Ecological niche modeling and principal component analysis of Krameria Loefl. (Krameriaceae)

Krameria plants are found in arid regions of the Americas and present a floral system that attracts oil-collecting bees. Niche modeling and multivariate tools were applied to examine ecological and geographical aspects of the 18 species of this genus, using occurrence data obtained from herbaria and literature. Niche modeling showed the potential areas of occurrence for each species and the analysis of climatic variables suggested that North American species occur mostly in deserted or xeric ecoregions with monthly precipitation below 140 mm and large temperature ranges. South American species are mainly found in deserted ecoregions and subtropical savannas where monthly precipitation often exceeds 150 mm and temperature ranges are smaller. Principal Component Analysis (PCA) performed with values of temperature and precipitation showed that the distribution limits of Krameria species are primarily associated with maximum and minimum temperatures. Modeling of Krameria species proved to be a useful tool for analyzing the influence of the ecological niche variables in the geographical distribution of species, providing new information to guide future investigations. (C) 2011 Elsevier Ltd. All rights reserved.

Ecological niche similarities of Peponapis bees and non-domesticated Cucurbita species

Peponapis bees are considered specialized pollinators of Cucurbita flowers, a genus that presents several species of economic value (squashes and pumpkins). Both genera originated in the Americas, and their diversity dispersion center is in Mexico. Ten species of Peponapis and ten species of Cucurbita (only non-domesticated species) were analyzed considering the similarity of their ecological niche characteristics with respect to climatic conditions of their occurrence areas (abiotic variables) and interactions between species (biotic variables). The similarity of climatic conditions (temperature and precipitation) was estimated through cluster analyses. The areas of potential occurrence of the most similar species were obtained through ecological niche modeling and summed with geographic information system tools. Three main clusters were obtained: one with species that shared potential occurrence areas mainly in deserts (P. pruinosa, P. timberlakei, C. digitata, C. palmata, C. foetidissima), another in moist forests (P. limitaris, P. atrata, C. lundelliana, C. o. martinezii) and a third mainly in dry forests (C. a. sororia, C. radicans, C. pedatifolia, P. azteca, P. smithi, P. crassidentata, P. utahensis). Some species with similar ecological niche presented potential shared areas that are also similar to their geographical distribution, like those occurring predominantly on deserts. However, some clustered species presented larger geographical areas, such as P. pruinosa and C. foetidissima suggesting other drivers than climatic conditions to shape their distributions. The domestication of Cucurbita and also the natural history of both genera were considered also as important factors. (C) 2011 Elsevier B.V. All rights reserved.

Using ecological niche modelling to infer past, present and future environmental suitability for Leiopelma hochstetteri, an endangered New Zealand native frog

Leiopelma hochstetteri is an endangered New Zealand frog now confined to isolated populations scattered across the North Island. A better understanding of its past, current and predicted future environmental suitability will contribute to its conservation which is in jeopardy due to human activities, feral predators, disease and climate change. Here we use ecological niche modelling with all known occurrence data (N = 1708) and six determinant environmental variables to elucidate current, pre-human and future environmental suitability of this species. Comparison among independent runs, subfossil records and a clamping method allow validation of models. Many areas identified as currently suitable do not host any known populations. This apparent discrepancy could be explained by several non exclusive hypotheses: the areas have not been adequately surveyed and undiscovered populations still remain, the model is over simplistic; the species` sensitivity to fragmentation and small population size; biotic interactions; historical events. An additional outcome is that apparently suitable, but frog-less areas could be targeted for future translocations. Surprisingly, pre-human conditions do not differ markedly highlighting the possibility that the range of the species was broadly fragmented before human arrival. Nevertheless, some populations, particularly on the west of the North Island may have disappeared as a result of human mediated habitat modification. Future conditions are marked with higher temperatures, which are predicted to be favourable to the species. However, such virtual gain in suitable range will probably not benefit the species given the highly fragmented nature of existing habitat and the low dispersal ability of this species. (C) 2010 Elsevier Ltd. All rights reserved.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Estimating abundance and spatial distribution patterns of the bubble crab Dotilla fenestrata (Crustacea : Brachyura)

The bubble crab Dotilla fenestrata forms very dense populations on the sand flats of the eastern coast of Inhaca Island, Mozambique, making it an interesting biological model to examine spatial distribution patterns and test the relative efficiency of common sampling methods. Due to its apparent ecological importance within the sandy intertidal community, understanding the factors ruling the dynamics of Dotilla populations is also a key issue. In this study, different techniques of estimating crab density are described, and the trends of spatial distribution of the different population categories are shown. The studied populations are arranged in discrete patches located at the well-drained crests of nearly parallel mega sand ripples. For a given sample size, there was an obvious gain in precision by using a stratified random sampling technique, considering discrete patches as strata, compared to the simple random design. Density average and variance differed considerably among patches since juveniles and ovigerous females were found clumped, with higher densities at the lower and upper shore levels, respectively. Burrow counting was found to be an adequate method for large-scale sampling, although consistently underestimating actual crab density by nearly half. Regression analyses suggested that crabs smaller than 2.9 mm carapace width tend to be undetected in visual burrow counts. A visual survey of sampling plots over several patches of a large Dotilla population showed that crab density varied in an interesting oscillating pattern, apparently following the topography of the sand flat. Patches extending to the lower shore contained higher densities than those mostly covering the higher shore. Within-patch density variability also pointed to the same trend, but the density increment towards the lowest shore level varied greatly among the patches compared.

Distribution of paracoccidioidomycosis: determination of ecologic correlates through spatial analyses

Paracoccidioidomycosis (PCM) is endemic in Latin America and in countries like Brazil it carries a high mortality rate. The fungus' habitat has not been precisely determined. The present study aims to identify ecologic correlates based on PCM distribution in a hyper-endemic area in southeastern Brazil. The Geographic Information System (GIS) and spatial statistics were used to associate environmental attributes, human population density and, PCM distribution. By means of the Pearson r correlation coefficient, the highest statistically significant associations with prevalence density were the percent area (by county) of: basaltic rocks (r = 0.63; P < 0.0001), Podzolic soils (r = - 0.48; P < 0.001), Latosol soils (r = 0.40; P < 0.01), mean annual precipitation between 1500 and 1600 mm (r = 0.46; P < 0.001) and, mean precipitation during the wet season between 940 and 1040 mm (r = - 0.44; P < 0.01). Soil texture and precipitation analyzed together reached r = 0.61 (P < 0.000002) for fine-textured soils with annual precipitation above 1400 mm. Environmental correlates indicate that moisture availability plays an important role in PCM distribution.

Cryptic sexual populations account for genetic diversity and ecological success in a widely distributed, asexual fungus-growing ant

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Historical biogeography and conservation of the golden-striped salamander (Chioglossa lusitanica) in northwestern Iberia: integrating ecological, phenotypic and phylogeographic data

The golden-striped salamander (Chioglossa lusitanica) is an endemic species inhabiting stream-side habitats in mountainous areas in the northwestern Iberian Peninsula. This salamandrid is listed in the IUCN Red Data Book as a threatened species. The combination of bioclimatic modeling of the species distribution and multivariate analysis of genetic and phenotypic data strengthens previous hypotheses concerning the historical biogeography of C. lusitanica: the Pleistocene subdivision of the species' range and a process of postglacial recolonization. Discrepancies between bioclimatic modeling predictions and the present-day distribution suggest that the species may still be expanding its range northwards. We propose the identification of two distinct units for the conservation of the species and suggest that this information should be taken into account in defining key areas for conservation in the Iberian Peninsula.

Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil

The non-native invasive anuran Lithobates catesbeianus is presently distributed in Brazil, especially in the Atlantic Rainforest biodiversity hotspot. Here, we use a maximum entropy ecological niche modeling algorithm (i) to model the North American native geographic distribution of this species and (ii) to project that model onto the whole of Brazil. After applying a threshold value that balances commission and omission errors, the projection results suggested high probabilities of occurrence mostly in southern and southeastern Brazil. We also present the first report on the species known distribution in Brazil, showing good agreement with model predictions. If the predictive map is interpreted as depicting invasiveness potential of L. catesbeianus, strategies to prevent further invasion in Brazil should be focused especially in the Atlantic Rainforest biodiversity hotspot.

Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Patterns of spatial distribution in macroalgal communities from tropical lotic ecosystems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

How the interplay between individual spatial memory and landscape persistence can generate population distribution patterns

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Temporal distribution of five bat species (Chiroptera, Phyllostomidae) from Panga Reserve, south-eastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial distribution of dengue in the city of Cruzeiro, São Paulo State, Brazil: use of geoprocessing tools

Este artigo tem por objetivo identificar padrões na distribuição espacial dos casos de dengue ocorridos no município de Cruzeiro/SP, no ano de 2006. Trata-se de um estudo ecológico e exploratório que utiliza as ferramentas de análise espacial na elaboração de mapas temáticos, com dados obtidos do SinanNet. Foi feita uma análise por área, tomando-se como unidade o setor censitário do IBGE; a análise considerou quatro meses do ano de 2006 que mostra a ocorrência da doença no município. Os mapas temáticos foram construídos pelo programa computacional TerraView 3.3.1; assim como os valores dos índices de Moran Global (I M) mês a mês e o estimador de Kernel. Foram georreferenciados 691 casos de dengue (taxa de 864,2 casos/100.000 habitantes); os Índices de Moran e p-valores obtidos foram I M = 0,080 (março) p = 0,11; I M = 0,285 (abril) p = 0,01; I M = 0,201 (maio) p = 0,01 e I M = 0,002 (junho) p = 0,57. Os primeiros casos foram identificados na região nordeste e central e os últimos casos, na região norte, nordeste e central. Foi possível identificar os setores censitários onde a epidemia teve início e como ocorreu têmporo-espacialmente no município.

Diversity and geographical distribution of phytoplasmas infecting China-tree in Argentina

Yellows diseases associated with phytoplasmas cause high mortality in China-tree (Melia azedarach) in Argentina, but there has been no previous large-scale survey to determine their diversity and geographical distribution. To assess the presence and identity of phytoplasmas affecting this species throughout the country, 425 samples of symptomatic trees collected at different geographic locations were analysed by a polymerase chain reaction (using universal and group-specific primers) and restriction fragment length polymorphism. Phytoplasmas belonging to 16SrIII-B group were detected at almost every location sampled, whereas 16SrXIII-C group phytoplasmas, reported for the first time in Argentina, were only found in two regions sharing similar agro-ecological characteristics (Northeast provinces and Tucuman). Double infections with 16SrIII-B and 16SrXIII-C group phytoplasmas were also recorded. Nucleotide sequencing of the 16S rDNA of three Argentinian 16SrXIII-C group phytoplasma isolates revealed high identity (99.6-99.3%) with the CbY1 isolate reported from Bolivia.