. A more effective best planning practice for developing a conservation strategy is to explicitly integrate SCMs and SDMs during plan preparation.

Species distribution models for conservation planning in fire‐prone landscapes

2021 ◽  
Vol 30 (4) ◽  
pp. 1119-1136
Author(s):  
Matthew Swan ◽  
Mark Le Pla ◽  
Julian Di Stefano ◽  
Jack Pascoe ◽  
Trent D. Penman
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Distribution Models ◽  
In Fire

scholarly journals REBIOMA Data Portal, Tool for Conservation Planning in Madagascar

2018 ◽  
Vol 2 ◽  
pp. e25864
Author(s):  
Rabetrano Tsiky
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Continuous Distribution ◽  
Environmental Data ◽  
Easy Access ◽  
Species Occurrence ◽  
Distribution Models ◽  
Occurrence Data ◽  
Data Portal

Recognizing the abundance and the accumulation of information and data on biodiversity that are still poorly exploited and even unfunded, the REBIOMA project (Madagascar Biodiversity Networking), in collaboration with partners, has developed an online dataportal in order to provide easy access to information and critical data, to support conservation planning and the expansion of scientific and professional activities in Madagascar biodiversity. The mission of the REBIOMA data portal is to serve quality-labeled, up-to-date species occurrence data and environmental niche models for Madagascar’s flora and fauna, both marine and terrestrial. REBIOMA is a project of the Wildlife Conservation Society Madagascar and the University of California, Berkeley. REBIOMA serves species occurrence data for marine and terrestrial regions of Madagascar. Following upload, data is automatically validated against a geographic mask and a taxonomic authority. Data providers can decide whether their data will be public, private, or shared only with selected collaborators. Data reviewers can add quality labels to individual records, allowing selection of data for modeling and conservation assessments according to quality. Portal users can query data in numerous ways. One of the key features of the REBIOMA web portal is its support for species distribution models, created from taxonomically valid and quality-reviewed occurrence data. Species distribution models are produced for species for which there are at least eight, reliably reviewed, non-duplicate (per grid cell) records. Maximum Entropy Modeling (MaxEnt for short) is used to produce continuous distribution models from these occurrence records and environmental data for different eras: past (1950), current (2000), and future (2080). The result is generally interpreted as a prediction of habitat suitability. Results for each model are available on the portal and ready for download as ASCII and HTML files. The REBIOMA Data Portal address is http://data.rebioma.net, or visit http://www.rebioma.netfor more general information about the entire REBIOMA project.

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