935 resultados para species distribution model


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Emerging infectious diseases are a growing concern in wildlife conservation. Documenting outbreak patterns and determining the ecological drivers of transmission risk are fundamental to predicting disease spread and assessing potential impacts on population viability. However, evaluating disease in wildlife populations requires expansive surveillance networks that often do not exist in remote and developing areas. Here, we describe the results of a community-based research initiative conducted in collaboration with indigenous harvesters, the Inuit, in response to a new series of Avian Cholera outbreaks affecting Common Eiders (Somateria mollissima) and other comingling species in the Canadian Arctic. Avian Cholera is a virulent disease of birds caused by the bacterium Pasteurella multocida. Common Eiders are a valuable subsistence resource for Inuit, who hunt the birds for meat and visit breeding colonies during the summer to collect eggs and feather down for use in clothing and blankets. We compiled the observations of harvesters about the growing epidemic and with their assistance undertook field investigation of 131 colonies distributed over >1200 km of coastline in the affected region. Thirteen locations were identified where Avian Cholera outbreaks have occurred since 2004. Mortality rates ranged from 1% to 43% of the local breeding population at these locations. Using a species-habitat model (Maxent), we determined that the distribution of outbreak events has not been random within the study area and that colony size, vegetation cover, and a measure of host crowding in shared wetlands were significantly correlated to outbreak risk. In addition, outbreak locations have been spatially structured with respect to hypothesized introduction foci and clustered along the migration corridor linking Arctic breeding areas with wintering areas in Atlantic Canada. At present, Avian Cholera remains a localized threat to Common Eider populations in the Arctic; however expanded, community-based surveillance will be required to track disease spread.

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The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

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fuzzySim is an R package for calculating fuzzy similarity in species occurrence patterns. It includes functions for data preparation, such as converting species lists (long format) to presence-absence tables (wide format), obtaining unique abbreviations of species names, or transposing (parts of) complex data frames; and sample data sets for providing practical examples. It can convert binary presence-absence to fuzzy occurrence data, using e.g. trend surface analysis, inverse distance interpolation or prevalence-independent environmental favourability modelling, for multiple species simultaneously. It then calculates fuzzy similarity among (fuzzy) species distributions and/or among (fuzzy) regional species compositions. Currently available similarity indices are Jaccard, Sørensen, Simpson, and Baroni-Urbani & Buser.

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Despite covering only approximately 138,000 km2, mangroves are globally important carbon sinks with carbon density values 3 to 4 times that of terrestrial forests. A key challenge in evaluating the carbon benefits from mangrove forest conservation is the lack of rigorous spatially resolved estimates of mangrove sediment carbon stocks; most mangrove carbon is stored belowground. Previous work has focused on detailed estimations of carbon stores over relatively small areas, which has obvious limitations in terms of generality and scope of application. Most studies have focused only on quantifying the top 1m of belowground carbon (BGC). Carbon stored at depths beyond 1m, and the effects of mangrove species, location and environmental context on these stores, is poorly studied. This study investigated these variables at two sites (Gazi and Vanga in the south of Kenya) and used the data to produce a country-specific BGC predictive model for Kenya and map BGC store estimates throughout Kenya at spatial scales relevant for climate change research, forest management and REDD+ (Reduced Emissions from Deforestation and Degradation). The results revealed that mangrove species was the most reliable predictor of BGC; Rhizophora muronata had the highest mean BGC with 1485.5t C ha-1. Applying the species-based predictive model to a base map of species distribution in Kenya for the year 2010 with a 2.5m2 resolution, produced an estimate of 69.41 Mt C (± 9.15 95% C.I.) for BGC in Kenyan mangroves. When applied to a 1992 mangrove distribution map, the BGC estimate was 75.65 Mt C (± 12.21 95% C.I.); an 8.3% loss in BGC stores between 1992 and 2010 in Kenya. The country level mangrove map provides a valuable tool for assessing carbon stocks and visualising the distribution of BGC. Estimates at the 2.5m2 resolution provide sufficient detail for highlighting and prioritising areas for mangrove conservation and restoration.

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Tese de Doutoramento, Ciências do Ambiente (Ecologia), 30 de Julho de 2013, Universidade dos Açores.

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A Lontra Euroasiática foi alvo de quatro prospeções na Península Ibérica (1990-2008). Em 2003, foi publicado um modelo de distribuição da lontra, com base nos dados de presença/ausência das prospeções publicadas em 1998. Dadas as suas características, este tipo de modelos pode tornar-se um elemento chave nas estratégias de recuperação da lontra como também, de outras espécies, se comprovada a sua fiabilidade e capacidade de antecipar tendências na distribuição das mesmas. Assim, esta dissertação confrontou as previsões do modelo com os dados de distribuição de 2008, a fim de identificar potências áreas de discordância. Os resultados revelam que, o modelo de distribuição de lontra proposto, apesar de ter por base dados de 1998 e de não considerar explicitamente processos biológicos, conseguiu captar o essencial da relação espécie-ambiente, resultando num bom desempenho preditivo para a distribuição da mesma em Espanha, uma década depois da sua construção; Evolution of otter (Lutra lutra L.) distribution in the Iberian Peninsula: Models at different scales and their projection through space and time Abstract: The Eurasian otter was already surveyed four times in the Iberian Peninsula (1990-2008). In 2003, a distribution model for the otter based on presence/absence data from the survey published in 1998, was published. This type of models has advantages that can make it in a key element for otter conservation strategies and also, for other species, but only, if their reliability and capability to predict species distribution tendencies are validated. The present thesis compares the model predictions with 2008 data, in order to find potential mismatch areas. Results suggest that, although the distribution model for the otter was based on data from 1998 and, doesn’t include explicitly biological mechanisms, it managed to correctly identify the essence of the species-environment relationship, what was translated in a good predictive performance for its actual distribution in Spain, after a decade of its construction.

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Forest trees, like oaks, rely on high levels of genetic variation to adapt to varying environmental conditions. Thus, genetic variation and its distribution are important for the long-term survival and adaptability of oak populations. Climate change is projected to lead to increased drought and fire events as well as a northward migration of tree species, including oaks. Additionally, decline in oak regeneration has become increasingly concerning since it may lead to decreased gene flow and increased inbreeding levels. This will in turn lead to lowered levels of genetic diversity, negatively affecting the growth and survival of populations. At the same time, populations at the speciesdistribution edge, like those in this study, could possess important stores of genetic diversity and adaptive potential, while also being vulnerable to climatic or anthropogenic changes. A survey of the level and distribution of genetic variation and identification of potentially adaptive genes is needed since adaptive genetic variation is essential for their long-term survival. Oaks possess a remarkable characteristic in that they maintain their species identity and specific environmental adaptations despite their propensity to hybridize. Thus, in the face of interspecific gene flow, some areas of the genome remain differentiated due to selection. This characteristic allows the study of local environmental adaptation through genetic variation analyses. Furthermore, using genic markers with known putative functions makes it possible to link those differentiated markers to potential adaptive traits (e.g., flowering time, drought stress tolerance). Demographic processes like gene flow and genetic drift also play an important role in how genes (including adaptive genes) are maintained or spread. These processes are influenced by disturbances, both natural and anthropogenic. An examination of how genetic variation is geographically distributed can display how these genetic processes and geographical disturbances influence genetic variation patterns. For example, the spatial clustering of closely related trees could promote inbreeding with associated negative effects (inbreeding depression), if gene flow is limited. In turn this can have negative consequences for a species’ ability to adapt to changing environmental conditions. In contrast, interspecific hybridization may also allow the transfer of genes between species that increase their adaptive potential in a changing environment. I have studied the ecologically divergent, interfertile red oaks, Quercus rubra and Q. ellipsoidalis, to identify genes with potential roles in adaptation to abiotic stress through traits such as drought tolerance and flowering time, and to assess the level and distribution of genetic variation. I found evidence for moderate gene flow between the two species and low interspecific genetic differences at most genetic markers (Lind and Gailing 2013). However, the screening of genic markers with potential roles in phenology and drought tolerance led to the identification of a CONSTANS-like (COL) gene, a candidate gene for flowering time and growth. This marker, located in the coding region of the gene, was highly differentiated between the two species in multiple geographical areas, despite interspecific gene flow, and may play a role in reproductive isolation and adaptive divergence between the two species (Lind-Riehl et al. 2014). Since climate change could result in a northward migration of trees species like oaks, this gene could be important in maintaining species identity despite increased contact zones between species (e.g., increased gene flow). Finally I examined differences in spatial genetic structure (SGS) and genetic variation between species and populations subjected to different management strategies and natural disturbances. Diverse management activities combined with various natural disturbances as well as species specific life history traits influenced SGS patterns and inbreeding levels (Lind-Riehl and Gailing submitted).

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Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of speciesdistribution data can affect the relationships that are found.

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Although on a local scale Iberian lynx distribution is determined by the availability of prey rabbits, recent modelling analyses have uncovered broad-scale disagreements between these two speciesdistribution trends. These analyses showed also that the lynx had become restricted to only a fraction of the rabbit’s genetic diversity, and that this could be jeopardising its survival in the face of environmental hazards and uncertainty. In the present paper, a follow-up was carried out through the building of lynx and rabbit distribution models based on the most recent Spanish mammal atlas. Environmental favourability values for lynx and rabbit were positively correlated within the lynx’s current distribution area, but they were negatively correlated within the total Spanish area where lynx used to occur in the 1980’s. Environmental favourability for rabbits was significantly higher where lynx maintains reproductive populations than where it recently disappeared, indicating that rabbit favourability plays an important role and can be a good predictor of lynx persistence. The lynx and rabbit models were extrapolated to predict favourable areas for both species in Spain as well as in Portugal, on the original scale of the distribution data (10x10 km) and on a 100 times finer spatial resolution (1x1 km). The lynx and rabbit models were also combined through fuzzy logic to forecast the potential for lynx occurrence incorporating information on favourable areas for its main prey. Several areas are proposed as favourable for lynx expansion or re-introduction,

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Transferring distribution models between different geographical areas may be problematic, as the performance of models outside their original scope is hard to predict. A modelling procedure is needed that gets the gist of the environmental descriptors of a distribution area, without either overfitting to the training data or overestimating the speciesdistribution potential.We tested the transferability power of the favourability function, a generalized linear model, on the distribution of the Iberian desman (Galemys pyrenaicus) in the Iberian territories of Portugal and Spain.We also tested the effects of two of the main potential constraints on model transferability: the analysed ranges of the predictor variables, and the completeness of the species distribution data. We modelled 10 km×10km presence/absence data from Portugal and Spain separately, extrapolated each model to the other country, and compared predictions with observations. The Spanish model, despite arguably containing more false absences, showed good predictive ability in Portugal. The Portuguese model, whose predictors ranged between only a subset of the values observed in Spain, overestimated desman distribution when transferred.We discuss possible reasons for this differential model behaviour, and highlight the importance of this kind of models for prediction and conservation applications

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The taxonomy of the genus Heliotropium L. in Brazil was studied, revealing nine species and two varieties: H. amplexicaule Vahl, H. angiospermum Murray, H. curassavicum L., H. curassavicum var. argentinum I.M. Johnst., H. elongatum (Lehm.) I.M. Johnst., H. elongatum var. burchellii I.M. Johnst., H. indicum L., H. leiocarpum Morong, H. nicotianaefolium Poir., H. phylicoides Cham. and H. transalpinum Vell. Descriptions, illustrations, comments on relationships based on morphology and data on species distribution are presented.

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Em Pedregulho, município do extremo nordeste do Estado de São Paulo, ocorrem fragmentos de cerrado considerados floristicamente distintos dos demais remanescentes paulistas. Nesse estudo, foi realizado um levantamento florístico em Pedregulho, abordando duas regiões geologicamente distintas: o Parque Estadual das Furnas do Bom Jesus e o distrito de Estreito. Em cada uma, delimitaram-se duas parcelas de 50×50 m, totalizando um hectare, onde foram encontradas 65 famílias e 379 espécies de angiospermas. Coletas em áreas adjacentes totalizaram 71 famílias e 443 espécies. As duas regiões estudadas têm baixa similaridade florística entre si. A distribuição geográfica das espécies é analisada e oito padrões são delimitados para aquelas cuja distribuição no Estado de São Paulo é restrita à região de Pedregulho.

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Background: Freshwaters are the most threatened ecosystems on earth. Although recent assessments provide data on global priority regions for freshwater conservation, local scale priorities remain unknown. Refining the scale of global biodiversity assessments (both at terrestrial and freshwater realms) and translating these into conservation priorities on the ground remains a major challenge to biodiversity science, and depends directly on species occurrence data of high taxonomic and geographic resolution. Brazil harbors the richest freshwater ichthyofauna in the world, but knowledge on endemic areas and conservation in Brazilian rivers is still scarce. Methodology/Principal Findings: Using data on environmental threats and revised species distribution data we detect and delineate 540 small watershed areas harboring 819 restricted-range fishes in Brazil. Many of these areas are already highly threatened, as 159 (29%) watersheds have lost more than 70% of their original vegetation cover, and only 141 (26%) show significant overlap with formally protected areas or indigenous lands. We detected 220 (40%) critical watersheds overlapping hydroelectric dams or showing both poor formal protection and widespread habitat loss; these sites harbor 344 endemic fish species that may face extinction if no conservation action is in place in the near future. Conclusions/Significance: We provide the first analysis of site-scale conservation priorities in the richest freshwater ecosystems of the globe. Our results corroborate the hypothesis that freshwater biodiversity has been neglected in former conservation assessments. The study provides a simple and straightforward method for detecting freshwater priority areas based on endemism and threat, and represents a starting point for integrating freshwater and terrestrial conservation in representative and biogeographically consistent site-scale conservation strategies, that may be scaled-up following naturally linked drainage systems. Proper management (e. g. forestry code enforcement, landscape planning) and conservation (e. g. formal protection) of the 540 watersheds detected herein will be decisive in avoiding species extinction in the richest aquatic ecosystems on the planet.

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(Notes on Acaulospora bireticulata Rothwell & Trappe and first record of Acaulospora koskei Blask. from Brazil). Our knowledge of species distribution in arbuscular mycorrhizal fungi (AMF) is still limited and morphological variations found in isolates of one species may provide additional insight for understanding the characters used in the taxonomy of this group. The aims of this work were to expand biogeographical data regarding Acaulospora koskei Blaszk. and Acaulospora bireticulata Rothwell & Trappe, both found in an Araucaria Forest in Sao Paulo state, Brazil, as well as to compare the descriptions of these species with those of other similar AMF.

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The development of biomonitoring programs based on the macroinvertebrate community requires the understanding of species distribution patterns, as well as of the responses of the community to anthropogenic stressors. In this study, 49 metrics were tested as potential means of assessing the condition of 29 first- and second-order streams located in areas of differing types of land use in So Paulo State, Brazil. Of the sampled streams, 15 were in well-preserved regions in the Atlantic Forest, 5 were among sugarcane cultivations, 5 were in areas of pasture, and 4 were among eucalyptus plantations. The metrics were assessed against the following criteria: (1) predictable response to the impact of human activity; (2) highest taxonomic resolution, and (3) operational and theoretical simplicity. We found that 18 metrics were correlated with the environmental and spatial predictors used, and seven of these satisfied the selection criteria and are thus candidates for inclusion in a multimetric system to assess low-order streams in So Paulo State. These metrics are family richness; Ephemeroptera, Plecoptera and Trichoptera (EPT) richness; proportion of Megaloptera and Hirudinea; proportion of EPT; Shannon diversity index for genus; and adapted Biological Monitoring Work Party biotic index.