Ecological traps and species distribution models: a challenge for prioritizing areas of conservation importance

Species distribution models analyse how species use different types of habitats. Their spatial predictions are often used to prioritize areas for conservation. Individuals may, however, prefer settling in habitat types of low quality compared to other available habitats. This ecological trap phenomenon is usually studied in a small number of habitat patches and consequences at the landscape level are largely unknown. It is therefore often unclear whether the spatial pattern of habitat use is aligned with the behavioural decisions made by the individuals during habitat selection or reflects actual variation in the quality of different habitat types. As species distribution models analyse the pattern of occurrence in different habitats, there is a conservation interest in examining what their predictions mean in terms of habitat quality when ecological traps are operating. Previous work in Belgium showed that red-backed shrikes Lanius collurio are more attracted to newly available clear-cut habitat in plantation forests than to the traditionally used farmland habitat. We developed models with shrike distribution data and compared their predictions with spatial variation in shrike reproductive performance used as a proxy for habitat quality. Models accurately predicted shrike distribution and identified the preferred clear-cut patches as the most frequently used habitat, but reproductive performance was lower in clear-cut areas than in farmland. With human-induced rapid environmental changes, organisms may indeed be attracted to low-quality habitats and occupy them at high densities. Consequently, the predictions of statistical models based on occurrence records may not align with variation in significant population parameters for the maintenance of the species. When species expand their range to novel habitats, such models are useful to document the spatial distribution of the organisms, but data on population growth rates are worth collecting before using model predictions to guide the spatial prioritization of conservation actions.     

Species distribution models predict temporal but not spatial variation in forest growth

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree‐ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate‐based habitat suitability with volume measurements from ~50‐year‐old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree‐ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree‐ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as ?.31. We conclude that tree responses to projected climate change are highly site‐specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.     

Toward community predictions: Multi‐scale modelling of mountain breeding birds' habitat suitability,landscape preferences,and environmental drivers

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including “Bio11” (Mean Temperature of Coldest Quarter), and “Bio 4” (Temperature Seasonality), then in the focal variables including “Forest”, “Orchard”, and “Agriculture area” as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment.     

Species distribution models as a tool to estimate reproductive parameters: a case study with a passerine bird species

1.?Correlative species distribution models (SDMs) assess relationships between species distribution data and environmental features, to evaluate the environmental suitability (ES) of a given area for a species, by providing a measure of the probability of presence. If the output of SDMs represents the relationships between habitat features and species performance well, SDM results can be related also to other key parameters of populations, including reproductive parameters. To test this hypothesis, we evaluated whether SDM results can be used as a proxy of reproductive parameters (breeding output, territory size) in red-backed shrikes (Lanius collurio). 2.?The distribution of 726 shrike territories in Northern Italy was obtained through multiple focused surveys; for a subset of pairs, we also measured territory area and number of fledged juveniles. We used Maximum Entropy modelling to build a SDM on the basis of territory distribution. We used generalized least squares and spatial generalized mixed models to relate territory size and number of fledged juveniles to SDM suitability, while controlling for spatial autocorrelation. 3.?Species distribution models predicted shrike distribution very well. Territory size was negatively related to suitability estimated through SDM, while the number of fledglings significantly increased with the suitability of the territory. This was true also when SDM was built using only spatially and temporally independent data. 4.?Results show a clear relationship between ES estimated through presence-only SDMs and two key parameters related to species' reproduction, suggesting that suitability estimated by SDM, and habitat quality determining reproduction parameters in our model system, are correlated. Our study shows the potential use of SDMs to infer important fitness parameters; this information can have great importance in management and conservation.     

Determining habitat quality for species that demonstrate dynamic habitat selection

Determining habitat quality for wildlife populations requires relating a species' habitat to its survival and reproduction. Within a season, species occurrence and density can be disconnected from measures of habitat quality when resources are highly seasonal, unpredictable over time, and patchy. Here we establish an explicit link among dynamic selection of changing resources, spatio‐temporal species distributions, and fitness for predictive abundance and occurrence models that are used for short‐term water management and long‐term restoration planning. We used the wading bird distribution and evaluation models (WADEM) that estimate (1) daily changes in selection across resource gradients, (2) landscape abundance of flocks and individuals, (3) conspecific foraging aggregation, and (4) resource unit occurrence (at fixed 400 m cells) to quantify habitat quality and its consequences on reproduction for wetland indicator species. We linked maximum annual numbers of nests detected across the study area and nesting success of Great Egrets (Ardea alba), White Ibises (Eudocimus albus), and Wood Storks (Mycteria americana) over a 20‐year period to estimated daily dynamics of food resources produced by WADEM over a 7490 km² area. For all species, increases in predicted species abundance in March and high abundance in April were strongly linked to breeding responses. Great Egret nesting effort and success were higher when birds also showed greater conspecific foraging aggregation. Synthesis and applications: This study provides the first empirical evidence that dynamic habitat selection processes and distributions of wading birds over environmental gradients are linked with reproductive measures over periods of decades. Further, predictor variables at a variety of temporal (daily‐multiannual) resolutions and spatial (400 m to regional) scales effectively explained variation in ecological processes that change habitat quality. The process used here allows managers to develop short‐ and long‐term conservation strategies that (1) consider flexible behavioral patterns and (2) are robust to environmental variation over time.     

Habitat change and the scale of habitat selection: shifting gradients used by coexisting Arctic rodents

The conservation and understanding of biodiversity requires development and testing of models that illustrate how climate change and other anthropogenic effects alter habitat and its selection at different spatial scales. Models of fitness along a habitat gradient illustrate the connection between fine‐scale variation in fitness and the selection of habitat as discontinuous patches in the landscape. According to these models, climate change can increase fitness values of static habitats, shift the fitness value of habitat patches along underlying gradients of habitat quality, or alter both fitness and habitat quality. It should be possible to differentiate amongst these scenarios by associating differences in the abundance and distribution of species with metrics of habitat that document the gradient while controlling for changes in density at larger scales of analysis. Comparisons of habitat selection by two species of lemmings, over an interval of 15 years, are consistent with the theory. The pattern of habitat selection at the scale of wet versus dry tundra habitats changed through time. The change in habitat selection was reflected by different, but nevertheless density‐dependent, patterns of association with the structure and composition of habitat. Abundant collared lemmings abandoned stations where altered habitat characteristics caused a shift to new locations along the wet‐to‐dry gradient. The confirmation of scale‐dependent theory provides new insights into how one might begin to forecast future habitat selection under different scenarios of climate and habitat change.     

Effects of species' ecology on the accuracy of distribution models

In the face of accelerating biodiversity loss and limited data, species distribution models – which statistically capture and predict species’ occurrences based on environmental correlates – are increasingly used to inform conservation strategies. Additionally, distribution models and their fit provide insights on the broad‐scale environmental niche of species. To investigate whether the performance of such models varies with species’ ecological characteristics, we examined distribution models for 1329 bird species in southern and eastern Africa. The models were constructed at two spatial resolutions with both logistic and autologistic regression. Satellite‐derived environmental indices served as predictors, and model accuracy was assessed with three metrics: sensitivity, specificity and the area under the curve (AUC) of receiver operating characteristics plots. We then determined the relationship between each measure of accuracy and ten ecological species characteristics using generalised linear models. Among the ecological traits tested, species’ range size, migratory status, affinity for wetlands and endemism proved most influential on the performance of distribution models. The number of habitat types frequented (habitat tolerance), trophic rank, body mass, preferred habitat structure and association with sub‐resolution habitats also showed some effect. In contrast, conservation status made no significant impact. These findings did not differ from one spatial resolution to the next. Our analyses thus provide conservation scientists and resource managers with a rule of thumb that helps distinguish, on the basis of ecological traits, between species whose occurrence is reliably or less reliably predicted by distribution models. Reasonably accurate distribution models should, however, be attainable for most species, because the influence ecological traits bore on model performance was only limited. These results suggest that none of the ecological traits tested provides an obvious correlate for environmental niche breadth or intra‐specific niche differentiation.     

Maladaptive Habitat Use of a North American Woodpecker in Population Decline

Rapid anthropogenic habitat changes can lead to non‐ideal habitat use by animals, often resulting in lower fitness and population declines. An extreme case of use and fitness mismatch is an ecological trap where habitat quality cues are disjointed from the true quality of the habitat. Species primarily associated with anthropogenically altered habitat, such as red‐headed woodpeckers (Melanerpes erythrocephalus), may be especially vulnerable to use and fitness mismatch as they encounter novel environmental challenges. We investigated multi‐scale habitat use and nesting success of red‐headed woodpeckers to assess their vulnerability to mismatches between use and fitness as a result of non‐ideal habitat use across multiple scales. We found that habitat characteristics that promote feeding potential such as canopy openness and greater dead limb length appeared paramount and were consistent in use across several spatial scales although reproductive fitness suffered. This contrasts with the assumption that habitat use by nesting birds should instead favor predation avoidance at smaller scales to improve reproductive fitness and suggests that maladaptive, food‐based habitat use by red‐headed woodpeckers in southern Ontario may result in ecological traps for the species. Whether due to poor habitat choices or costly ones in favor of feeding potential, it is vital to consider this behavior in conservation and management plans for this and similar species. We suggest multi‐scale habitat use studies that consider fitness outcomes are critical for species‐at‐risk in human‐modified landscapes.     

Habitat selection of breeding riparian birds in an urban environment: untangling the relative importance of biophysical elements and spatial scale

Aim Urbanization is a leading threat to global biodiversity, yet little is known about how the spatial arrangement and composition of biophysical elements – buildings and vegetation – within a metropolitan area influence habitat selection. Here, we ask: what is the relative importance of the structure and composition of these elements on bird species across multiple spatial scales? Location The temperate metropolitan area of Cincinnati, Ohio, USA. Methods We surveyed breeding birds on 71 plots along an urban gradient. We modelled relative density for 48 bird species in relation to local woody vegetation composition and structure and to tree cover, grass cover and building density within 50–1000 m of each plot. We used an information‐theoretic approach to compare models and variables. Results At the proximate scale, native tree and understory stem frequency were the most important vegetation variables explaining bird distributions. Species’ responses to landscape biophysical features and spatial scales varied. Most native species responded positively to vegetation measures and negatively to building density. Models combining both local vegetation and landscape information represented best or competitive models for the majority of species, while models containing only local vegetation characteristics were rarely competitive. Smaller spatial scales (≤ 500 m) were most important for 36 species, and eight species had best models at larger scales (> 500 m); however, several species had competitive models across multiple scales. Main conclusions Habitat selection by birds within the urban matrix is the result of a combination of factors operating at both proximate and broader spatial scales. Efforts to manage and design urban areas to benefit native birds require both fine‐scale (e.g., individual landowners and landscape design) and larger landscape actions (e.g., regional comprehensive planning).     

Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis

Scaling is a key process in modelling approaches since it allows for translating information from one scale to another. However, the success of this procedure may depend on ‘source’ and ‘target’ scales, but also on the biogeographic/ecological context of the study area. We aimed to quantify the performance and success of scaling species distribution model (SDM) predictions across spatial resolution and extent along a biogeographic gradient using the Iberian mole as study case. We ran separate MaxEnt models at two extents (national and regional) using independent datasets (species locations and environmental predictors) collected at 10 km and 50 m resolutions respectively. Model performance and success of scaling SDMs were quantified on the basis of accuracy measures and spatial predictions. Complementarily, we calculated marginality and tolerance as indicators of habitat availability and niche truncation along the biogeographic gradient. Model performance increased with resolution and extent, as well as from north to south (mainly for high resolution models). When regional models were validated at different scales, their performance reduced severely, particularly in the case of coarse resolution models (some of them performed worse than random). However, when the 10 km‐national model was downscaled within regions, it performed better (AUC_test: 0.82, 0.85 and 0.55 respectively for Galicia, Madrid and Granada) than models specifically calibrated within each region at 10 km (0.47, 0.65, 0.44). Indeed, it also had a better accuracy when projected at 50 m (0.77, 0.91, 0.79) than models fitted at that resolution (0.62, 0.83, 0.96) in two of the three cases. The success of scaling model predictions decreased along the biogeographic gradient, being these differences associated to niche truncation. Models representing non‐truncated niches were more successfully scaled across resolutions and extents (particularly in areas not offering all possible habitats for species), which has important implications for SDM applications.     

Land use changes affect distributional patterns of desert birds in the Baja California peninsula, Mexico

Reliable plans for desert bird conservation will depend on accurate prediction of habitat change effects on their distribution and abundance patterns. Predictive models can help highlight relationships between human‐related and other environmental variables and the presence of desert bird species. Presence/absence of 30 desert bird species of Baja California peninsula was modelled on the basis of explanatory variables taken from the field, maps, and digital imagery. Generalized linear models were fit to each bird species using both variables representing human activity and other environmental factors as predictors that might influence distribution. Probability of species presence was used as a habitat suitability index to evaluate the effect of human activity when the model contained a significant human activity variable. No differences were found in bird species richness between natural sites and those transformed by agriculture or urbanization. Of 59 bird species recorded in surveys, 34% were positively or negatively associated with human‐transformed habitats. Fourteen species seem to benefit from transformation of natural vegetation by agriculture or urbanization, while six were negatively affected. Sensitivity analyses of final models indicated all were robust. Results suggest that the occurrence of a large percentage of bird species inhabiting scrub habitats is sensitive to human habitat transformation. This finding has important conservation implications at regional scale as fragmentation and conversion of desert ecosystems into agricultural and urban areas affect the distribution of species that are highly selective for scrub habitat. Land use and anthropogenic activities seem to change ecological patterns at large spatial scales, but other factors could drive species richness distribution too (i.e. individual species response, species–energy relationships). The spatial modelling approach at regional scale used in this study can be useful for designing natural resource management plans in the Sonoran desert scrub.     

The nest predator community of grassland birds responds to agroecosystem habitat at multiple scales

Nest predation is the leading cause of reproductive failure for grassland birds of conservation concern. Understanding variation in nest predation rates is complicated by the diverse assemblage of species known to prey on nests. As part of a long‐term study of grassland bird ecology, we monitored populations of predators known to prey on grassland bird nests. We used information theoretic approach to examine the predator community's association with habitat at multiple scales, including local vegetation structure of grassland patches, spatial attributes of grassland patches (size and shape), and landscape composition surrounding grassland patches (land cover within 400 and 1600 m). Our results confirmed that nest predators respond to habitat at multiple scales and different predator species respond to habitat in different ways. The most informative habitat models we selected included variability in local vegetation (CV in the density of forbs), local patch (area and edge‐to‐interior ratio), and landscape within a 1600 m buffer around grasslands (percent of land covered by human structures and development). As a separate question, we asked if models that incorporated information from multiple scales simultaneously might improve the ability to explain variation in the predator community. Multi‐ scale models were not consistently superior to models derived from variables focused at a single spatial scale. Our results suggest that minimizing human development on and surrounding conservation land and the management of the vegetation structure on grassland fragments both may benefit grassland birds by decreasing the risk of nest predation.     

Updating bird species distribution at large spatial scales: applications of habitat modelling to data from long-term monitoring programs

Mapping of species distributions at large spatial scales has been often based on the representation of gathered observations in a general grid atlas framework. More recently, subsampling and subsequent interpolation or habitat spatial modelling techniques have been incorporated in these projects to allow more detailed species mapping. Here, we explore the usefulness of data from long-term monitoring (LTM) projects, primarily aimed at estimating trends in species abundance and collected at shorter time intervals (usually yearly) than atlas data, to develop predictive habitat models. We modelled habitat occupancy for 99 species using a bird LTM program and evaluated the predictive accuracy of these models using independent data from a contemporary and comprehensive breeding bird atlas project from the same region. Habitat models from LTM data using generalized linear modelling were significant for all the species and generally showed a high predictive power, albeit lower than that from atlas models. Sample size and species range size and niche breadth were the most important factors behind variability in model predictive accuracy, whereas the spatial distribution of sampling units at a given sample size had minor effects. Although predictive accuracy of habitat modelling was strongly species dependent, increases in sample size and, secondarily, a better spatial distribution of sampling units should lead to more powerful predictive distribution models. We suggest that data from LTM programs, now established in a large number of countries, has the potential for being a major source of good quality data suitable for the estimation and regularly update of distributions at large spatial scales for a number of species.     

Dynamic occupancy models reveal within‐breeding season movement up a habitat quality gradient by a migratory songbird

The timing of settlement decisions likely influences the quality of breeding site choices.This is particularly the case in migratory birds, because the conditions that enhance breeding success are often not apparent upon arrival after migration. A strategy that addresses this problem is to adjust settlement decisions when reliable information becomes available. We used a new indirect method – dynamic site occupancy modeling – to estimate apparent movement of black‐throated blue warblers Dendroica caerulescens among sites within a breeding season. Because individuals should disperse to sites that maximize their fitness, we hypothesized that warblers would move up a habitat quality gradient when opportunities arose. For our study species, that would involve moving into sites with greater shrub density and at higher elevation within northern hardwoods forest, as these two features are positively correlated with reproduction and apparent survival in this species. Although the probability of site occupancy in our study landscape remained consistent throughout the breeding season (range: 0.66–0.69), occupancy models revealed substantial support for apparent movement of individuals within the breeding season. The mean probability of emigration from a point count site was 0.21 (±0.03 SE), and the mean probability of immigration to a site not previously occupied was 0.51 (±0.05 SE). The spatial distribution of this movement was a function of habitat quality. A portion of the black‐throated blue warbler population appears to arrive on the breeding grounds and settle initially in sub‐optimal habitat, moving subsequently into high quality densely shrubbed habitat at higher elevations. This modeling approach provides a new means to test hypotheses about habitat selection and movement by using presence–non‐detection data.     

Modelling the distribution of a threatened habitat: the California sage scrub

Aim Using predictive species distribution and ecological niche modelling our objectives are: (1) to identify important climatic drivers of distribution at regional scales of a locally complex and dynamic system – California sage scrub; (2) to map suitable sage scrub habitat in California; and (3) to distinguish between bioclimatic niches of floristic groups within sage scrub to assess the conservation significance of analysing such species groups. Location Coastal mediterranean‐type shrublands of southern and central California. Methods Using point localities from georeferenced herbarium records, we modelled the potential distribution and bioclimatic envelopes of 14 characteristic sage scrub species and three floristic groups (south‐coastal, coastal–interior disjunct and broadly distributed species) based upon current climate conditions. Maxent was used to map climatically suitable habitat, while principal components analysis followed by canonical discriminant analysis were used to distinguish between floristic groups and visualize species and group distributions in multivariate ecological space. Results Geographical distribution patterns of individual species were mirrored in the habitat suitability maps of floristic groups, notably the disjunct distribution of the coastal–interior species. Overlap in the distributions of floristic groups was evident in both geographical and multivariate niche space; however, discriminant analysis confirmed the separability of floristic groups based on bioclimatic variables. Higher performance of floristic group models compared with sage scrub as a whole suggests that groups have differing climate requirements for habitat suitability at regional scales and that breaking sage scrub into floristic groups improves the discrimination between climatically suitable and unsuitable habitat. Main conclusions The finding that presence‐only data and climatic variables can produce useful information on habitat suitability of California sage scrub species and floristic groups at a regional scale has important implications for ongoing efforts of habitat restoration for sage scrub. In addition, modelling at a group level provides important information about the differences in climatic niches within California sage scrub. Finally, the high performance of our floristic group models highlights the potential a community‐level modelling approach holds for investigating plant distribution patterns.     

Does bird community structure vary with landscape patchiness? A Chihuahuan Desert perspective

During the springs of 1995–1997, we studied birds and landscapes at 70 sites in the Chihuahuan Desert to assess relations between bird community structure and landscape patchiness. Within each of two spatial extents (1‐km and 2‐km‐radius areas centered on each site), we measured the number of patches of individual land‐cover types and the total number of patches of all land‐cover types. Mean bird richness, and the mean abundance and probability of occurrence of most bird species were significantly correlated with one or more of these variables. Contrary to evidence from other systems, positive association with landscape patchiness did not increase with the degree to which species were habitat generalists, was not negatively related to body size, and did not differ between neotropical migrants and nonmigrants. For the communities’ primary constituent species as a group, the strength of positive and negative associations with patchiness did not differ between landscape extents. Within the 1‐km but not the 2‐km extent, habitat specialists were more positively and negatively associated with patchiness than were habitat generalists. In general, however, neither habitat breadth, body size, nor migratory status seemed to be responsible for associations with landscape patchiness. Mean richness, and the mean abundance and probability of occurrence of most species were significantly correlated with patchiness within one or both extents, and patchiness of all of the most extensive land‐cover types was influential. The simplest explanation for most of the bird‐patchiness relations we found is that the associations reflected species‐specific habitat needs. Through effects on avian richness, abundance, and occurrence, landscape patchiness affected bird community structure. A more complete understanding of the effects of landscape patchiness on bird community structure is likely to emerge when ecologists study the patchiness of major land‐cover types at various spatial extents.     

Experimental evidence of a link between breeding conditions and the decision to breed or to help in a colonial cooperative bird

In many species mature individuals delay independent reproduction and may help others to reproduce. This behaviour is often explained through ecological constraints, although recently attention has also been paid to the variation in habitat quality. If the quality of vacant habitat influences the fitness trade-off between delaying reproduction and breeding independently, individuals should delay reproduction when conditions for breeding are poor. Yet, no study has experimentally manipulated habitat quality or the conditions experienced during the breeding period to test this assertion conclusively. We report results from an experiment conducted on a colonial cooperative bird with no territory constraints on reproduction. We artificially improved breeding conditions in several colonies of sociable weavers, Philetairus socius, through the provision of an easily obtainable and unlimited supply of food. We provide experimental evidence showing that under enhanced conditions some individuals reduce their age at first reproduction, a greater proportion of colony members engage in independent breeding and proportionally fewer birds act as helpers. Hence, these results also provide evidence for a direct influence of reproductive costs on life-history decisions such as age at first reproduction and breeding and helping behaviours.     

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.     

Development and field validation of a regional,management‐scale habitat model: A koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional‐scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently‐collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2‐km spatial filter and by modeling separately two subregions separated by the 500‐m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground‐truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground‐truth sites. Similarly, a site habitat quality index at ground‐truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site‐based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field‐validated models of similar resolution would assist in guiding management of conservation‐dependent species.     

Impact of spatial variation of a crucial prey,the molecricket,on hoopoe territory occupancy and reproduction

Direct benefits accrued from securing a territory of sufficient quality are important determinants of individual fitness and population persistence. Food supply is one of the main factors of animal territory quality, with spatial and temporal variation in prey availability largely dictating reproductive output and thus population dynamics. In a Swiss hoopoe population, molecrickets Gryllotalpa gryllotalpa, the most profitable prey locally, can constitute most of the food biomass delivered to chicks by parents. We first investigated the impact of molecricket prey on hoopoes' fitness‐related traits by quantifying the spatial variation in the food allocation pattern of both male and female parents to chicks across the whole population range; and second, analysed the impact of this prey on current reproduction and, using a 11 yr dataset, on the temporal occupancy rate of each territory. We found considerable but spatially repeatable variation, over the years, of molecricket biomass in the diet provisioned to chicks. This spatial heterogeneity in chicks' diet composition was mirrored both in the history of territory occupancy (2002–2012) and in current reproductive success (2012). Territories with a greater biomass of molecrickets in chicks' diet produced more fledglings in better body condition. Yet, these effects on current reproduction were exclusively demonstrated for male parents, corroborating that paternal provisioning patterns play a predominant role in hoopoe reproductive success. This study demonstrates how a single, very profitable prey species might affect spatial variation in territory settlement and individual reproductive success in a regionally endangered bird species, with potential consequences for its population dynamics and persistence.