892 resultados para Plant population density


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In many countries, high densities of domestic cats (Felis catus) are found in urban habitats where they have the potential to exert considerable predation pressure on their prey. However, little is known of the ranging behaviour of cats in the UK. Twenty cats in suburban Reading, UK, were fitted with GPS trackers to quantify movement patterns. Cats were monitored during the summer and winter for an average of 6.8 24 h periods per season. Mean daily area ranged (95 % MCP) was 1.94 ha. Including all fixes, mean maximum area ranged was 6.88 ha. These are broadly comparable to those observed in urban areas in other countries. Daily area ranged was not affected by the cat’s sex or the season, but was significantly larger at night than during the day. There was no relationship between area ranged and habitat availability. Taking available habitat into account, cat ranging area contained significantly more garden and other green space than urban habitats. If cats were shown to be negatively affecting prey populations, one mitigation option for consideration in housing developments proposed near important wildlife sites would be to incorporate a ‘buffer zone’ in which cat ownership was not permitted. Absolute maximum daily area ranged by a cat in this study was 33.78 ha. This would correspond to an exclusory limit of approximately 300–400 m to minimise the negative effects of cat predation, but this may need to be larger if cat ranging behaviour is negatively affected by population density

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This paper reports the results of a 2-year study of water quality in the River Enborne, a rural river in lowland England. Concentrations of nitrogen and phosphorus species and other chemical determinands were monitored both at high-frequency (hourly), using automated in situ instrumentation, and by manual weekly sampling and laboratory analysis. The catchment land use is largely agricultural, with a population density of 123 persons km−2. The river water is largely derived from calcareous groundwater, and there are high nitrogen and phosphorus concentrations. Agricultural fertiliser is the dominant source of annual loads of both nitrogen and phosphorus. However, the data show that sewage effluent discharges have a disproportionate effect on the river nitrogen and phosphorus dynamics. At least 38% of the catchment population use septic tank systems, but the effects are hard to quantify as only 6% are officially registered, and the characteristics of the others are unknown. Only 4% of the phosphorus input and 9% of the nitrogen input is exported from the catchment by the river, highlighting the importance of catchment process understanding in predicting nutrient concentrations. High-frequency monitoring will be a key to developing this vital process understanding.

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Global controls on month-by-month fractional burnt area (2000–2005) were investigated by fitting a generalised linear model (GLM) to Global Fire Emissions Database (GFED) data, with 11 predictor variables representing vegetation, climate, land use and potential ignition sources. Burnt area is shown to increase with annual net primary production (NPP), number of dry days, maximum temperature, grazing-land area, grass/shrub cover and diurnal temperature range, and to decrease with soil moisture, cropland area and population density. Lightning showed an apparent (weak) negative influence, but this disappeared when pure seasonal-cycle effects were taken into account. The model predicts observed geographic and seasonal patterns, as well as the emergent relationships seen when burnt area is plotted against each variable separately. Unimodal relationships with mean annual temperature and precipitation, population density and gross domestic product (GDP) are reproduced too, and are thus shown to be secondary consequences of correlations between different controls (e.g. high NPP with high precipitation; low NPP with low population density and GDP). These findings have major implications for the design of global fire models, as several assumptions in current models – most notably, the widely assumed dependence of fire frequency on ignition rates – are evidently incorrect.

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1. Comparative analyses are used to address the key question of what makes a species more prone to extinction by exploring the links between vulnerability and intrinsic species’ traits and/or extrinsic factors. This approach requires comprehensive species data but information is rarely available for all species of interest. As a result comparative analyses often rely on subsets of relatively few species that are assumed to be representative samples of the overall studied group. 2. Our study challenges this assumption and quantifies the taxonomic, spatial, and data type biases associated with the quantity of data available for 5415 mammalian species using the freely available life-history database PanTHERIA. 3. Moreover, we explore how existing biases influence results of comparative analyses of extinction risk by using subsets of data that attempt to correct for detected biases. In particular, we focus on links between four species’ traits commonly linked to vulnerability (distribution range area, adult body mass, population density and gestation length) and conduct univariate and multivariate analyses to understand how biases affect model predictions. 4. Our results show important biases in data availability with c.22% of mammals completely lacking data. Missing data, which appear to be not missing at random, occur frequently in all traits (14–99% of cases missing). Data availability is explained by intrinsic traits, with larger mammals occupying bigger range areas being the best studied. Importantly, we find that existing biases affect the results of comparative analyses by overestimating the risk of extinction and changing which traits are identified as important predictors. 5. Our results raise concerns over our ability to draw general conclusions regarding what makes a species more prone to extinction. Missing data represent a prevalent problem in comparative analyses, and unfortunately, because data are not missing at random, conventional approaches to fill data gaps, are not valid or present important challenges. These results show the importance of making appropriate inferences from comparative analyses by focusing on the subset of species for which data are available. Ultimately, addressing the data bias problem requires greater investment in data collection and dissemination, as well as the development of methodological approaches to effectively correct existing biases.

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This study develops a simplified model describing the evolutionary dynamics of a population composed of obligate sexually and asexually reproducing, unicellular organisms. The model assumes that the organisms have diploid genomes consisting of two chromosomes, and that the sexual organisms replicate by first dividing into haploid intermediates, which then combine with other haploids, followed by the normal mitotic division of the resulting diploid into two new daughter cells. We assume that the fitness landscape of the diploids is analogous to the single-fitness-peak approach often used in single-chromosome studies. That is, we assume a master chromosome that becomes defective with just one point mutation. The diploid fitness then depends on whether the genome has zero, one, or two copies of the master chromosome. We also assume that only pairs of haploids with a master chromosome are capable of combining so as to produce sexual diploid cells, and that this process is described by second-order kinetics. We find that, in a range of intermediate values of the replication fidelity, sexually reproducing cells can outcompete asexual ones, provided the initial abundance of sexual cells is above some threshold value. The range of values where sexual reproduction outcompetes asexual reproduction increases with decreasing replication rate and increasing population density. We critically evaluate a common approach, based on a group selection perspective, used to study the competition between populations and show its flaws in addressing the evolution of sex problem.

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This thesis consists of a summary and five self-contained papers addressing dynamics of firms in the Swedish wholesale trade sector. Paper [1] focuses upon determinants of new firm formation in the Swedish wholesale trade sector, using two definitions of firms’ relevant markets, markets defined as administrative areas, and markets based on a cost minimizing behavior of retailers. The paper shows that new entering firms tend to avoid regions with already high concentration of other firms in the same branch of wholesaling, while right-of-the-center local government and quality of the infrastructure have positive impacts upon entry of new firms. The signs of the estimated coefficients remain the same regardless which definition of relevant market is used, while the size of the coefficients is generally higher once relevant markets delineated on the cost-minimizing assumption of retailers are used. Paper [2] analyses determinant of firm relocation, distinguishing between the role of the factors in in-migration municipalities and out-migration municipalities. The results of the analysis indicate that firm-specific factors, such as profits, age and size of the firm are negatively related to the firm’s decision to relocate. Furthermore, firms seems to be avoiding municipalities with already high concentration of firms operating in the same industrial branch of wholesaling and also to be more reluctant to leave municipalities governed by right-of-the- center parties. Lastly, firms seem to avoid moving to municipalities characterized with high population density. Paper [3] addresses determinants of firm growth, adopting OLS and a quantile regression technique. The results of this paper indicate that very little of the firm growth can be explained by the firm-, industry- and region-specific factors, controlled for in the estimated models. Instead, the firm growth seems to be driven by internal characteristics of firms, factors difficult to capture in conventional statistics. This result supports Penrose’s (1959) suggestion that internal resources such as firm culture, brand loyalty, entrepreneurial skills, and so on, are important determinants of firm growth rates. Paper [4] formulates a forecasting model for firm entry into local markets and tests this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms and identification of low- and high-return local markets. The results indicate that 19 of 30 estimated models have more net entry in high-return municipalities, but the estimated parameters is only statistically significant at conventional level in one of our estimated models, and then with unexpected negative sign. Paper [5] studies effects of firm relocation on firm profits of relocating firms, employing a difference-in-difference propensity score matching. Using propensity score matching, the pre-relocalization differences between relocating and non-relocating firms are balanced, while the difference-in-difference estimator controls for all time-invariant unobserved heterogeneity among firms. The results suggest that firms that relocate increase their profits significantly, in comparison to what the profits would be had the firms not relocated. This effect is estimated to vary between 3 to 11 percentage points, depending on the length of the analyzed period. 

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Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

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After declining steadily for several decades, the South China tiger (Panthera tigris amoyensis) is now thought to be extinct in the wild. However, there is some hope of reintroduction, with Hupingshan-Houhe and Mangshan-Nanling National Nature Reserves in southern China seeming to hold the most promise. Our study used slope, elevation, vegetation, and landcover variables to construct a rough habitat suitability index for tigers in these two parks. According to our model, there are areas of suitable habitat within both parks. However, there are some important variables that we were unable to include in our model, such as human population density and prey availability. Considerable in-depth research will be necessary to evaluate the suitability of these locations before reintroduction is considered.

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Currently, there is a public bus transportation route in Waterville, Maine. However, this system could be improved. Our goal was to use GIS to find optimal public transportation routes throughout the city based on given points of interest and high population density areas. Three different groups of points of interest were created in the North, West, and South sections of Waterville. Using the Network Analyst tool, which calculates optimal routes, using existing street data, based on the input of stops, barriers, and impedance, we ran an analysis of what we thought would be the routes that best served the greatest number of people. Two different sets of routes were found: one with length as the impedance (the shortest length between the selected stops was favored), and one with population density as the impedance (the roads with the highest population density were favored). Finally, the times of the resulting routes (given a constant speed limit of 25 mph) were calculated and evaluated.

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The eastern timber wolf (Canis lupus lycaon) once inhabited Maine, as well as the rest of the eastern United States and southern Canada. As a result of human land use and widespread extermination campaigns, wolf numbers dramatically decreased, and by the early twentieth century, no wolves remained in Maine. As large carnivorous and territorial mammals, wolves require contiguous undeveloped areas with abundant prey. This project is a feasibility study that identifies the areas in Maine that are suitable for the reintroduction of wolves. We used GIS modeling to identify contiguous forested areas over 1,000 km2, calculate road and population density, and map the presence or absence of prey throughout the state. These variables were combined in a habitat suitability model to determine the location and amount of suitable wolf habitat in Maine. The northwestern part of the state appears most suitable for wolf reintroduction as it is relatively undeveloped with low road and population densities. There is also a smaller isolated area in Washington County that might be suitable, but further investigation is required.

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Moose (Alces alces) are a keystone herbivore in Maine. Because of the large number of rural roads in Maine, there is a high rate of moose-vehicle collisions (MVCs), which is increasing. On-road encounters with animals resulted in 231 fatalities in the United States in 1999. Because of the fatality of MVCs, it is important to know where they are most likely to occur. I used GIS analysis to estimate where future MVCs would occur, factoring in the variables of land cover suitability for moose, distance from water bodies, locations of past MVCs, and speed limits on the roads. I ran four different analyses, each one weighting the variables equally. I also ran a regression to determine if increasing road speed was associated with the increase in the number of MVCs per length of road. There was not a strong positive relationship between the number of MVCs per length of road and the speed limit, but it was interesting to note that there were more MVCs per length of road on 35mph and 40mph roads than on 45, 50, 55 or 65mph roads. Future research on MVCs would benefit from the inclusion of include moose population density and road traffic data.

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The South China tiger, Panthera tigris amoyensis, once roamed the greater part of southern China. However, expanding human populations and other anthropogenic effects have resulted in the extinction of the wild population. The Chinese government has expressed interest in a reintroduction program for this species of tigers. Recent studies suggest that the Hupingshan preserve is potentially a good candidate for a tiger reintroduction program. Hupingshan is located on the border of the Hunan and Hubei provinces in Southern China. This study was a preliminary habitat suitability analysis, for the restoration of South China tigers in the Hupingshan reserve, China. ArcGIS 9.0 was used to develop a model that combined roads, railroads, slope, land cover, park classification, and population density. The tiger habitat suitability analysis was performed by weighting and combining the various layers. Preliminary results suggest that the Hupingshan reserve is suitable habitat for the reintroduction of South China tigers.

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O trabalho procura dar uma contribuição ao conhecimento varejista no Brasil, integrando aspectos teóricos e empíricos sobre a Área de Influência, conceito de fundamental importância no marketing varejista. A metodologia engloba uma revisão e reordenação do conhecimento teórico existente, e desenvolve uma investigação sobre o fenômeno da Área de Influência com base em pesquisa empírica com clientes de supermercados brasileiros. Através desta análise, chegou-se a conclusão de que as Áreas de Influência de diferentes supermercados, apesar de terem dimensões e comportamentos muito variados, guardam um padrão de distribuição geográfica com características semelhantes. A descoberta de certas generalizações ocorreu quando analisamos o fenômeno da área de influência através de curvas acumuladas de clientes. Verificamos também que o tamanho da loja e a densidade populacional da região onde está localizada parecem ser fatores determinantes da extensão da área de influência.

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Esse trabalho dá continuidade a estudos anteriores e visa contribuir para o avanço da ainda embrionária teoria varejista. Conseguimos desenvolver e operacionalizar os conceitos de área de influência, demanda de mercado e fatia de mercado, e analisar os resultados desses indicadores para os 27 supermercados de São Paulo, que participaram de nossa extensa pesquisa empírica. Um processo de modelagem econométrica foi conduzido, resultando em um modelo de regressão múltipla que satisfatoriamente explica e prevê área de influência como função de três variáveis: tamanho da loja, densidade populacional e disponibilidade de transporte coletivo. Apoiado em rigorosa metodologia de previsão de mercado, o estudo também revela estimativas de mercado que substancialmente diferem dos valores que vem sendo publicados na mídia especializada do setor. Nossa estimativa da demanda de mercado para o setor 'supermercados' no Brasil, em 2002, chega a superar R$ 100 bilhões, enquanto que nossa projeção da concentração das 5 maiores empresas no setor é de apenas 25%.

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O Brasil é um país onde os 50% mais pobres se apropriam aproximadamente de 10% da renda agregada, e os 10% mais ricos detêm quase 50% deste mesmo. O colorário desse alto grau de desigualdade é que se uma pessoa está somente preocupada em maximizar o nível de GPD, a função de bem–estar social implícita adotada devota parte do seu peso ao bem-estar de 10% da população. Em outras palavras, a concentração brasileira de renda cria uma anomalia dentro da perspectiva de agente representativo implícito na análise macroeconômica aonde as pessoas valem aquilo que ganham. A análise da pobreza inverte esse peso estrutural da população, estipulando zero de peso para o segmento não pobre da sociedade e atribuindo pesos aos indivíduos que aumentam com suas necessidades insatisfeitas. Esse projeto estuda as conexões entre a evolução macroeconômica Brasileira recente e da pobreza. A análise é dividida em duas partes: A primeira parte descreve a evolução da pobreza brasileira e seus principais determinantes macroeconômicos durante os últimos 15 anos. A segunda parte tira proveito das mudanças da pobreza e desigualdades medidas durante o período 1993-96 para estudar seus principais determinantes macroeconômicos. Dado a maior importância do Plano Real, uma especial atenção foi dada a análise dos impactos da desinflação no nível e na distribuição de renda e a possível sinergia entre essas duas dimensões de determinação da pobreza. A terceira parte do projeto decompõe as mudanças dos diversos índices de pobreza através dos diferentes grupos dado pelas características dos chefes de família (i.e.; sexo, anos de estudo, raça, classe trabalhadora, setores de atividades, região, densidade populacional). Depois essa decomposição é avançada um passo desatrelando as mudanças nessa diferentes células de pobreza em termos de suas respectivas mudanças em termos de desigualdade da renda per capita. Esse perfil de pobreza ajuda a mapear as diferentes fontes de mudança da pobreza na análise histórica e fornece consistência interna para os exercícios de análises contra-factuais.