1,350 research outputs found
Stepwise basis set selection
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146410/1/jcc25363.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146410/2/jcc25363_am.pd
Using Ecological Modelling Tools to Inform Policy Makers of Potential Changes in Crop Distribution: An Example with Cacao Crops in Latin America
International audienceSpecies distribution models (SDM) is a powerful simulation tool that has become widely used in the ecological and agronomical sciences. The use of easily available presence data, global downscaled climate layers and software that can run on desktop computer has contributed to their popularity. The most used application is based on maximum entropy models that fit presence data to a series of environmental descriptors. SDM can be used to predict crop distribution under future conditions but the level of uncertainty of those models can be very high. The best use of these models is to be used as generators of hypothesis to be combined with other type of analysis
Modelling fish habitat preference with a genetic algorithm-optimized Takagi-Sugeno model based on pairwise comparisons
Species-environment relationships are used for evaluating the current status of target species and the potential impact of natural or anthropogenic changes of their habitat. Recent researches reported that the results are strongly affected by the quality of a data set used. The present study attempted to apply pairwise comparisons to modelling fish habitat preference with Takagi-Sugeno-type fuzzy habitat preference models (FHPMs) optimized by a genetic algorithm (GA). The model was compared with the result obtained from the FHPM optimized based on mean squared error (MSE). Three independent data sets were used for training and testing of these models. The FHPMs based on pairwise comparison produced variable habitat preference curves from 20 different initial conditions in the GA. This could be partially ascribed to the optimization process and the regulations assigned. This case study demonstrates applicability and limitations of pairwise comparison-based optimization in an FHPM. Future research should focus on a more flexible learning process to make a good use of the advantages of pairwise comparisons
Mapping and modelling the geographical distribution and environmental limits of podoconiosis in Ethiopia
BACKGROUND
Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues.
METHODOLOGY
Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008-2010. The integrated mapping used woreda (district) health offices' reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT) modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence.
PRINCIPAL FINDINGS
Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2-51.7) million people (i.e. 43.8%; 95% CI: 25.3-64.8% of Ethiopia's national population) lived in areas environmentally suitable for the occurrence of podoconiosis.
CONCLUSIONS
Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide programme planning and implementation and estimate disease burden in Ethiopia. This work provides a framework with which the geographical limits of podoconiosis could be delineated at a continental scale
Current and potential geographical distribution of Platymeris biguttatus (Linnaeus, 1767) with description of nymphs
Background: The description of Platymeris biguttatus (Linnaeus 1767) nymphal instars as well as the prediction of
the potentially suitable ecological niche was the main goal of this study. Our research was based on 258 specimens
of P. biguttatus species of museum collections. A set of 23 environmental predictor variables covering Africa was
used at ecological niche modeling - a method performed using the Maxent software to prepare potential distribution
maps for this species.
Results: The results suggested the most suitable areas seen as potentially suitable ecological niche for P. biguttatus in
Africa. A jackknife test showed that temperature seasonality and percentage of tree cover were among the most
important environmental variables affecting the distribution of the species. The analysis of climate preferences shows
that most of the potentially suitable niches for this species were located in the area of tropical savanna climate, with a
small participation of tree vegetation.
Conclusions: P. biguttatus was only known to be widely distributed in the tropical part of continental Africa. Thanks to
the ecological niche modeling methods and the museum data on the occurrence of the species, we introduced new
information about potentially suitable ecological niches and the possible range of distribution
Using geographically weighted regression to explore the spatially heterogeneous spread of bovine tuberculosis in England and Wales
An understanding of the factors that affect the spread of endemic bovine tuberculosis (bTB) is critical for the development of measures to stop and reverse this spread. Analyses of spatial data need to account for the inherent spatial heterogeneity within the data, or else spatial autocorrelation can lead to an overestimate of the significance of variables. This study used three methods of analysis—least-squares linear regression with a spatial autocorrelation term, geographically weighted regression (GWR) and boosted regression tree (BRT) analysis—to identify the factors that influence the spread of endemic bTB at a local level in England and Wales. The linear regression and GWR methods demonstrated the importance of accounting for spatial differences in risk factors for bTB, and showed some consistency in the identification of certain factors related to flooding, disease history and the presence of multiple genotypes of bTB. This is the first attempt to explore the factors associated with the spread of endemic bTB in England and Wales using GWR. This technique improves on least-squares linear regression approaches by identifying regional differences in the factors associated with bTB spread. However, interpretation of these complex regional differences is difficult and the approach does not lend itself to predictive models which are likely to be of more value to policy makers. Methods such as BRT may be more suited to such a task. Here we have demonstrated that GWR and BRT can produce comparable outputs
Predicting the Impact of Climate Change on Threatened Species in UK Waters
Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina)
Both habitat change and local lek structure influence patterns of spatial loss and recovery in a black grouse population
The final publication is available at Springer via http://dx.doi.org/10.1007/s10144-015-0484-3Land use change is a major driver of declines in wildlife populations. Where human economic or recreational interests and wildlife share landscapes this problem is exacerbated. Changes in UK black grouse Tetrao tetrix populations are thought to have been strongly influenced by upland land use change. In a long-studied population within Perthshire, lek persistence is positively correlated with lek size, and remaining leks clustered most strongly within the landscape when the population is lowest, suggesting that there may be a demographic and/or spatial context to the reaction of the population to habitat changes. Hierarchical cluster analysis of lek locations revealed that patterns of lek occupancy when the population was declining were different to those during the later recovery period. Response curves from lek-habitat models developed using MaxEnt for periods with a declining population, low population, and recovering population were consistent across years for most habitat measures. We found evidence linking lek persistence with habitat quality changes and more leks which appeared between 1994 and 2008 were in improving habitat than those which disappeared during the same period. Generalised additive models (GAMs) identified changes in woodland and starting lek size as being important indicators of lek survival between declining and low/recovery periods. There may also have been a role for local densities in explaining recovery since the population low point. Persistence of black grouse leks was influenced by habitat, but changes in this alone did not fully account for black grouse declines. Even when surrounded by good quality habitat, leks can be susceptible to extirpation due to isolation
Claims of Potential Expansion throughout the U.S. by Invasive Python Species Are Contradicted by Ecological Niche Models
BACKGROUND: Recent reports from the United States Geological Survey (USGS) suggested that invasive Burmese pythons in the Everglades may quickly spread into many parts of the U.S. due to putative climatic suitability. Additionally, projected trends of global warming were predicted to significantly increase suitable habitat and promote range expansion by these snakes. However, the ecological limitations of the Burmese python are not known and the possible effects of global warming on the potential expansion of the species are also unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that a predicted continental expansion is unlikely based on the ecology of the organism and the climate of the U.S. Our ecological niche models, which include variables representing climatic extremes as well as averages, indicate that the only suitable habitat in the U.S. for Burmese pythons presently occurs in southern Florida and in extreme southern Texas. Models based on the current distribution of the snake predict suitable habitat in essentially the only region in which the snakes are found in the U.S. Future climate models based on global warming forecasts actually indicate a significant contraction in suitable habitat for Burmese pythons in the U.S. as well as in their native range. CONCLUSIONS/SIGNIFICANCE: The Burmese python is strongly limited to the small area of suitable environmental conditions in the United States it currently inhabits due to the ecological niche preferences of the snake. The ability of the Burmese python to expand further into the U.S. is severely limited by ecological constraints. Global warming is predicted to significantly reduce the area of suitable habitat worldwide, underscoring the potential negative effects of climate change for many species
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