877 resultados para species distribution model
Resumo:
Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.
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We developed a conceptual ecological model (CEM) for invasive species to help understand the role invasive exotics have in ecosystem ecology and their impacts on restoration activities. Our model, which can be applied to any invasive species, grew from the eco-regional conceptual models developed for Everglades restoration. These models identify ecological drivers, stressors, effects and attributes; we integrated the unique aspects of exotic species invasions and effects into this conceptual hierarchy. We used the model to help identify important aspects of invasion in the development of an invasive exotic plant ecological indicator, which is described a companion paper in this special issue journal. A key aspect of the CEM is that it is a general ecological model that can be tailored to specific cases and species, as the details of any invasion are unique to that invasive species. Our model encompasses the temporal and spatial changes that characterize invasion, identifying the general conditions that allow a species to become invasive in a de novo environment; it then enumerates the possible effects exotic species may have collectively and individually at varying scales and for different ecosystem properties, once a species becomes invasive. The model provides suites of characteristics and processes, as well as hypothesized causal relationships to consider when thinking about the effects or potential effects of an invasive exotic and how restoration efforts will affect these characteristics and processes. In order to illustrate how to use the model as a blueprint for applying a similar approach to other invasive species and ecosystems, we give two examples of using this conceptual model to evaluate the status of two south Florida invasive exotic plant species (melaleuca and Old World climbing fern) and consider potential impacts of these invasive species on restoration.
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Antillean manatees (Trichechus manatus manatus) were heavily hunted in the past throughout the Wider Caribbean Region (WCR), and are currently listed as endangered on the IUCN Red List of Threatened Species. In most WCR countries, including Haiti and the Dominican Republic, remaining manatee populations are believed to be small and declining, but current information is needed on their status, distribution, and local threats to the species.
To assess the past and current distribution and conservation status of the Antillean manatee in Hispaniola, I conducted a systematic review of documentary archives dating from the pre-Columbian era to 2013. I then surveyed more than 670 artisanal fishers from Haiti and the Dominican Republic in 2013-2014 using a standardized questionnaire. Finally, to identify important areas for manatees in the Dominican Republic, I developed a country-wide ensemble model of manatee distribution, and compared modeled hotspots with those identified by fishers.
Manatees were historically abundant in Hispaniola, but were hunted for their meat and became relatively rare by the end of the 19th century. The use of manatee body parts diversified with time to include their oil, skin, and bones. Traditional uses for folk medicine and handcrafts persist today in coastal communities in the Dominican Republic. Most threats to Antillean manatees in Hispaniola are anthropogenic in nature, and most mortality is caused by fisheries. I estimated a minimum island-wide annual mortality of approximately 20 animals. To understand the impact of this level of mortality, and to provide a baseline for measuring the success of future conservation actions, the Dominican Republic and Haiti should work together to obtain a reliable estimate of the current population size of manatees in Hispaniola.
In Haiti, the survey of fishers showed a wider distribution range of the species than suggested by the documentary archive review: fishers reported recent manatee sightings in seven of nine coastal departments, and three manatee hotspot areas were identified in the north, central, and south coasts. Thus, the contracted manatee distribution range suggested by the documentary archive review likely reflects a lack of research in Haiti. Both the review and the interviews agreed that manatees no longer occupy freshwater habitats in the country. In general, more dedicated manatee studies are needed in Haiti, employing aerial, land, or boat surveys.
In the Dominican Republic, the documentary archive review and the survey of fishers showed that manatees still occur throughout the country, and occasionally occupy freshwater habitats. Monte Cristi province in the north coast, and Barahona province in the south coast, were identified as focal areas. Sighting reports of manatees decreased from Monte Cristi eastwards to the adjacent province in the Dominican Republic, and westwards into Haiti. Along the north coast of Haiti, the number of manatee sighting and capture reports decreased with increasing distance to Monte Cristi province. There was good agreement among the modeled manatee hotspots, hotspots identified by fishers, and hotspots identified during previous dedicated manatee studies. The concordance of these results suggests that the distribution and patterns of habitat use of manatees in the Dominican Republic have not changed dramatically in over 30 years, and that the remaining manatees exhibit some degree of site fidelity. The ensemble modeling approach used in the present study produced accurate and detailed maps of manatee distribution with minimum data requirements. This modeling strategy is replicable and readily transferable to other countries in the Caribbean or elsewhere with limited data on a species of interest.
The intrinsic value of manatees was stronger for artisanal fishers in the Dominican Republic than in Haiti, and most Dominican fishers showed a positive attitude towards manatee conservation. The Dominican Republic is an upper middle income country with a high Human Development Index. It possesses a legal framework that specifically protects manatees, and has a greater number of marine protected areas, more dedicated manatee studies, and more manatee education and awareness campaigns than Haiti. The constant presence of manatees in specific coastal segments of the Dominican Republic, the perceived decline in the number of manatee captures, and a more conservation-minded public, offer hope for manatee conservation, as non-consumptive uses of manatees become more popular. I recommend a series of conservation actions in the Dominican Republic, including: reducing risks to manatees from harmful fishing gear and watercraft at confirmed manatee hotspots; providing alternative economic alternatives for displaced fishers, and developing responsible ecotourism ventures for manatee watching; improving law enforcement to reduce fisheries-related manatee deaths, stop the illegal trade in manatee body parts, and better protect manatee habitat; and continuing education and awareness campaigns for coastal communities near manatee hotspots.
In contrast, most fishers in Haiti continue to value manatees as a source of food and income, and showed a generally negative attitude towards manatee conservation. Haiti is a low income country with a low Human Development Index. Only a single dedicated manatee study has been conducted in Haiti, and manatees are not officially protected. Positive initiatives for manatees in Haiti include: protected areas declared in 2013 and 2014 that enclose two of the manatee hotspots identified in the present study; and local organizations that are currently working on coastal and marine environmental issues, including research and education on marine mammals. Future conservation efforts for manatees in Haiti should focus on addressing poverty and providing viable economic alternatives for coastal communities. I recommend a community partnership approach for manatee conservation, paired with education and awareness campaigns to inform coastal communities about the conservation situation of manatees in Haiti, and to help change their perceived value. Haiti should also provide legal protection for manatees and their habitat.
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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.
Resumo:
We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.
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Thesis (Master's)--University of Washington, 2016-08
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Inland sand dune systems are amongst the most threatened habitat types of Europe. Affected by severe conditions, these habitats present distinct community compositions, which makes them excellent for studying possible interactions among their integrating species and the environment. We focus on understanding the distribution and cooccurrence of the species from dune plant assemblages as a key step for the adequate protection of these habitats. Using data from an extensive survey we identified the shrub species that could be considered indicators of the different xerophytic scrub dune communities in South West Portugal. Then, we modelled the responses of these species to the environmental conditions using Ecological Niche Factor Analysis. We present some preliminary results elucidating whether using species distribution models of indicator species at a regional scale is a valid approach to predict the distribution of the different types of communities inhabiting these endangered habitats.
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In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.
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Organisations at the centre of the state’s industry, such as Screen Queensland, have undergone substantial and ongoing changes in the last five years. Other organisations funded by Screen Queensland, such as QPIX, Queensland’s only film development centre, have recently closed. The Brisbane International Film Festival has been restructured to become the Brisbane Asia Pacific Film Festival as of 2014. In an uncertain industry currently characterised by limited funding and diminishing support structures, local emerging filmmakers require significant initiatives and a sophisticated understanding of how to best utilise fledgling distribution models as part of a tailored strategy for their content. This essay includes interviews with emerging Brisbane filmmakers who have used a combination of traditional and contemporary approaches to exhibition and distribution thus far in their careers. It argues that for these filmmakers, while film festivals do function as crucial platforms for exposure, in the current digital market they cannot be relied upon as the only platform in securing further mainstream or commercial release. They can, however, be incorporated into an alternative distribution model that shows awareness of the contemporary situation in Australia. The research findings are arguably indicative of the challenges faced by filmmakers statewide, and suggest that further support strategies need to be considered to revive Queensland’s film culture and provide immediate support for emerging filmmakers. Queensland’s film sector is currently in the midst of significant change.
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Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.
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Strategic searching for invasive pests presents a formidable challenge for conservation managers. Limited funding can necessitate choosing between surveying many sites cursorily, or focussing intensively on fewer sites. While existing knowledge may help to target more likely sites, e.g. with species distribution models (maps), this knowledge is not flawless and improving it also requires management investment. 2.In a rare example of trading-off action against knowledge gain, we combine search coverage and accuracy, and its future improvement, within a single optimisation framework. More specifically we examine under which circumstances managers should adopt one of two search-and-control strategies (cursory or focussed), and when they should divert funding to improving knowledge, making better predictive maps that benefit future searches. 3.We use a family of Receiver Operating Characteristic curves to reflect the quality of maps that direct search efforts. We demonstrate our framework by linking these to a logistic model of invasive spread such as that for the red imported fire ant Solenopsis invicta in south-east Queensland, Australia. 4.Cursory widespread searching is only optimal if the pest is already widespread or knowledge is poor, otherwise focussed searching exploiting the map is preferable. For longer management timeframes, eradication is more likely if funds are initially devoted to improving knowledge, even if this results in a short-term explosion of the pest population. 5.Synthesis and applications. By combining trade-offs between knowledge acquisition and utilization, managers can better focus - and justify - their spending to achieve optimal results in invasive control efforts. This framework can improve the efficiency of any ecological management that relies on predicting occurrence. © 2010 The Authors. Journal of Applied Ecology © 2010 British Ecological Society.
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Aim Determining how ecological processes vary across space is a major focus in ecology. Current methods that investigate such effects remain constrained by important limiting assumptions. Here we provide an extension to geographically weighted regression in which local regression and spatial weighting are used in combination. This method can be used to investigate non-stationarity and spatial-scale effects using any regression technique that can accommodate uneven weighting of observations, including machine learning. Innovation We extend the use of spatial weights to generalized linear models and boosted regression trees by using simulated data for which the results are known, and compare these local approaches with existing alternatives such as geographically weighted regression (GWR). The spatial weighting procedure (1) explained up to 80% deviance in simulated species richness, (2) optimized the normal distribution of model residuals when applied to generalized linear models versus GWR, and (3) detected nonlinear relationships and interactions between response variables and their predictors when applied to boosted regression trees. Predictor ranking changed with spatial scale, highlighting the scales at which different species–environment relationships need to be considered. Main conclusions GWR is useful for investigating spatially varying species–environment relationships. However, the use of local weights implemented in alternative modelling techniques can help detect nonlinear relationships and high-order interactions that were previously unassessed. Therefore, this method not only informs us how location and scale influence our perception of patterns and processes, it also offers a way to deal with different ecological interpretations that can emerge as different areas of spatial influence are considered during model fitting.
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Twenty new Australian species of the scarabaeine genus Onthophagus Latreille are described: O. arkoola, O. beelarong, O. bindaree, O. binyana, O. bundara, O. cooloola, O. dinjerra, O. godarra, O. gurburra, O. kakadu, O. mije, O. mongana, O. pinaroo, O. trawalla, O. weringerong, O. williamsi, O. worooa, O. yackatoon, O. yaran, O. yourula. Notes and scanning electron micrographs are given to assist in the separation of each from previously described Australian species. Distribution maps are provided for each species
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Scarab species associated with groundnuts were surveyed in Andhra Pradesh, Karnataka and Tamil Nadu, southern India, between 1995 and 2001. Scarab adults were collected from trees on which they were feeding and/or mating, and larvae (white grubs) from groundnut fields. Holotrichia species, especially H. reynaudi and H. serrata were the major species associated with groundnut. H. reynaudi predominated in the central Deccan area, while H. serrata was most abundant in areas to the south and west. A new, undescribed, Holotrichia species near H. consanguinea was collected south and south-west of Hyderabad in mixed populations with H. reynaudi. However, the full extent of this new species’ distribution remains uncertain. H. rufoflava was rarely associated with groundnut, but was common as an adult at some locations. Other genera encountered during surveys were Anomala, Adoretus, Schizonycha, Autoserica. In survey data, densities of Holotrichia larvae and ‘all other white grubs’ were both very highly correlated with % of damaged groundnut plants. These correlations in combination with concurrent observations of plant damage establish a causal link between white grubs and plant damage and death in southern Indian groundnut. Ranking of preferred host trees for adults were developed from field observations for four Holotrichia species and Schizonycha spp. and will assist grower-initiated surveys of pest occurrence. In combination with insecticide efficacy data published elsewhere, the survey provides the basis for an environmentally friendly and economically viable pest-management system for white grubs on groundnut in southern India.
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Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.