962 resultados para habitat models


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This paper establishes the spawning habitat of the Brazilian sardine Sardinella brasiliensis and investigates the spatial variability of egg density and its relation with oceanographic conditions in the shelf of the south-east Brazil Bight (SBB). The spawning habitats of S. brasiliensis have been defined in terms of spatial models of egg density, temperature-salinity plots, quotient (Q) analysis and remote sensing data. Quotient curves (Q(C)) were constructed using the geographic distribution of egg density, temperature and salinity from samples collected during nine survey cruises between 1976 and 1993. The interannual sea surface temperature (SST) variability was determined using principal component analysis on the SST anomalies (SSTA) estimated from remote sensing data over the period between 1985 and 2007. The spatial pattern of egg occurrences in the SBB indicated that the largest concentration occurred between Paranagua and Sao Sebastiao. Spawning habitat expanded and contracted during the years, fluctuating around Paranagua. In January 1978 and January 1993, eggs were found nearly everywhere along the inner shelf of the SBB, while in January 1988 and 1991 spawning had contracted to their southernmost position. The SSTA maps for the spawning periods showed that in the case of habitat expansion (1993 only) anomalies over the SBB were zero or slightly negative, whereas for the contraction period anomalies were all positive. Sardinella brasiliensis is capable of exploring suitable spawning sites provided by the entrainment of the colder and less-saline South Atlantic Central Water onto the shelf by means of both coastal wind-driven (to the north-east of the SBB) and meander-induced (to the south-west of the SBB) upwelling.

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Coexistence of sympatric species is mediated by resource partitioning. Pumas occur sympatrically with jaguars throughout most of the jaguar's range but few studies have investigated space partitioning between both species. Here, camera trapping and occupancy models accounting for imperfect detection were employed in a Bayesian framework to investigate space partitioning between the jaguar and puma in Emas National Park (ENP), central Brazil. Jaguars were estimated to occupy 54.1% and pumas 39.3% of the sample sites. Jaguar occupancy was negatively correlated with distance to water and positively correlated with the amount of dense habitat surrounding the camera trap. Puma occupancy only showed a weak negative correlation with distance to water and with jaguar presence. Both species were less often present at the same site than expected under independent distributions. Jaguars had a significantly higher detection probability at cameras on roads than at off-road locations. For pumas, detection was similar on and off-road. Results indicate that both differences in habitat use and active avoidance shape space partitioning between jaguars and pumas in ENP. Considering its size, the jaguar is likely the competitively dominant of the two species. Owing to its habitat preferences, suitable jaguar habitat outside the park is probably sparse. Consequently, the jaguar population is likely largely confined to the park, while the puma population is known to extend into ENP's surroundings. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

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Habitat use by Sharp-tailed Tyrant (Culicivora caudacuta), and Cock-tailed Tyrant (Alectrurus tricolor) in the Cerrado of Southeastern Brazil. Obligatory grassland birds are dependent on a limited set of native habitats that are disappearing almost everywhere. We examined the use of macrohabitat and microhabitat by two threatened species of flycatchers, the Sharp-tailed Tyrant, Culicivora caudacuta and the Cock-tailed Tyrant, Alectrurus tricolor in a preserved area of cerrado. We generated logistic regression models to explain the presence of these species through variables of microhabitat. Both flycatchers occurred mainly in grassland areas and favored areas with a low density of palms (Attalea geraensis) and trees. The Sharp-tailed Tyrant also favored areas with a high density of low shrubs (< 1 m) and less exposed soil. The positive relationship found between the presence of Sharp-tailed Tyrant and soil cover may indicate the importance of litter and understory vegetation for shelter and food. The conservation of both flycatcher species in the study area should benefit from controlling palm density and the maintenance of grasslands with low shrubs.

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During the last three decades, several predictive models have been developed to estimate the somatic production of macroinvertebrates. Although the models have been evaluated for their ability to assess the production of macrobenthos in different marine ecosystems, these approaches have not been applied specifically to sandy beach macrofauna and may not be directly applicable to this transitional environment. Hence, in this study, a broad literature review of sandy beach macrofauna production was conducted and estimates obtained with cohort-based and size-based methods were collected. The performance of nine models in estimating the production of individual populations from the sandy beach environment, evaluated for all taxonomic groups combined and for individual groups separately, was assessed, comparing the production predicted by the models to the estimates obtained from the literature (observed production). Most of the models overestimated population production compared to observed production estimates, whether for all populations combined or more specific taxonomic groups. However, estimates by two models developed by Cusson and Bourget provided best fits to measured production, and thus represent the best alternatives to the cohort-based and size-based methods in this habitat. The consistent performance of one of these Cusson and Bourget models, which was developed for the macrobenthos of sandy substrate habitats (C&B-SS), shows that the performance of a model does not depend on whether it was developed for a specific taxonomic group. Moreover, since some widely used models (e.g., the Robertson model) show very different responses when applied to the macrofauna of different marine environments (e.g., sandy beaches and estuaries), prior evaluation of these models is essential.

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The Great Barrier Reef hosts the only known reliable aggregation of dwarf minke whale (Balaenoptera acutorostrata subspecies) in Australian waters. While this short seasonal aggregation is quite predictable, the distribution and movements of the whales during the rest of their annual cycle are poorly understood. In particular, feeding and resting areas on their southward migration which are likely to be important have not been described. Using satellite telemetry data, I modelled the habitat use of seven whales during their southward migration through waters surrounding Tasmania. The whales were tagged with LIMPET satellite tags in the GBR in July 2013 (2 individuals) and 2014 (5 individuals). The study area around Tasmania was divided into 10km² cells and the time spent by each individual in each cell was calculated and averaged based on the number of animals using the cell. Two areas of high residency time were highlighted: south-western Bass Strait and Storm Bay (SE Tasmania). Remotely sensed ocean data were extracted for each cell and averaged temporally during the entire period of residency. Using Generalised Additive Models I explored the influence of key environmental characteristics. Nine predictors (bathymetry, distance from coast, distance from shore, gradient of sea surface temperature, sea surface height (absolute and variance), gradient of current speed, wind speed and chlorophyll-a concentration) were retained in the final model which explained 68% of the total variance. Regions of higher time-spent values were characterised by shallow waters, proximity to the coast (but not to the shelf break), high winds and sea surface height but low gradient of sea surface temperature. Given that the two high residency areas corresponded with regions where other marine predators also forage in Bass Strait and Storm Bay, I suggest the whales were probably feeding, rather than resting in these areas.

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P>1. There are a number of models describing population structure, many of which have the capacity to incorporate spatial habitat effects. One such model is the source-sink model, that describes a system where some habitats have a natality that is higher than mortality (source) and others have a mortality that exceeds natality (sink). A source can be maintained in the absence of migration, whereas a sink will go extinct. 2. However, the interaction between population dynamics and habitat quality is complex, and concerns have been raised about the validity of published empirical studies addressing source-sink dynamics. In particular, some of these studies fail to provide data on survival, a significant component in disentangling a sink from a low quality source. Moreover, failing to account for a density-dependent increase in mortality, or decrease in fecundity, can result in a territory being falsely assigned as a sink, when in fact, this density-dependent suppression only decreases the population size to a lower level, hence indicating a 'pseudo-sink'. 3. In this study, we investigate a long-term data set for key components of territory-specific demography (mortality and reproduction) and their relationship to habitat characteristics in the territorial, group-living Siberian jay (Perisoreus infaustus). We also assess territory-specific population growth rates (r), to test whether spatial population dynamics are consistent with the ideas of source-sink dynamics. 4. Although average mortality did not differ between sexes, habitat-specific mortality did. Female mortality was higher in older forests, a pattern not observed in males. Male mortality only increased with an increasing amount of open areas. Moreover, reproductive success was higher further away from human settlement, indicating a strong effect of human-associated nest predators. 5. Averaged over all years, 76% of the territories were sources. These territories generally consisted of less open areas, and were located further away from human settlement. 6. The source-sink model provides a tool for modelling demography in distinct habitat patches of different quality, which can aid in identifying key habitats within the landscape, and thus, reduce the risk of implementing unsound management decisions.

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In most species, some individuals delay reproduction or occupy inferior breeding positions. The queue hypothesis tries to explain both patterns by proposing that individuals strategically delay breeding (queue) to acquire better breeding or social positions. In 1995, Ens, Weissing, and Drent addressed evolutionarily stable queuing strategies in situations with habitat heterogeneity. However, their model did not consider the non - mutually exclusive individual quality hypothesis, which suggests that some individuals delay breeding or occupy inferior breeding positions because they are poor competitors. Here we extend their model with individual differences in competitive abilities, which are probably plentiful in nature. We show that including even the smallest competitive asymmetries will result in individuals using queuing strategies completely different from those in models that assume equal competitors. Subsequently, we investigate how well our models can explain settlement patterns in the wild, using a long-term study on oystercatchers. This long-lived shorebird exhibits strong variation in age of first reproduction and territory quality. We show that only models that include competitive asymmetries can explain why oystercatchers' settlement patterns depend on natal origin. We conclude that predictions from queuing models are very sensitive to assumptions about competitive asymmetries, while detecting such differences in the wild is often problematic.

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Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

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We investigate the effect of habitat fragmentation on the genetic diversity of a species experiencing a range expansion. These two evolutionary processes have not been studied yet, at the same time, owing to the difficulties of deriving analytic results for non-equilibrium models. Here we provide a description of their interaction by using extensive spatial and temporal coalescent simulations and we suggest guidelines for a proper genetic sampling to detect fragmentation. To model habitat fragmentation, we simulated a two-dimensional lattice of demes partitioned into groups (patches) by adding barriers to dispersal. After letting a population expand on this grid, we sampled lineages from the lattice at several scales and studied their coalescent history. We find that in order to detect fragmentation, one needs to extensively sample at a local level rather than at a landscape level. This is because the gene genealogy of a scattered sample is less sensitive to the presence of genetic barriers. Considering the effect of temporal changes of fragmentation intensities, we find that at least 10, but often >100, generations are needed to affect local genetic diversity and population structure. This result explains why recent habitat fragmentation does not always lead to detectable signatures in the genetic structure of populations. Finally, as expected, long-distance dispersal increases local genetic diversity and decreases levels of population differentiation, efficiently counteracting the effects of fragmentation.

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Background: A small pond, c. 90 years old, near Bern, Switzerland contains a population of threespine stickleback (Gasterosteus aculeatus) with two distinct male phenotypes. Males of one type are large, and red, and nest in the shallow littoral zone. The males of the other are small and orange, and nest offshore at slightly greater depth. The females in this population are phenotypically highly variable but cannot easily be assigned to either male type. Question: Is the existence of two sympatric male morphs maintained by substrate-associated male nest site choice and facilitated by female mate preferences? Organisms: Male stickleback caught individually at their breeding sites. Females caught with minnow traps. Methods: In experimental tanks, we simulated the slope and substrate of the two nesting habitats. We then placed individual males in a tank and observed in which habitat the male would build his nest. In a simultaneous two-stimulus choice design, we gave females the choice between a large, red male and a small, orange one. We measured female morphology and used linear mixed effect models to determine whether female preference correlated with female morphology. Results: Both red and orange males preferred nesting in the habitat that simulated the slightly deeper offshore condition. This is the habitat occupied by the small, orange males in the pond itself. The proportion of females that chose a small orange male was similar to that which chose a large red male. Several aspects of female phenotype correlated with the male type that a female preferred.

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We present a framework for fitting multiple random walks to animal movement paths consisting of ordered sets of step lengths and turning angles. Each step and turn is assigned to one of a number of random walks, each characteristic of a different behavioral state. Behavioral state assignments may be inferred purely from movement data or may include the habitat type in which the animals are located. Switching between different behavioral states may be modeled explicitly using a state transition matrix estimated directly from data, or switching probabilities may take into account the proximity of animals to landscape features. Model fitting is undertaken within a Bayesian framework using the WinBUGS software. These methods allow for identification of different movement states using several properties of observed paths and lead naturally to the formulation of movement models. Analysis of relocation data from elk released in east-central Ontario, Canada, suggests a biphasic movement behavior: elk are either in an "encamped" state in which step lengths are small and turning angles are high, or in an "exploratory" state, in which daily step lengths are several kilometers and turning angles are small. Animals encamp in open habitat (agricultural fields and opened forest), but the exploratory state is not associated with any particular habitat type.

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We compared lifetime and population energy budgets of the extraordinary long-lived ocean quahog Arctica islandica from 6 different sites - the Norwegian coast, Kattegat, Kiel Bay, White Sea, German Bight, and off northeast Iceland - covering a temperature and salinity gradient of 4-10°C (annual mean) and 25-34, respectively. Based on von Bertalanffy growth models and size-mass relationships, we computed organic matter production of body (PSB) and of shell (PSS), whereas gonad production (PG) was estimated from the seasonal cycle in mass. Respiration (R) was computed by a model driven by body mass, temperature, and site. A. islandica populations differed distinctly in maximum life span (40 y in Kiel Bay to 197 y in Iceland), but less in growth performance (phi' ranged from 2.41 in the White Sea to 2.65 in Kattegat). Individual lifetime energy throughput, as approximated by assimilation, was highest in Iceland (43,730 kJ) and lowest in the White Sea (313 kJ). Net growth efficiency ranged between 0.251 and 0.348, whereas lifetime energy investment distinctly shifted from somatic to gonad production with increasing life span; PS/PG decreased from 0.362 (Kiel Bay, 40 y) to 0.031 (Iceland, 197 y). Population annual energy budgets were derived from individual budgets and estimates of population mortality rate (0.035/y in Iceland to 0.173/y in Kiel Bay). Relationships between budget ratios were similar on the population level, albeit with more emphasis on somatic production; PS/ PG ranged from 0.196 (Iceland) to 2.728 (White Sea), and P/B ranged from 0.203-0.285/y. Life span is the principal determinant of the relationship between budget parameters, whereas temperature affects net growth efficiency only. In the White Sea population, both growth performance and net growth efficiency of A. islandica were lowest. We presume that low temperature combined with low salinity represent a particularly stressful environment for this species.

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Persistence and abundance of species is determined by habitat availability and the ability to disperse and colonize habitats at contrasting spatial scales. Favourable habitat fragments are also heterogeneous in quality, providing differing opportunities for establishment and affecting the population dynamics of a species. Based on these principles, we suggest that the presence and abundance of epiphytes may reflect their dispersal ability, which is primarily determined by the spatial structure of host trees, but also by host quality. To our knowledge there has been no explicit test of the importance of host tree spatial pattern for epiphytes in Mediterranean forests. We hypothesized that performance and host occupancy in a favourable habitat depend on the spatial pattern of host trees, because this pattern affects the dispersal ability of each epiphyte and it also determines the availability of suitable sites for establishment. We tested this hypothesis using new point pattern analysis tools and generalized linear mixed models to investigate the spatial distribution and performance of the epiphytic lichen Lobaria pulmonaria, which inhabits two types of host trees (beeches and Iberian oaks). We tested the effects on L. pulmonaria distribution of tree size, spatial configuration, and host tree identity. We built a model including tree size, stand structure, and several neighbourhood predictors to understand the effect of host tree on L. pulmonaria. We also investigated the relative importance of spatial patterning on the presence and abundance of the species, independently of the host tree configuration. L. pulmonaria distribution was highly dependent on habitat quality for successful establishment, i.e., tree species identity, tree diameter, and several forest stand structure surrogates. For beech trees, tree diameter was the main factor influencing presence and cover of the lichen, although larger lichen-colonized trees were located close to focal trees, i.e., young trees. However, oak diameter was not an important factor, suggesting that bark roughness at all diameters favoured lichen establishment. Our results indicate that L. pulmonaria dispersal is not spatially restricted, but it is dependent on habitat quality. Furthermore, new spatial analysis tools suggested that L. pulmonaria cover exhibits a distinct pattern, although the spatial pattern of tree position and size was random.

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Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.