Sea-level rise threatens both human communities and vulnerable species within coastal areas. Joint spatial planning can allow conservation and social resiliency goals to work in synergy. We present a case study integrating distribution information of a threatened saltmarsh bird, the eastern black rail (Laterallus jamaicensis jamaicensis), with social information to facilitate such joint planning. We constructed a distribution model for the species within an urbanizing coastal region (New Jersey, USA) and integrated this with publicly available parcel and protected area data to summarize ownership patterns. We estimated that c. 0.3–2.8% (c. 260–2200 ha) of available saltmarsh is occupied by eastern black rail, most of which is publicly owned (79%). Privately owned saltmarsh was spread across nearly 5000 individual parcels, 10% of which contained areas with the highest likelihood of rail presence according to our model (top quartile of predicted occupancy probabilities). Compared with all privately owned saltmarsh, parcels with probable rail habitat were larger (median: 5 versus 2 ha), contained more marsh (87% versus 59%) and were less economically valuable (US$11 200 versus US$36 100). Our approach of integrating species distributions with landownership data helps clarify trade-offs and synergies in species conservation and coastal resiliency planning.

Species distribution models (SDMs) are statistical tools used to develop continuous predictions of species occurrence. ‘Integrated SDMs’ (ISDMs) are an elaboration of this approach with potential advantages that allow for the dual use of opportunistically collected presence-only data and site-occupancy data from planned surveys. These models also account for survey bias and imperfect detection through the use of a hierarchical modelling framework that separately estimates the species–environment response and detection process. This is particularly helpful for conservation applications and predictions for rare species, where data are often limited and prediction errors may have significant management consequences. Despite this potential importance, ISDMs remain largely untested under a variety of scenarios. We performed an exploration of key modelling decisions and assumptions on an ISDM using the endangered Baird’s tapir (Tapirus bairdii) as a test species. We found that site area had the strongest effect on the magnitude of population estimates and underlying intensity surface and was driven by estimates of model intercepts. Selecting a site area that accounted for the individual movements of the species within an average home range led to population estimates that coincided with expert estimates. ISDMs that do not account for the individual movements of species will likely lead to less accurate estimates of species intensity (number of individuals per unit area) and thus overall population estimates. This bias could be severe and highly detrimental to conservation actions if uninformed ISDMs are used to estimate global populations of threatened and data-deficient species, particularly those that lack natural history and movement information. However, the ISDM was consistently the most accurate model compared to other approaches, which demonstrates the importance of this new modelling framework and the ability to combine opportunistic data with systematic survey data. Thus, we recommend researchers use ISDMs with conservative movement information when estimating population sizes of rare and data-deficient species. ISDMs could be improved by using a similar parameterization to spatial capture–recapture models that explicitly incorporate animal movement as a model parameter, which would further remove the need for spatial subsampling prior to implementation.

Baird's tapir Tapirus bairdii is categorized as Endangered on the IUCN Red List and is considered rare and locally extirpated from most of its historic range in Costa Rica. We conducted camera-trap and track surveys at 38 forested sites in and around the San Juan–La Selva Biological Corridor in the Northern Zone of Costa Rica. Cameras were set along established game trails and natural funnels and operated for 14–38 days per site. Additionally, we documented tapir tracks at many sites. We used survey photographs and track presence to create detection histories to estimate the habitat and survey-specific variables that influence the probability of detection and the probability of occurrence of Baird's tapir. The two major protected areas within and adjacent to the corridor were most positively associated with tapir occurrence, and forest cover and native and exotic tree plantations were also positively associated with tapirs’ use of sites. Although the Baird's tapir is rare, our findings suggest that it is more resilient and better able to use available habitat in the fragmented corridor than previously thought. This is most likely a consequence of increased forest cover from reforestation and tree plantations and limited hunting pressure. Given its charismatic nature we recommend that Baird's tapir could be used as a flagship species for the San Juan–La Selva Biological Corridor, to raise local awareness about conservation and increase economic growth from ecotourism.

A large deviations principle (LDP), demonstrated for occupancy problems with indistinguishable balls, is generalized to the case in which balls are distinguished by a finite number of colors. The colors of the balls are chosen independently from the occupancy process itself. There are r balls thrown into n urns with the probability of a ball entering a given urn being 1/n (i.e. Maxwell-Boltzmann statistics). The LDP applies with the scale parameter, n, tending to infinity and r increasing proportionally. The LDP holds under mild restrictions, the key one being that the coloring process by itself satisfies an LDP. This includes the important special cases of deterministic coloring patterns and colors chosen with fixed probabilities independently for each ball.

An occupancy model that has arisen in the investigation of randomized distributed schedules in all-optical networks is considered. The model consists of B initially empty urns, and at stage j of the process dj ≤ B balls are placed in distinct urns with uniform probability. Let Mi(j) denote the number of urns containing i balls at the end of stage j. An explicit expression for the joint factorial moments of M0(j) and M1(j) is obtained. A multivariate generating function for the joint factorial moments of Mi(j), 0 ≤ i ≤ I, is derived (where I is a positive integer). Finally, the case in which the dj, j ≥ 1, are independent, identically distributed random variables is investigated.