Simultaneous-count models to estimate abundance from counts of unmarked individuals with imperfect detection

We developed a method to estimate population abundance from simultaneous counts of unmarked individuals over multiple sites. We considered that at each sampling occasion, individuals in a population could be detected at 1 of the survey sites or remain undetected and used either multinomial or binomial simultaneous-count models to estimate abundance, the latter being equivalent to an N-mixture model with one site. We tested model performance with simulations over a range of detection probabilities, population sizes, growth rates, number of years, sampling occasions, and sites. We then applied our method to 3 critically endangered vulture species in Cambodia to demonstrate the real-world applicability of the model and to provide the first abundance estimates for these species in Cambodia. Our new approach works best when existing methods are expected to perform poorly (i.e., few sites and large variation in abundance among sites) and if individuals may move among sites between sampling occasions. The approach performed better when there were >8 sampling occasions and net probability of detection was high (>0.5). We believe our approach will be useful in particular for simultaneous surveys at aggregation sites, such as roosts. The method complements existing approaches for estimating abundance of unmarked individuals and is the first method designed specifically for simultaneous counts.     

Quantifying the conservation gains from shared access to linear infrastructure

The proliferation of linear infrastructure such as roads and railways is a major global driver of cumulative biodiversity loss. One strategy for reducing habitat loss associated with development is to encourage linear infrastructure providers and users to share infrastructure networks. We quantified the reductions in biodiversity impact and capital costs under linear infrastructure sharing of a range of potential mine to port transportation links for 47 mine locations operated by 28 separate companies in the Upper Spencer Gulf Region of South Australia. We mapped transport links based on least‐cost pathways for different levels of linear‐infrastructure sharing and used expert‐elicited impacts of linear infrastructure to estimate the consequences for biodiversity. Capital costs were calculated based on estimates of construction costs, compensation payments, and transaction costs. We evaluated proposed mine‐port links by comparing biodiversity impacts and capital costs across 3 scenarios: an independent scenario, where no infrastructure is shared; a restricted‐access scenario, where the largest mining companies share infrastructure but exclude smaller mining companies from sharing; and a shared scenario where all mining companies share linear infrastructure. Fully shared development of linear infrastructure reduced overall biodiversity impacts by 76% and reduced capital costs by 64% compared with the independent scenario. However, there was considerable variation among companies. Our restricted‐access scenario showed only modest biodiversity benefits relative to the independent scenario, indicating that reductions are likely to be limited if the dominant mining companies restrict access to infrastructure, which often occurs without policies that promote sharing of infrastructure. Our research helps illuminate the circumstances under which infrastructure sharing can minimize the biodiversity impacts of development.