Habitat connectivity for pollinator beetles using surface metrics

Measuring habitat connectivity in complex landscapes is a major focus of landscape ecology and conservation research. Most studies use a binary landscape or patch mosaic model for describing spatial heterogeneity and understanding pattern-process relationships. While the value of landscape gradient approaches proposed by McGarigal and Cushman are recognized, applications of these newly proposed three dimensional surface metrics remain under-used. We created a gradient map of habitat quality from several GIS layers and applied three dimensional surface metrics to measure connectivity between 67 locations in Indiana, USA surveyed for one group of ecosystem service providers, flower longicorn beetles (Cerambycidae: Lepturinae). The three dimensional surface metrics applied to the landscape gradient model showed great potential to explain the differences of lepturine assemblages among the 2,211 studied landscapes (between site pairs). Surface kurtosis and its interaction with geographic distance were among the most important metrics. This approach provided unique information about the landscape through four configuration metrics. There were some uniform trends of the responses of many species to some of surface metrics, however some species responded differently to other metrics. We suggest that three dimensional surface metrics applied to a habitat surface map created with insight into species requirements is a valuable approach to understanding the spatial dynamics of species, guilds, and ecosystem services.     

Evaluation of landscape connectivity at community level using satellite-derived NDVI

Landscape connectivity, defined as the degree to which the landscape facilitates or impedes movement among resource patches, has been considered to be a key issue for biodiversity conservation. However, the use of landscape connectivity measurements has been strongly criticised due to uncertainties in the methods used and the lack of validation. Moreover, measurements are typically restricted to the population level, whereas management is generally carried out at the community level. Here, we used satellite imagery and network metrics to predict the landscape connectivity at community level for semi-natural herbaceous patches in an urban area near Paris (France). We tested different measurement methods, both taking into account and ignoring the spatial heterogeneity of matrix resistance estimated by the normalised difference vegetation index (NDVI), and quantifying the link strength between patches with the shortest path and flow metrics. We assessed the fit of these connectivity predictions with empirical data on plant communities embedded in an urban matrix. Our results indicate that the best fit with the empirical data is obtained when the connectivity is estimated with the flow metric and takes into account the matrix heterogeneity. Overall, our study helps to estimate the landscape connectivity of urban areas and makes recommendations for ways in which we might optimise landscape planning with respect to conservation of urban biodiversity.     

Targeting and evaluating biodiversity conservation action within fragmented landscapes: an approach based on generic focal species and least-cost networks

The focus of biodiversity conservation is shifting to larger spatial scales in response to habitat fragmentation and the need to integrate multiple landscape objectives. Conservation strategies increasingly incorporate measures to combat fragmentation such as ecological networks. These are often based on assessment of landscape structure but such approaches fail to capitalise on the potential offered by more ecologically robust assessments of landscape function and connectivity. In this paper, we describe a modelling approach to identifying functional habitat networks and demonstrate its application to a fragmented landscape where policy initiatives seek to improve conditions for woodland biodiversity including increasing woodland cover. Functional habitat networks were defined by identifying suitable habitat and by modelling connectivity using least-cost approaches to account for matrix permeability. Generic focal species (GFS) profiles were developed, in consultation with stakeholders, to represent species with high and moderate sensitivity to fragmentation. We demonstrated how this form of analysis can be used to aid the spatial targeting of conservation actions. This ‘targeted’ action scenario was tested for effectiveness against comparable scenarios, which were based on random and clumped actions within the same landscape. We tested effectiveness using structural metrics, network-based metrics and a published functional connectivity indicator. Targeting actions within networks resulted in the highest mean woodland area and highest connectivity indicator value. Our approach provides an assessment of landscape function by recognising the importance of the landscape matrix. It provides a framework for the targeting and evaluation of alternative conservation options, offering a pragmatic, ecologically-robust solution to a current need in applied landscape ecology.     

A comparison of metrics predicting landscape connectivity for a highly interactive species along an urban gradient in Colorado, USA

Many organisms persist in fragmented habitat where movement between patches is essential for long-term demographic and genetic stability. In the absence of direct observation of movement, connectivity or isolation metrics are useful to characterize potential patch-level connectivity. However, multiple metrics exist at varying levels of complexity, and empirical data on species distribution are rarely used to compare performance of metrics. We compared 12 connectivity metrics of varying degrees of complexity to determine which metric best predicts the distribution of prairie dog colonies along an urban gradient of 385 isolated habitat patches in Denver, Colorado, USA. We found that a modified version of the incidence function model including area-weighting of patches and a cost-weighted distance surface best predicted occupancy, where we assumed roads were fairly impermeable to movement, and low-lying drainages provided dispersal corridors. We also found this result to be robust to a range of cost weight parameters. Our results suggest that metrics should incorporate both patch area and the composition of the surrounding matrix. These results provide guidance for improved landscape habitat modeling in fragmented landscapes and can help identify target habitat for conservation and management of prairie dogs in urban systems.     

Is landscape connectivity a dependent or independent variable?

With growing interest in landscape connectivity, it is timely to ask what research has been done and what re mains to be done. I surveyed papers investigating landscape connectivity from 1985 to 2000. From these papers, I determined if connectivity had been treated as an independent or dependent variable, what connectivity metrics were used, and if the study took an empirical or modeling approach to studying connectivity. Most studies treated connectivity as an independent variable, despite how little we know about how landscape structure and organism movement behaviour interact to determine landscape connectivity. Structural measures of connectivity were more common than functional measures, particularly if connectivity was treated as an independent variable. Though there was a good balance between modeling and empirical approaches overall – studies dealing with connectivity as a dependent, functional variable were mainly modeling studies. Based on the research achieved thus far, fu ture landscape connectivity research should focus on: (1) elucidating the relationship between landscape struc ture, organism movement behaviour, and landscape connectivity (e.g., treating connectivity as a dependent variable), (2) determining the relationships between different measures of connectivity, particularly structural and functional measures, and (3) empirically testing model predictions regarding landscape connectivity.This revised version was published online in May 2005 with corrections to the Cover Date.     

Modeling occupancy dynamics of a rare species,Franklin’s ground squirrel,with limited data: are simple connectivity metrics adequate?

Conservation of populations in fragmented habitats is often based on spatially realistic metapopulation theory, which predicts negative relationships between patch extinction and area and patch colonization and isolation. Cost-distance metrics have been developed to integrate habitat quality into measures of connectivity, and thus may improve predictive power of the area-isolation paradigm. Few studies use empirical data to compare predictive performance of complex cost-distance metrics to simple metrics relying on Euclidean distances. We used 3 years of presence–absence data to examine relative influence of habitat quality, habitat area, and connectivity on occupancy and extinction rates for Poliocitellus franklinii (Franklin’s ground squirrel), a rare grassland species of conservation concern. We calculated connectivity using nearest-neighbor (NN) and incidence function model (IFM) metrics based on Euclidean and cost-distances. Habitat quality, area, and connectivity were all positive predictors for occupancy, but only isolation was a positive predictor of extinction. P. franklinii does not appear to be a tallgrass prairie obligate, but the species distribution is limited by isolation of suitable grassland habitat. A simple NN metric measuring Euclidean distance between a target area and nearest occupied source outperformed IFM (Euclidean and cost-distance) in predicting occupancy and extinction for P. franklinii. Although NN metrics are criticized for considering only the contribution of the source nearest to a target, this simplicity may be acceptable when measuring connectivity for rare species with few occupied habitat patches within dispersal distance.     

Integrating graph-based connectivity metrics into species distribution models

Species distribution models (SDMs) are commonly used in ecology to map the probability of species occurrence on the basis of predictive factors describing the physical environment. We propose an improvement on SDMs by using graph methods to quantify landscape connectivity. After (1) mapping the habitat suitable for a given species, this approach consists in (2) building a landscape graph, (3) computing patch-based connectivity metrics, (4) extrapolating the values of those metrics to any point of space, and (5) integrating those connectivity metrics into a predictive model of presence. For a given species, this method can be used to interpret the significance of the metrics in the models in terms of population structure. The method is illustrated here by the construction of an SDM for the European tree frog in the region of Franche-Comté (France). The results show that the connectivity metrics improve the explanatory power of the SDM and emphasize the important role of the habitat network.     

Using network theory to prioritize management in a desert bighorn sheep metapopulation

Connectivity models using empirically-derived landscape resistance maps can predict potential linkages among fragmented animal and plant populations. However, such models have rarely been used to guide systematic decision-making, such as identifying the most important habitat patches and dispersal corridors to protect or restore in order to maximize regional connectivity. Combining resistance models with network theory offers one means of prioritizing management for connectivity, and we applied this approach to a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave Desert of the southwestern United States. We used a genetic-based landscape resistance model to construct network models of genetic connectivity (potential for gene flow) and demographic connectivity (potential for colonization of empty habitat patches), which may differ because of sex-biased dispersal in bighorn sheep. We identified high-priority habitat patches and corridors and found that the type of connectivity and the network metric used to quantify connectivity had substantial effects on prioritization results, although some features ranked highly across all combinations. Rankings were also sensitive to our empirically-derived estimates of maximum effective dispersal distance, highlighting the importance of this often-ignored parameter. Patch-based analogs of our network metrics predicted both neutral and mitochondrial genetic diversity of 25 populations within the study area. This study demonstrates that network theory can enhance the utility of landscape resistance models as tools for conservation, but it is critical to consider the implications of sex-biased dispersal, the biological relevance of network metrics, and the uncertainty associated with dispersal range and behavior when using this approach.     

Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation

The loss of connectivity of natural areas is a major threat for wildlife dispersal and survival and for the conservation of biodiversity in general. Thus, there is an increasing interest in considering connectivity in landscape planning and habitat conservation. In this context, graph structures have been shown to be a powerful and effective way of both representing the landscape pattern as a network and performing complex analysis regarding landscape connectivity. Many indices have been used for connectivity analyses so far but comparatively very little efforts have been made to understand their behaviour and sensitivity to spatial changes, which seriously undermines their adequate interpretation and usefulness. We systematically compare a set of ten graph-based connectivity indices, evaluating their reaction to different types of change that can occur in the landscape (habitat patches loss, corridors loss, etc.) and their effectiveness for identifying which landscape elements are more critical for habitat conservation. Many of the available indices were found to present serious limitations that make them inadequate as a basis for conservation planning. We present a new index (IIC) that achieves all the properties of an ideal index according to our analysis. We suggest that the connectivity problem should be considered within the wider concept of habitat availability, which considers a habitat patch itself as a space where connectivity exists, integrating habitat amount and connectivity between habitat patches in a single measure.     

How should we measure landscape connectivity?

The methods for measuring landscape connectivity have never been compared or tested for their responses to habitat fragmentation. We simulated movement, mortality and boundary reactions across a wide range of landscape structures to analyze the response of landscape connectivity measures to habitat fragmentation. Landscape connectivity was measured as either dispersal success or search time, based on immigration into all habitat patches in the landscape. Both measures indicated higher connectivity in more fragmented landscapes, a potential for problematic conclusions for conservation plans. We introduce cell immigration as a new measure for landscape connectivity. Cell immigration is the rate of immigration into equal-sized habitat cells in the landscape. It includes both within- and between-patch movement, and shows a negative response to habitat fragmentation. This complies with intuition and existing theoretical work. This method for measuring connectivity is highly robust to reductions in sample size (i.e., number of habitat cells included in the estimate), and we hypothesize that it therefore should be amenable to use in empirical studies. The connectivity measures were weakly correlated to each other and are therefore generally not comparable. We also tested immigration into a single patch as an index of connectivity by comparing it to cell immigration over the landscape. This is essentially a comparison between patch-scale and landscape-scale measurement, and revealed some potential for patch immigration to predict connectivity at the landscape scale. However, this relationship depends on the size of the single patch, the dispersal characteristics of the species, and the amount of habitat in the landscape. We conclude that the response of connectivity measures to habitat fragmentation should be understood before deriving conclusions for conservation management.     

Improved connectivity analysis using multiple low-cost paths to evaluate habitat for the endangered San Martin titi monkey (Plecturocebus oenanthe) in north-central Peru

Context

Graph-theoretic evaluations of habitat connectivity often rely upon least-cost path analyses to evaluate connectedness of habitat patches, based on an underlying cost surface. We present two improvements upon these methods.

Objectives

As a case study to test these methods, we evaluated habitat connectivity for the endangered San Martin titi monkey (Plecturocebus oenanthe) in north-central Peru, to prioritize habitat patches for conservation.

Methods

First, rather than using a single least-cost path between habitat patches, we analyzed multigraphs made up of multiple low-cost paths. This allows us to differentiate between patches connected through a single narrow corridor, and patches connected by a wide swath of traversable land. We evaluate potential movement pathways by iteratively removing paths and recomputing connectivity metrics. Second, instead of performing a sensitivity analysis by varying costs uniformly across the landscape, we generated landscapes with spatially varying costs.

Results

This approach produced a more informative assessment of connectivity than standard graph analyses. Of the 4340 habitat patches considered across the landscape, we identified the most important 100, those frequently ranked highly through repeated network modifications, for multiple metrics and cost surfaces.

Conclusions

These methods represent a novel approach for assessing connectivity, better accounting for spatial configurations of habitat patches and uncertainty in cost surfaces. The ability to identify habitat patches with more possible routes to other patches is of interest for resiliency planning and prioritization in the face of continued habitat loss and climate change. These methods should be broadly applicable to conservation planning for other wildlife species.

     

Measuring landscape connectivity: On the importance of within-patch connectivity

Context

Many connectivity metrics have been used to measure the connectivity of a landscape and to evaluate the effects of land-use changes and potential mitigation measures. However, there are still gaps in our understanding of how to accurately quantify landscape connectivity.

Objectives

A number of metrics only measure between-patch connectivity, i.e. the connectivity between different habitat patches, which can produce misleading results. This paper demonstrates that the inclusion of within-patch connectivity is important for accurate results.

Methods

The behavior of two metrics is compared: the Connectance Index (CONNECT), which measures only between-patch connectivity, and the effective mesh size (m_eff), which includes both within-patch and between-patch connectivity. The connectivity values of both metrics were calculated on a set of simulated landscapes. Twenty cities were then added to these landscapes to calculate the resulting changes in connectivity.

Results

We found that when using CONNECT counter-intuitive results occurred due to not including within-patch connectivity, such as scenarios where connectivity increased with increasing habitat loss and fragmentation. These counter-intuitive results were resolved when using m_eff. For example, landscapes with low habitat amount may be particularly sensitive to urban development, but this is not reflected by CONNECT.

Conclusions

Applying misleading results from metrics like CONNECT can have detrimental effects on natural ecosystems, because reductions in within-patch connectivity by human activities are neglected. Therefore, this paper provides evidence for the crucial need to consider the balance between within-patch connectivity and between-patch connectivity when calculating the connectivity of landscapes.

     

Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal

Landscape connectivity can be viewed from two perspectives that could be considered as extremes of a gradient: functional connectivity (refers to how the behavior of a dispersing organism is affected by landscape structure and elements) and structural connectivity (depends on the spatial configuration of habitat patches in the landscape like vicinity or presence of barriers). Here we argue that dispersal behavior changes with landscape configuration stressing the evolutionary dimension that has often been ignored in landscape ecology. Our working hypothesis is that the functional grain of resource patches in the landscape is a crucial factor shaping individual movements, and therefore influencing landscape connectivity. Such changes are likely to occur on the short-term (some generations). We review empirical studies comparing dispersal behavior in landscapes differing in their fragmentation level, i.e., with variable resource grain. We show that behavioral variation affecting each of the three stages of the dispersal process (emigration, displacement or transfer in the matrix, and immigration) is indeed likely to occur according to selective pressures resulting from changes in the grain of the landscape (mortality or deferred costs). Accordingly, landscape connectivity results from the interaction between the dispersal behavior of individuals and the grain of each particular landscape. The existence of this interaction requires that connectivity estimates (being based on individual-based models, least cost distance algorithms, and structural connectivity metrics or even Euclidian distance) should be carefully evaluated for their applicability with respect to the required level of precision in species-specific and landscape information.     

Quantifying landscape connectivity through the use of connectivity response curves

Habitat connectivity is an essential component of biodiversity conservation. Simulated landscapes were manipulated to quantify the impact of changes to the amount, fragmentation and dispersion of habitat on a widely applied landscape connectivity metric, the probability of connectivity index. Index results for different landscape scenarios were plotted against the dispersal distances used for their calculation to create connectivity response curves for each scenario. Understanding index response to controlled changes in landscape structure at a range of spatial scales can be used to give context to comparison of alternative landscape management scenarios. Increased amounts of habitat, decreased fragmentation and decreased inter-patch distances resulted in increased connectivity index values. Connectivity response curves demonstrated increases in assessed connectivity for scenarios with continuous corridors or “stepping stone” connectors. The sensitivity of connectivity response curves to controlled changes in landscape structure indicate that this approach is able to detect and distinguish between different types of landscape changes, but that delineation of habitat and method of quantifying dispersal probability incorporate assumptions that must be recognized when interpreting results to guide landscape management. Representing landscape connectivity in this manner allows for the impacts of alternative landscape management strategies to be compared visually through comparative plots, or statistically through the parameters that describe connectivity response curves.     

Comparing the role of site disturbance and landscape properties on understory species richness in fragmented periurban Mediterranean forests

We hypothesized that the spatial configuration and dynamics of periurban forest patches in Barcelona (NE of Spain) played a minor role in determining plant species richness and assemblage compared to site conditions, and particularly to both direct (measured at plot level) and potential (inferred from landscape metrics) human-associated site disturbance. The presence of all understory vascular plants was recorded on 252 plots of 100 m² randomly selected within forest patches ranging in size from 0.25 ha to 218 ha. Species were divided into 6 groups, according to their ecology and conservation status. Site condition was assessed at plot level and included physical attributes, human-induced disturbance and Quercus spp. tree cover. Landscape structure and dynamics were assessed from patch metrics and patch history. We also calculated a set of landscape metrics related to potential human accessibility to forests. Results of multiple linear regressions indicated that the variance explained for non-forest species groups was higher than for forest species richness. Most of the main correlates corresponded to site disturbance variables related to direct human alteration, or to landscape variables associated to indirect human effects on forests: Quercus tree cover (a proxy for successional status) was the most important correlate of non-forest species richness, which decreased when Quercus tree cover increased. Human-induced disturbance was an important correlate of synanthropic and total species richness, which were higher in recently managed and in highly frequented forests. Potential human accessibility also affected the richness of most species groups. In contrast, patch size, patch shape and connectivity played a minor role, as did patch history. We conclude that human influence on species richness in periurban forests takes place on a small scale, whereas large-scale effects attributable to landscape structure and fragmentation are comparatively less important. Implications of these results for the conservation of plant species in periurban forests are discussed.     

Two measures of landscape-graph connectivity: assessment across gradients in area and configuration

Landscape connectivity is critical to species persistence in the face of habitat loss and fragmentation. Graph theory is a well-defined method for quantifying connectivity that has tremendous potential for ecology, but its application has been limited to a small number of conservation scenarios, each with a fixed proportion of habitat. Because it is important to distinguish changes in habitat configuration from changes in habitat area in assessing the potential impacts of fragmentation, we investigated two metrics that measure these different influences on connectivity. The first metric, graph diameter, has been advocated as a useful measure of habitat configuration. We propose a second area-based metric that combines information on the amount of connected habitat and the amount of habitat in the largest patch. We calculated each metric across gradients in habitat area and configuration using multifractal neutral landscapes. The results identify critical connectivity thresholds as a function of the level of fragmentation and a parallel is drawn between the behavior of graph theory metrics and those of percolation theory. The combination of the two metrics provides a means for targeting sites most at risk of suffering low potential connectivity as a result of habitat fragmentation.     

Finding the functional grain: comparing methods for scaling resistance surfaces

The influence of landscape features on the movement of an organism between two point locations is often measured as an effective distance. Typically, raster models of landscape resistance are used to calculate effective distance. Because organisms may experience landscape heterogeneity at different scales (i.e. functional grains), using a raster with too fine or too coarse a spatial grain (i.e. analysis grain) may lead to inaccurate estimates of effective distance. We adopted a simulation approach where the true functional grain and effective distance for a theoretical organism were defined and the analysis grains of landscape connectivity models were systematically changed. We used moving windows and grains of connectivity, a recently introduced landscape graph method that uses an irregular tessellation of the resistance surface to coarsen the landscape data. We then used least-cost path metrics to measure effective distance and found that matching the functional and analysis grain sizes was most accurate at recovering the expected effective distance, affirming the importance of multi-scale analysis. Moving window scaling with a maximum function (win.max) performed well when the majority of landscape structure influencing connectivity consisted of high resistance features. Moving window scaling with a minimum function (win.min) performed well when the relevant landscape structure consisted of low resistance regions. The grains of connectivity method performed well under all scenarios, avoiding an a priori choice of window function, which may be challenging in complex landscapes. Appendices are provided that demonstrate the use of grains of connectivity models.     

Surface metrics: an alternative to patch metrics for the quantification of landscape structure

Modern landscape ecology is based on the patch mosaic paradigm, in which landscapes are conceptualized and analyzed as mosaics of discrete patches. While this model has been widely successful, there are many situations where it is more meaningful to model landscape structure based on continuous rather than discrete spatial heterogeneity. The growing field of surface metrology offers a variety of surface metrics for quantifying landscape gradients, yet these metrics are largely unknown and/or unused by landscape ecologists. In this paper, we describe a suite of surface metrics with potential for landscape ecological application. We assessed the redundancy among metrics and sought to find groups of similarly behaved metrics by examining metric performance across 264 sample landscapes in western Turkey. For comparative purposes and to evaluate the robustness of the observed patterns, we examined 16 different patch mosaic models and 18 different landscape gradient models of landscape structure. Surface metrics were highly redundant, but less so than patch metrics, and consistently aggregated into four cohesive clusters of similarly behaved metrics representing surface roughness, shape of the surface height distribution, and angular and radial surface texture. While the surface roughness metrics have strong analogs among the patch metrics, the other surface components are largely unique to landscape gradients. We contend that the surface properties we identified are nearly universal and have potential to offer new insights into landscape pattern–process relationships. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The pond network: can structural connectivity reflect on (amphibian) biodiversity patterns?

Landscape connectivity is a very recurrent theme in landscape ecology as it is considered pivotal for the long term conservation of any organism’s populations. Nevertheless, this complex concept is still surrounded by uncertainty and confusion, largely due to the separation between structural and functional connectivity. Amphibians are the most threatened vertebrates around the globe, in Europe mostly due to habitat alteration, and to their particular life cycle. Pond breeding amphibians are considered to be organised in metapopulations, enhancing the importance of landscape connectivity in this group of animals. We sampled the amphibian species present in two pond groups in Central Western Spain. We applied the graph theory framework to these two pond networks in order to determine the importance of each pond for the entire network connectivity. We related the pond importance for connectivity with the species richness present in each pond. We tested if connectivity (partially) determined the presence of the amphibian species sampled using logistic regression. The results show that the structural connectivity of the pond network impacts on the amphibian species richness pattern and that the importance of the pond for the connectivity of the network is an important factor for the presence of some species. Our results, hence, attest the importance of (structural) landscape connectivity determining the pattern of amphibian (functional) colonization in discrete ponds.     

The relative impact of forest patch and landscape attributes on black howler monkey populations in the fragmented Lacandona rainforest, Mexico

Land-use change is forcing many animal populations to inhabit forest patches in which different processes can threaten their survival. Some threatening processes are mainly related to forest patch characteristics, but others depend principally on the landscape spatial context. Thus, the impact of both patch and landscape spatial attributes needs to be assessed to have a better understanding of the habitat spatial attributes that constraint the maintenance of populations in fragmented landscapes. Here, we evaluated the relative effect of three patch-scale (i.e., patch size, shape, and isolation) and five landscape-scale metrics (i.e., forest cover, fragmentation, edge density, mean inter-patch isolation distance, and matrix permeability) on population composition and structure of black howler monkeys (Alouatta pigra) in the Lacandona rainforest, Mexico. We measured the landscape-scale metrics at two spatial scales: within 100 and 500 ha landscapes. Our findings revealed that howler monkeys were more strongly affected by local-scale metrics. Smaller and more isolated forest patches showed a lower number of individuals but at higher densities. Population density also tended to be positively associated to matrices with higher proportion of secondary forests and arboreal crops (i.e. with greater permeability), most probably because these matrices can offer supplementary foods. The immature-to-female ratio also increased with matrix permeability, shape complexity, and edge density; habitat characteristics that can increase landscape connectivity and sources availability. The prevention of habitat loss and isolation, and the increment of matrix permeability are therefore needed for the conservation of this endangered Neotropical mammal.