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Direct road mortality and the barrier effect of roads are typically identified as one of the greatest threats to wildlife. In addition, collisions with large mammals are also a threat to human safety and represent an economic cost to society. We documented and explored the effects of animal-vehicle crashes on human safety in São Paulo State, Brazil. We estimated the costs of these crashes to society, and we summarized the legal perspectives. On average, the Military Highway Police of São Paulo reported 2,611 animal-vehicle crashes per year (3.3% of total crashes), and 18.5% of these resulted in human injuries or fatalities. The total annual cost to society was estimated at R$ 56,550,642 (US $ 25,144,794). The average cost for an animal-vehicle crash, regardless of whether human injuries and fatalities occurred, was R$ 21,656 (US $ 9,629). The Brazilian legal system overwhelmingly (91.7% of the cases) holds the road administrator liable for animal-vehicle collisions, both with wild and domestic species. On average, road administrators spent R$ 2,463,380 (US $ 1,005,051) per year compensating victims. The logical conclusion is that the Brazilian legal system expects road administrators to keep animals, both wild and domestic species, off the road. We suggest an improved coordination between the laws that relate to animal-vehicle collisions and human safety, and the process for environmental licenses that focusses on reducing collisions with wildlife and providing habitat connectivity. In addition, we suggest better management practices, raising awareness and social change with regard to abandoned domesticated animals including horses, cattle, and dogs. This should ultimately result in a road system with improved human safety, reduced unnatural mortality for both domestic and wild animal species, safe crossing opportunities for wildlife, and reduced monetary costs to society.

The broad negative consequences of habitat degradation on biodiversity have been studied, but the complex effects of natural–agricultural landscape matrices remain poorly understood. Here we used stable carbon and nitrogen isotopes to detect changes in mammal resource and habitat use and trophic structure between preserved areas and human-modified landscapes (HMLs) in a biodiversity hot spot in South America. We classified mammals into trophic guilds and compared resource use (in terms of C₃- and C₄-derived carbon), isotopic niches, and trophic structure across the 2 systems. In HMLs, approximately one-third of individuals fed exclusively on items from the agricultural matrix (C₄), while in preserved areas, ∼68% depended on forest remnant resources (C₃). Herbivores, omnivores, and carnivores were the guilds that most incorporated C₄ carbon in HMLs. Frugivores maintained the same resource use between systems (C₃ resources), while insectivores showed no significant difference. All guilds in HMLs except insectivores presented larger isotopic niches than those in preserved areas. We observed a complex trophic structure in preserved areas, with increasing δ15N values from herbivores to insectivores and carnivores, differing from that in HMLs. This difference is partially explained by species loss and turnover and mainly by the behavioral plasticity of resilient species that use nitrogen-enriched food items. We concluded that the landscape cannot be seen as a habitat/nonhabitat dichotomy because the agricultural landscape matrix in HMLs provides mammal habitat and opportunities for food acquisition. Thus, favorable management of the agricultural matrix and slowing the conversion of forests to agriculture are important for conservation in this region.

The jaguar, Panthera onca, is a top predator with the extant population found within the Brazilian Caatinga biome now known to be on the brink of extinction. Designing new conservation units and potential corridors are therefore crucial for the long-term survival of the species within the Caatinga biome. Thus, our aims were: 1) to recognize suitable areas for jaguar occurrence, 2) to delineate areas for jaguar conservation (PJCUs), 3) to design corridors among priority areas, and 4) to prioritize PJCUs. A total of 62 points records of jaguar occurrence and 10 potential predictors were analyzed in a GIS environment. A predictive distributional map was obtained using Species Distribution Modeling (SDM) as performed by the Maximum Entropy (Maxent) algorithm. Areas equal to or higher than the median suitability value of 0.595 were selected as of high suitability for jaguar occurrence and named as Priority Jaguar Conservation Units (PJCU). Ten PJCUs with sizes varying from 23.6 km2 to 4,311.0 km2 were identified. Afterwards, we combined the response curve, as generated by SDM, and expert opinions to create a permeability matrix and to identify least cost corridors and buffer zones between each PJCU pair. Connectivity corridors and buffer zone for jaguar movement included an area of 8.884,26 km2 and the total corridor length is about 160.94 km. Prioritizing criteria indicated the PJCU representing c.a. 68.61% of the total PJCU area (PJCU # 1) as of high priority for conservation and connectivity with others PJCUs (PJCUs # 4, 5 and 7) desirable for the long term survival of the species. In conclusion, by using the jaguar as a focal species and combining SDM and expert opinion we were able to create a valid framework for practical conservation actions at the Caatinga biome. The same approach could be used for the conservation of other carnivores.

A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma's habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species' occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental policies and land use planning in São Paulo State, Brazil.

Understanding the distribution patterns of threatened species is central to conservation. The Amazonian distribution of the northern tiger cat (N-tiger cat, Leopardus tigrinus ) and its interspecific relationship with the ocelot, its potential intraguild killer, are intriguing. Here, we combined presence/absence records with species distribution models (SDMs) to determine N-tiger cat occurrence in the Amazon. We also modeled ocelot density from 46 published estimates. The N-tiger cat’s presence in the Amazon was negatively influenced by ocelot density and net primary productivity and positively influenced by savannas and precipitation in the driest month. The best-fitting model predicted highly patchy N-tiger cat occurrence over an area of 236,238.67 km 2 , almost exclusively in savanna enclaves. Additionally, 312,348 camera trap-days at 49 sites in the Amazon revealed no N-tiger cats. The ocelot densities were significantly higher in areas with denser vegetation cover and warmer habitats, with predicted densities ≥ 0.6 ind/km 2 throughout most of the biome. The lowest ocelot densities (≤ 0.06 ind/km 2 ) were observed along the predicted range of N-tiger cats. Our findings highlight that the N-tiger cat’s presence in the Amazon is restricted to savannas and highly influenced by ocelot density, emphasizing the importance of including species interactions in SDMs.

Despite major advances in mammal research, there are knowledge gaps regarding distribution, composition, and the functional role of mammal species within agricultural and fragmented landscapes. Also, there is a lack of knowledge about which factors influence mammal assemblages within agricultural ecosystems. Therefore, this study aimed to estimate the contribution of forest cover, functional connectivity, drainage, and amount of sugar cane toward explaining the functional diversity of terrestrial mammals. We made an inventory of terrestrial mammals in an agricultural and fragmented landscape in an Atlantic Forest-Cerrado ecotone in southeastern Brazil, assessed the functional diversity of mammal assemblages, and proposed conservation strategies at the landscape level. Data collection occurred from September/2011 to August/2012 through a combination of complementary methods: active search; trapping stations; collection of fecal samples, which were identified by hair cuticle and fecal DNA analysis; and data from the literature. Functional diversity (FD) was calculated using a set of ecological traits including body mass, locomotion form, behavioral and dietary traits, and the environmental sensitivity of species. Akaike information criterion was used to compare generalized linear models between FD values and landscape metrics. Our results reveal a surprising insight about the role exerted by agricultural and fragmented landscapes, which still sustain impressively high biodiversity levels and a meaningful amount of ecological functions, indicating some resistance of species to pressure from the agricultural matrix and advancing urbanization. The amount of ecological functions performed by mammal species within agricultural and fragmented landscapes was similar to pristine areas and more preserved landscapes. Functional connectivity (amount of area assessed for species able to cross 200 m of matrix) was the most plausible model (wAICc = 0.873). Thus, we concluded that improving functional connectivity guarantees high FD values, and we demonstrate the importance of maintaining and restoring structural connections between fragment patches within these landscapes for species conservation and the maintenance of populations over time.

The expansion of human activity forces species to co-exist with people in human-modified landscapes (HMLs). However, living in HMLs demands behavioral adaptations, and the proximity between wildlife and people heightens human–wildlife conflicts. Capybara (Hydrochoerus hydrochaeris) is a thriving rodent species in HMLs in Brazil and as such, is involved in human–wildlife conflicts, such as vehicle collisions and transmission of Brazilian spotted fever (BSF). Despite their public importance, the effects of HMLs on capybara movement behavior have never been investigated. Our study aimed to investigate changes in home range, ranging pattern, and activity, for capybaras in six HMLs and two natural landscapes (NLs) by monitoring capybaras with GPS collars. We found home ranges 2.43 times greater in NLs than in HMLs and differences in ranging pattern in HMLs. Capybaras tended to be more nocturnal and move shorter distances across HMLs than NLs. Our results confirm the impacts of the HMLs altering capybara movement. The aggregation of capybaras in very small home ranges might imply on greater risks of tick infestations. In addition, capybara–vehicle collision may be increased during capybaras' nocturnal activity. Therefore, we recommend that transportation agencies avoid the construction of transportation infrastructures (roads, railways, airstrips) in capybaras' home ranges, which should be of restricted access to people in BSF endemic areas.

Assessment of the suitability of anthropogenic landscapes for wildlife species is crucial for setting priorities for biodiversity conservation. This study aimed to analyse the environmental suitability of a highly fragmented region of the Brazilian Atlantic Forest, one of the world's 25 recognized biodiversity hotspots, for forest bird species. Eight forest bird species were selected for the analyses, based on point counts (n = 122) conducted in April–September 2006 and January–March 2009. Six additional variables (landscape diversity, distance from forest and streams, aspect, elevation and slope) were modelled in Maxent for (1) actual and (2) simulated land cover, based on the forest expansion required by existing Brazilian forest legislation. Models were evaluated by bootstrap or jackknife methods and their performance was assessed by AUC, omission error, binomial probability or p value. All predictive models were statistically significant, with high AUC values and low omission errors. A small proportion of the actual landscape (24.41 ± 6.31%) was suitable for forest bird species. The simulated landscapes lead to an increase of c.30% in total suitable areas. In average, models predicted a small increase (23.69 ± 6.95%) in the area of suitable native forest for bird species. Being close to forest increased the environmental suitability of landscapes for all bird species; landscape diversity was also a significant factor for some species. In conclusion, this study demonstrates that species distribution modelling (SDM) successfully predicted bird distribution across a heterogeneous landscape at fine spatial resolution, as all models were biologically relevant and statistically significant. The use of landscape variables as predictors contributed significantly to the results, particularly for species distributions over small extents and at fine scales. This is the first study to evaluate the environmental suitability of the remaining Brazilian Atlantic Forest for bird species in an agricultural landscape, and provides important additional data for regional environmental planning.

Transdisciplinary projects are fundamental to a more effective and just conservation, but their application and coherent framing present challenges, since their nature is to bring together different epistemological backgrounds and world views. This paper identifies the possibilities offered by stakeholder mapping as a tool for generating common understandings in transdisciplinary conservation research projects. Lessons are drawn from experiential learning through the case of jaguar conservation in the Brazilian Atlantic Forest (BAF). Stakeholder mapping proved to be an essential diagnostic tool that generated an overview of the material context of human–jaguar interactions in the BAF to stakeholders engaged in the project. The process and overview drew attention to gaps in stakeholder knowledge that need to be addressed to enhance conviviality between humans and jaguars in fragmented landscapes. Recognizing these knowledge gaps assists in the production of methodologies that can effectively encompass different social groups, and increase all parties' perceptions of the legitimacy of conservation activities. We argue that, due to its collective nature, stakeholder mapping can foster mutual learning and deeper communication in the context of divergent framings of complex nature conservation problems, such as in jaguar conservation. This article aims at identifying limits and possibilities of stakeholder mapping as a tool for generating common understandings in transdisciplinary research projects in conservation. The lessons are drawn from experiential learning trough the study case of Jaguar conservation in the Brazilian Atlantic Forest.

The jaguar Panthera onca, a threatened species in Brazil, is losing suitable habitat as a result of agricultural expansion and other forms of land conversion, especially in the Cerrado biome. In the current context of habitat loss and fragmentation, a network of protected areas is paramount for the conservation of this species. We aimed to identify jaguar conservation units in the Cerrado, and propose a ranking of priority areas for the species in this region. We used the maximum entropy algorithm to model habitat suitability for the jaguar in the Cerrado, with nine uncorrelated environmental variables and 106 non-autocorrelated presence-only records. We prioritized regions, using Zonation, and ranked jaguar conservation units according to their area, proximity to strictly protected areas, jaguar presence, and potential for connectivity. Circa 30% of the Cerrado is suitable for the jaguar. The most important variables affecting jaguar distribution are mean rainfall and land cover, with a high probability of jaguar presence in forest and savannah. We selected 31 high-priority jaguar conservation units, covering c. 174,825 km2 (8.5%) of the Cerrado. We emphasize the need for new protected areas and the promotion of sustainable development, as only 0.4% of the Cerrado (8,345 km2) has high environmental suitability for jaguars and < 1% of the area covered by jaguar conservation units falls within protected areas. Most jaguar conservation units identified here are relevant for habitat connectivity in Brazil, given their proximity to other critical areas for jaguar conservation in the Caatinga and the Amazon.