DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

Ecological niche modeling and geographical distribution of pollinator and plants: A case study of Peponapis fervens (Smith, 1879) (Eucerini: Apidae) and Cucurbita species (Cucurbitaceae)

The bees of the Peponapes genus (Eucerini, Apidae) have a Neotropical distribution with the center of species diversity located in Mexico and are specialized in Cucurbita plants. which have many species of economic importance. such as squashes and pumpkins Peponapis fervens is the only species of the genus known from southern South America The Cucurbita species occurring in the same area as P fervens Include four domesticated species (C ficifolia, C maxima maxima, C moschata and C pepo) and one non-domesticated species (Cucurbita maxima andreana) It was suggested that C. in andreana was the original pollen source to P fervens, and this bee expanded its geographical range due to the domestication of Cucurbita The potential geographical areas of these species were determined and compared using ecological niche modeling that was performed with the computational system openModeller and GARP with best subsets algorithm The climatic variables obtained through modeling were compared using Cluster Analysis Results show that the potential areas of domesticated species practically spread all over South America The potential area of P fervens Includes the areas of C m andreana but reaches a larger area, where the domesticated species of Cucurbita also Occur The Cluster Analysis shows a high climatic similarity between P fervens and C. m. andreana Nevertheless. P fervens presents the ability to occupy areas with wider ranges of climatic variables and to exploit resources provided by domesticated species (C) 2009 Elsevier B V All rights reserved

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.

A reference business process for ecological niche modelling

Ecological niche modelling combines species occurrence points with environmental raster layers in order to obtain models for describing the probabilistic distribution of species. The process to generate an ecological niche model is complex. It requires dealing with a large amount of data, use of different software packages for data conversion, for model generation and for different types of processing and analyses, among other functionalities. A software platform that integrates all requirements under a single and seamless interface would be very helpful for users. Furthermore, since biodiversity modelling is constantly evolving, new requirements are constantly being added in terms of functions, algorithms and data formats. This evolution must be accompanied by any software intended to be used in this area. In this scenario, a Service-Oriented Architecture (SOA) is an appropriate choice for designing such systems. According to SOA best practices and methodologies, the design of a reference business process must be performed prior to the architecture definition. The purpose is to understand the complexities of the process (business process in this context refers to the ecological niche modelling problem) and to design an architecture able to offer a comprehensive solution, called a reference architecture, that can be further detailed when implementing specific systems. This paper presents a reference business process for ecological niche modelling, as part of a major work focused on the definition of a reference architecture based on SOA concepts that will be used to evolve the openModeller software package for species modelling. The basic steps that are performed while developing a model are described, highlighting important aspects, based on the knowledge of modelling experts. In order to illustrate the steps defined for the process, an experiment was developed, modelling the distribution of Ouratea spectabilis (Mart.) Engl. (Ochnaceae) using openModeller. As a consequence of the knowledge gained with this work, many desirable improvements on the modelling software packages have been identified and are presented. Also, a discussion on the potential for large-scale experimentation in ecological niche modelling is provided, highlighting opportunities for research. The results obtained are very important for those involved in the development of modelling tools and systems, for requirement analysis and to provide insight on new features and trends for this category of systems. They can also be very helpful for beginners in modelling research, who can use the process and the experiment example as a guide to this complex activity. (c) 2008 Elsevier B.V. All rights reserved.

Ecological niche overlap in sister species: how do oil-collecting bees Macropis europaea and M. fulvipes (Hymenoptera: Melittidae) avoid competition and hybridization?

Oil-collecting bees are found worldwide and always in association with particular oil-producing flowers. In the Western Palearctic, three oil-collecting bee species within the genus Macropis (Hymenoptera, Melittidae) interact in a tight pollination mutualism with species of the only European oil-producing plant genus Lysimachia L. (Myrsinaceae). Two of these oil-collecting bees (Macropis europaea and Macropis fulvipes) show overlapping geographic distributions, comparable morphologies, and similar ecological characteristics (e.g., habitat type, floral preferences). In view of these similarities, we presume that hybridization should occur between the two species unless potential variation among the species' ecological niches prevents it, simultaneously decreasing competition for resources. Using modern genetic analyses and ecological niche modeling on a large bee sampling throughout Europe, we discuss new perspectives on the ecology and evolutionary history of this mutualism.

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 environmental niche modeling to understand biological invasions in a changing world

L'activité humaine affecte particulièrement la biodiversité, qui décline à une vitesse préoccupante. Parmi les facteurs réduisant la biodiversité, on trouve les espèces envahissantes. Symptomatiques d'un monde globalisé où l'échange se fait à l'échelle de la planète, certaines espèces, animales ou végétales, sont introduites, volontairement ou accidentellement par l'activité humaine (par exemple lors des échanges commerciaux ou par les voyageurs). Ainsi, ces espèces atteignent des régions qu'elles n'auraient jamais pu coloniser naturellement. Une fois introduites, l'absence de compétiteur peut les rendre particulièrement nuisibles. Ces nuisances sont plus ou moins directes, allant de problèmes sanitaires (p. ex. les piqûres très aigües des fourmis de feu, originaires d'Amérique du Sud et colonisant à une vitesse fulgurante les USA, l'Australie ou la Chine) à des nuisances sur la biodiversité (p. ex. les ravages de la perche du Nil sur la diversité unique des poissons Cichlidés du Lac Victoria). Il est donc important de pouvoir prévenir de telles introductions. De plus, pour le biologiste, ces espèces représentent une rare occasion de pouvoir comprendre les mécanismes évolutifs et écologiques qui expliquent le succès des envahissantes dans un monde où les équilibres sont bouleversés. Les modèles de niche environnementale sont un outil particulièrement utile dans le cadre de cette problématique. En reliant des observations d'espèces aux conditions environnementales où elles se trouvent, ils peuvent prédire la distribution potentielle des envahissantes, permettant d'anticiper et de mieux limiter leur impact. Toutefois, ils reposent sur des hypothèses pas évidentes à démontrer. L'une d'entre elle étant que la niche d'une espèce reste constante dans le temps, et dans l'espace. Le premier objectif de mon travail est de comparer si la niche d'une espèce envahissante diffère entre sa distribution d'origine native et celle d'origine introduite. En étudiant 50 espèces de plantes et 168 espèces de Mammifères, je démontre que c'est le cas et que par corolaire, il est possible de prédire leurs distributions. La deuxième partie de mon travail consiste à comprendre quelles seront les interactions entre le changement climatiques et les envahissantes, afin d'estimer leur impact sous un climat réchauffé. En étudiant la distribution de 49 espèces de plantes envahissantes, je démontre que les montagnes, régions relativement préservée par ce problème, deviendront bien plus exposées aux risques d'invasions biologiques. J'expose aussi comment les interactions entre l'activité humaine, le réchauffement climatique et les espèces envahissantes menacent la vigne sauvage en Europe et propose des zones géographiques particulièrement adaptée pour sa conservation. Enfin, à une échelle beaucoup plus locale, je montre qu'il est possible d'utiliser ces modèles de niches le long d'une rivière à une échelle extrêmement fine (1 mètre), potentiellement utile pour rationnaliser des mesures de conservations sur le terrain. - Biodiversity is significantly negatively affected by human activity. Invasive species are one of the most important factors causing biodiversity's decline. Intimately linked to the era of global trade, some plant or animal species can be accidentally or casually introduced with human activity (e.g. trade or travel). In this way, these species reach areas they could never reach through natural dispersal. Once naturalized, the lack of competitors can make these species highly noxious. Their effect is more or less direct, from sanitary problems (e.g. the harmful sting of Fire Ants, originating from South America and now spreading throughout USA, China and Australia) or can affect biodiversity (e.g. the Nile perch, devastating the one of the richest hotspot of Cichlid fishes diversity in Lake Victoria). It is thus important to prevent such harmful introductions. Moreover, invasive species represent for biologists one of the rare occasions to understand the evolutionary and ecological mechanisms behind the success of invaders in a world where natural equilibrium is already disturbed. Environmental niche models are particularly useful to tackle this problematic. By relating species observation to the environmental conditions where they occur, they can predict the potential distribution of invasive species, allowing a better anticipation and thus limiting their impact. However, they rely on strong assumption, one of the most important being that the modeled niche remains constant through space and time. The first aim of my thesis is to quantify the difference between the native and the invaded niche. By investigating 50 plant and 168 mammal species, I show that the niche is at least partially conserved, supporting for reliable predictions of invasive' s potential distributions. The second aim of my thesis is to understand the possible interactions between climate change and invasive species, such as to assess their impact under a warmer climate. By studying 49 invasive plant species, I show that mountain areas, which were relatively preserved, will become more suitable for biological invasions. Additionally, I show how interactions between human activity, global warming and invasive species are threatening the wild grapevine in Europe and propose geographical areas particularly adapted for conservation measures. Finally, at a much finer scale where conservation plannings ultimately take place, I show that it is possible to model the niche at very high resolution (1 meter) in an alluvial area allowing better prioritizations for conservation.

Measuring ecological niche overlap from occurrence and spatial environmental data

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

On the unknown ecological niche of Paracoccidioides brasiliensis: our hypothesis of 1989: present status and perspectives

In 1989, CONTI DÍAZ & RILLA published a hypothesis concerning the as yet unknown ecological niche of Paracoccidioides brasiliensis. The hypothesis proposed a highly efficient paracoccidioidal ecological strategy based on an important natural reservoir of the parasite, probably in heterothermic animals from fresh water environments. Further, the hypothesis proposed, a transient and variable residence in the soil with a wide aleuriospore dispersion throughout the environment together with an elevated capability of infecting humans, and domestic and wild animals. This paper analyzes scientific publications from the IX International Meeting on Paracoccidioidomycosis held in Águas de Lindoia, São Paulo, Brazil from 2-5 October 2005, providing a comparative study among this articles and with other recently published papers and the hypothesis' postulates. Since various findings and observations appear to agree with the postulates, the pursuit of novel, specific research projects in the supposed reservoirs is recommended partially or fully to confirm the hypothesis using classical laboratorial methods and modern molecular biology techniques.

Valuation of marine and coastal ecosystems: The role of ecological-economic modeling

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Ecological niche modelling and differentiation between Rhodnius neglectus Lent, 1954 and Rhodnius nasutus Stål, 1859 (Hemiptera: Reduviidae: Triatominae) in Brazil

Ecological niche modelling was used to predict the potential geographical distribution of Rhodnius nasutus Stål and Rhodnius neglectus Lent, in Brazil and to investigate the niche divergence between these morphologically similar triatomine species. The distribution of R. neglectus covered mainly the cerrado of Central Brazil, but the prediction maps also revealed its occurrence in transitional areas within the caatinga, Pantanal and Amazon biomes. The potential distribution of R. nasutus covered the Northeastern Region of Brazil in the semi-arid caatinga and the Maranhão babaçu forests. Clear ecological niche differences between these species were observed. R. nasutus occurred more in warmer and drier areas than R. neglectus. In the principal component analysis PC1 was correlated with altitude and temperature (mainly temperature in the coldest and driest months) and PC2 with vegetation index and precipitation. The prediction maps support potential areas of co-occurrence for these species in the Maranhão babaçu forests and in caatinga/cerrado transitional areas, mainly in state of Piaui. Entomologists engaged in Chagas disease vector surveillance should be aware that R. neglectus and R. nasutus can occur in the same localities of Northeastern Brazil. Thus, the identification of bugs in these areas should be improved by applying morphometrical and/or molecular methods.

Ecological niche models and patterns of richness and endemism of the southern Andean genus Eurymetopum (Coleoptera, Cleridae)

Eurymetopum is an Andean clerid genus with 22 species. We modeled the ecological niches of 19 species with Maxent and used them as potential distributional maps to identify patterns of richness and endemicity. All modeled species maps were overlapped in a single map in order to determine richness. We performed an optimality analysis with NDM/VNDM in a grid of 1º latitude-longitude in order to identify endemism. We found a highly rich area, located between 32º and 41º south latitude, where the richest pixels have 16 species. One area of endemism was identified, located in the Maule and Valdivian Forest biogeographic provinces, which extends also to the Santiago province of the Central Chilean subregion, and contains four endemic species (E. parallelum, E. prasinum, E. proteus, and E. viride), as well as 16 non-endemic species. The sympatry of these phylogenetically unrelated species might indicate ancient vicariance processes, followed by episodes of dispersal. Based on our results, we suggest a close relationship between these provinces, with the Maule representing a complex area.

Understanding the ecological niche to elucidate spatial strategies of the southernmost Tupinambis lizards

Understanding factors that shape ranges of species is central in evolutionary biology. Species distribution models have become important tools to test biogeographical, ecological and evolutionary hypotheses. Moreover, from an ecological and evolutionary perspective, these models help to elucidate the spatial strategies of species at a regional scale. We modelled species distributions of two phylogenetically, geographically and ecologically close Tupinambis species (Teiidae) that occupy the southernmost area of the genus distribution in South America. We hypothesized that similarities between these species might have induced spatial strategies at the species level, such as niche differentiation and divergence of distribution patterns at a regional scale. Using logistic regression and MaxEnt we obtained species distribution models that revealed interspecific differences in habitat requirements, such as environmental temperature, precipitation and altitude. Moreover, the models obtained suggest that although the ecological niches of Tupinambis merianae and T. rufescens are different, these species might co-occur in a large contact zone. We propose that niche plasticity could be the mechanism enabling their co-occurrence. Therefore, the approach used here allowed us to understand the spatial strategies of two Tupinambis lizards at a regional scale.

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.