Aim Our objective was to identify the distribution of the endangered golden-cheeked warbler (Setophaga chrysoparia) in fragmented oak–juniper woodlands by applying a geoadditive semiparametric occupancy model to better assist decision-makers in identifying suitable habitat across the species breeding range on which conservation or mitigation activities can be focused and thus prioritize management and conservation planning. Location Texas, USA. Methods We used repeated double-observer detection/non-detection surveys of randomly selected (n = 287) patches of potential habitat to evaluate warbler patch-scale presence across the species breeding range. We used a geoadditive semiparametric occupancy model with remotely sensed habitat metrics (patch size and landscape composition) to predict patch-scale occupancy of golden-cheeked warblers in the fragmented oak–juniper woodlands of central Texas, USA. Results Our spatially explicit model indicated that golden-cheeked warbler patch occupancy declined from south to north within the breeding range concomitant with reductions in the availability of large habitat patches. We found that 59% of woodland patches, primarily in the northern and central portions of the warbler’s range, were predicted to have occupancy probabilities ≤0.10 with only 3% of patches predicted to have occupancy probabilities >0.90. Our model exhibited high prediction accuracy (area under curve = 0.91) when validated using independently collected warbler occurrence data. Main conclusions We have identified a distinct spatial occurrence gradient for golden-cheeked warblers as well as a relationship between two measurable landscape characteristics. Because habitat-occupancy relationships were key drivers of our model, our results can be used to identify potential areas where conservation actions supporting habitat mitigation can occur and identify areas where conservation of future potential habitat is possible. Additionally, our results can be used to focus resources on maintenance and creation of patches that are more likely to harbour viable local warbler populations.

Population abundance estimates using predictive models are important for describing habitat use and responses to population‐level impacts, evaluating conservation status of a species, and for establishing monitoring programs. The golden‐cheeked warbler (Setophaga chrysoparia) is a neotropical migratory bird that was listed as federally endangered in 1990 because of threats related to loss and fragmentation of its woodland habitat. Since listing, abundance estimates for the species have mainly relied on localized population studies on public lands and qualitative‐based methods. Our goal was to estimate breeding population size of male warblers using a predictive model based on metrics for patches of woodland habitat throughout the species' breeding range. We first conducted occupancy surveys to determine range‐wide distribution. We then conducted standard point‐count surveys on a subset of the initial sampling locations to estimate density of males. Mean observed patch‐specific density was 0.23 males/ha (95% CI = 0.197–0.252, n = 301). We modeled the relationship between patch‐specific density of males and woodland patch characteristics (size and landscape composition) and predicted patch occupancy. The probability of patch occupancy, derived from a model that used patch size and landscape composition as predictor variables while addressing effects of spatial relatedness, best predicted patch‐specific density. We predicted patch‐specific densities as a function of occupancy probability and estimated abundance of male warblers across 63,616 woodland patches accounting for 1.678 million ha of potential warbler habitat. Using a Monte Carlo simulation, our approach yielded a range‐wide male warbler population estimate of 263,339 (95% CI: 223,927–302,620). Our results provide the first abundance estimate using habitat and count data from a sampling design focused on range‐wide inference. Managers can use the resulting model as a tool to support conservation planning and guide recovery efforts. © 2012 The Wildlife Society.

The conservation and management of natural resources operates in social-ecological systems in which resource users are embedded in social and environmental contexts that influence their management decisions. Characterizing social networks of resource users can be used to inform understanding of social influences on decision making, and social network analysis (SNA) has emerged as a useful technique to explore these relationships. We synthesized how SNA has been used in 85 studies of natural resource management. We considered how social networks and social processes (e.g., interactions between individuals) influence each other and in turn influence social outcomes (e.g., decisions or actions) that affect environmental outcomes (e.g., improved condition). Descriptive methods were used in 58% of the studies to characterize social processes, and 42% of the studies compared multiple networks or multiple points in time to assess social or environmental outcomes. In 4 studies, authors assessed network interventions intended to affect social processes or environmental outcomes. The heterogeneity in case studies, methods, and analyses preclude general lessons. Thus, to structure and further learning about the role of social networks in achieving environmental outcomes, we created a typology that deconstructs social processes, social outcomes, and environmental outcomes into themes and options of social and ecological measures within each. We suggest shifts in research foci toward intervention studies to aid in understanding causality and inform the design of conservation initiatives. There is a need to develop clearer justification and guidance around the proliferation of network measures. The use of SNA in natural resource management is expanding rapidly; thus, now is the time for the conservation community to build a more rigorous evidence base to demonstrate the extent to which social networks can play a role in achieving desired social and environmental outcomes.

There is a growing recognition of the contribution that privately-owned land makes to conservation efforts, and governments are increasingly counting privately protected areas (PPAs) towards their international conservation commitments. The public availability of spatial data on countries' conservation estates is important for broad-scale conservation planning and monitoring and for evaluating progress towards targets. Yet there has been limited consideration of how PPA data is reported to national and international protected area databases, particularly whether such reporting is transparent and fair (i.e., equitable) to the landholders involved. Here we consider PPA reporting procedures from three countries with high numbers of PPAs-Australia, South Africa, and the United States-illustrating the diversity within and between countries regarding what data is reported and the transparency with which it is reported. Noting a potential tension between landholder preferences for privacy and security of their property information and the benefit of sharing this information for broader conservation efforts, we identify the need to consider equity in PPA reporting processes. Unpacking potential considerations and tensions into distributional, procedural, and recognitional dimensions of equity, we propose a series of broad principles to foster transparent and fair reporting. Our approach for navigating the complexity and context-dependency of equity considerations will help strengthen PPA reporting and facilitate the transparent integration of PPAs into broader conservation efforts.

ABSTRACT1. The Leon River drainage, located in the Brazos River basin, has not been extensively surveyed for freshwater mussels (Family Unionidae). This is problematic given that three state-threatened species, Quadrula houstonensis, Quadrula mitchelli, and Truncilla macrodon, have historically occurred in this drainage and two are now candidates for protection under the US Endangered Species Act.2. Mussels were sampled qualitatively at 44 sites in the summer and fall of 2011 to determine whether these species were still extant in the Leon River. The distributions and abundances of species at present considered common were also examined. Shell length data were assessed to determine the overall viability of the mussel fauna within the Leon River drainage.3. In total, 2081 live mussels were collected representing 12 species, including the federal candidate species Quadrula houstonensis, but Lampsilis hydiana, Quadrula mitchelli and Truncilla macrodon were not collected. Overall mussel abundance and species richness was low and community composition was highly fragmented with riverine species largely occurring in the middle portion of the Leon River. There was evidence that population recruitment is occurring, but only for a few species.4. River impoundment, inadequate instream flows, and agricultural practices are probable causes of the changes in mussel species composition. Further studies are needed to evaluate the impacts of reservoir releases on mussel persistence within this basin and in areas where droughts and low stream flow are commonplace. More information is needed on how agricultural practices affect mussel communities; the information that is currently available does little in the way of identifying factors that can be managed at site or reach scales. Studies that address these knowledge gaps will help resource managers to design more effective strategies to protect mussel populations within and outside this basin.