Incorporating classified dispersal assumptions in predictive distribution models – A case study with grasshoppers and bush-crickets

2011 ◽  
Vol 222 (13) ◽  
pp. 2130-2141 ◽  
Author(s):  
Jörn Buse ◽  
Eva Maria Griebeler
Keyword(s):  
Predictive Distribution ◽  
Distribution Models ◽  
Bush Crickets

Predictive distribution models of European hake in the south-central Mediterranean Sea

Hydrobiologia ◽  
2017 ◽  
Vol 821 (1) ◽  
pp. 153-172 ◽  
Author(s):  
G. Garofalo ◽  
S. Fezzani ◽  
F. Gargano ◽  
G. Milisenda ◽  
O. Ben Abdallah ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Predictive Distribution ◽  
The South ◽  
Distribution Models ◽  
Central Mediterranean ◽  
South Central ◽  
Central Mediterranean Sea ◽  
European Hake

scholarly journals Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

2020 ◽  
Vol 12 (3) ◽  
pp. 562 ◽  
Author(s):  
Francesco Valerio ◽  
Eduardo Ferreira ◽  
Sérgio Godinho ◽  
Ricardo Pita ◽  
António Mira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Landscape Heterogeneity ◽  
Remote Sensing Data ◽  
Predictive Distribution ◽  
Distribution Models ◽  
Explanatory Variables ◽  
Habitat Features ◽  
Main Challenge ◽  
Cabrera Vole ◽  
Sentinel 2

Accurate mapping is a main challenge for endangered small-sized terrestrial species. Freely available spatio-temporal data at high resolution from multispectral satellite offer excellent opportunities for improving predictive distribution models of such species based on fine-scale habitat features, thus making it easier to achieve comprehensive biodiversity conservation goals. However, there are still few examples showing the utility of remote-sensing-based products in mapping microhabitat suitability for small species of conservation concern. Here, we address this issue using Sentinel-2 sensor-derived habitat variables, used in combination with more commonly used explanatory variables (e.g., topography), to predict the distribution of the endangered Cabrera vole (Microtus cabrerae) in agrosilvopastorial systems. Based on vole surveys conducted in two different seasons over a ~176,000 ha landscape in Southern Portugal, we assessed the significance of each predictor in explaining Cabrera vole occurrence using the Boruta algorithm, a novel Random forest variant for dealing with high dimensionality of explanatory variables. Overall, results showed a strong contribution of Sentinel-2-derived variables for predicting microhabitat suitability of Cabrera voles. In particular, we found that photosynthetic activity (NDI45), specific spectral signal (SWIR1), and landscape heterogeneity (Rao’s Q) were good proxies of Cabrera voles’ microhabitat, mostly during temporally greener and wetter conditions. In addition to remote-sensing-based variables, the presence of road verges was also an important driver of voles’ distribution, highlighting their potential role as refuges and/or corridors. Overall, our study supports the use of remote-sensing data to predict microhabitat suitability for endangered small-sized species in marginal areas that potentially hold most of the biodiversity found in human-dominated landscapes. We believe our approach can be widely applied to other species, for which detailed habitat mapping over large spatial extents is difficult to obtain using traditional descriptors. This would certainly contribute to improving conservation planning, thereby contributing to global conservation efforts in landscapes that are managed for multiple purposes.

scholarly journals Combining Deforestation and Species Distribution Models to Improve Measures of Chimpanzee Conservation Impacts of REDD: A Case Study from Ntakata Mountains, Western Tanzania

Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1195
Author(s):  
Rebecca Dickson ◽  
Marc Baker ◽  
Noémie Bonnin ◽  
David Shoch ◽  
Benjamin Rifkin ◽  
...  
Keyword(s):  
Biodiversity Conservation ◽  
Species Distribution ◽  
Carbon Emissions ◽  
Species Distribution Models ◽  
Cost Effective ◽  
Climate Mitigation ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Western Tanzania

Projects to reduce emissions from deforestation and degradation (REDD) are designed to reduce carbon emissions through avoided deforestation and degradation, and in many cases, to produce additional community and biodiversity conservation co-benefits. While these co-benefits can be significant, quantifying conservation impacts has been challenging, and most projects use simple species presence to demonstrate positive biodiversity impact. Some of the same tools applied in the quantification of climate mitigation benefits have relevance and potential application to estimating co-benefits for biodiversity conservation. In western Tanzania, most chimpanzees live outside of national park boundaries, and thus face threats from human activity, including competition for suitable habitat. Through a case study of the Ntakata Mountains REDD project in western Tanzania, we demonstrate a combined application of deforestation modelling with species distribution models to assess forest conservation benefits in terms of avoided carbon emissions and improved chimpanzee habitat. The application of such tools is a novel approach that we argue permits the better design of future REDD projects for biodiversity co-benefits. This approach also enables project developers to produce the more manageable, accurate and cost-effective monitoring, reporting and verification of project impacts that are critical to verification under carbon standards.

scholarly journals Watching Battlestar Galactica in Australia and the Tyranny of Digital Distance

2008 ◽  
Vol 126 (1) ◽  
pp. 145-154 ◽  
Author(s):  
Tama Leaver
Keyword(s):  
Digital Media ◽  
Communication Technologies ◽  
Rapid Rise ◽  
Speed Of Light ◽  
Distribution Models ◽  
Battlestar Galactica ◽  
Economic Decisions ◽  
Technical Potential ◽  
Media Corporations

In an era where communication technologies can move digital media at close to the speed of light, this paper explores the rupture between this technical potential and the actual model by which international television screening dates are determined in Australia. As the delays between overseas and Australian airdates can be as long two years, and average over six months, the rapid rise in both official and fan-produced online material and interaction relating to television series has given rise to a massive but largely unfulfilled demand for simultaneous access to episodes across the globe. Using the case study of the critically acclaimed fan favourite Battlestar Galactica, this paper outlines some of the strategies by which producers build global fan loyalty — from official websites, blogs, commentary podcasts and online deleted scenes to exclusive webisodes and official participation in fan forums. The paper argues that these trends, combined with the time delay between release dates, are the largest factors contributing to the unlawful downloading of television via peer-to-peer file-sharing platforms such as BitTorrent. In attempting to maintain distribution models that began as geographic necessities, but have become exclusively political and economic decisions in an era of digital communication technologies, this paper argues that media corporations are perpetuating a ‘tyranny of digital distance’ and alienating their own audiences.

scholarly journals Probability Distributions for a Quantile Mapping Technique for a Bias Correction of Precipitation Data: A Case Study to Precipitation Data Under Climate Change

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1475 ◽  
Author(s):  
Jun-Haeng Heo ◽  
Hyunjun Ahn ◽  
Ju-Young Shin ◽  
Thomas Rodding Kjeldsen ◽  
Changsam Jeong
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Shape Parameter ◽  
Mapping Method ◽  
Distribution Model ◽  
Parameter Distribution ◽  
Precipitation Data ◽  
Distribution Models ◽  
Quantile Mapping

The quantile mapping method is a bias correction method that leads to a good performance in terms of precipitation. Selecting an appropriate probability distribution model is essential for the successful implementation of quantile mapping. Probability distribution models with two shape parameters have proved that they are fit for precipitation modeling because of their flexibility. Hence, the application of a two-shape parameter distribution will improve the performance of the quantile mapping method in the bias correction of precipitation data. In this study, the applicability and appropriateness of two-shape parameter distribution models are examined in quantile mapping, for a bias correction of simulated precipitation data from a climate model under a climate change scenario. Additionally, the impacts of distribution selection on the frequency analysis of future extreme precipitation from climate are investigated. Generalized Lindley, Burr XII, and Kappa distributions are used, and their fits and appropriateness are compared to those of conventional distributions in a case study. Applications of two-shape parameter distributions do lead to better performances in reproducing the statistical characteristics of observed precipitation, compared to those of conventional distributions. The Kappa distribution is considered the best distribution model, as it can reproduce reliable spatial dependences of the quantile corresponding to a 100-year return period, unlike the gamma distribution.

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