A flexible framework for spatial capture-recapture with unknown identities.

Camera traps or acoustic recorders are often used to sample wildlife populations. When animals can be individually identified, these data can be used with spatial capture-recapture (SCR) methods to assess populations. However, obtaining animal identities is often labor-intensive and not always possible for all detected animals. To address this problem, we formulate SCR, including acoustic SCR, as a marked Poisson process, comprising a single counting process for the detections of all animals and a mark distribution for what is observed (eg, animal identity, detector location). The counting process applies equally when it is animals appearing in front of camera traps and when vocalizations are captured by microphones, although the definition of a mark changes. When animals cannot be uniquely identified, the observed marks arise from a mixture of mark distributions defined by the animal activity centers and additional characteristics. Our method generalizes existing latent identity SCR models and provides an integrated framework that includes acoustic SCR. We apply our method to estimate density from a camera trap study of fisher (Pekania pennanti) and an acoustic survey of Cape Peninsula moss frog (Arthroleptella lightfooti). We also test it through simulation. We find latent identity SCR with additional marks such as sex or time of arrival to be a reliable method for estimating animal density.

Quantifying the Extent of Anthropogenic Eutrophication of Lakes at a National Scale in New Zealand.

Quantifying environmental changes relative to ecosystem reference conditions (baseline or natural states) can inform assessment of anthropogenic impacts and the development of restoration objectives and targets. We developed statistical models to predict current and reference concentrations of total nitrogen (TN) and total phosphorus (TP) in surface waters for a nationally representative sample of ≥1033 New Zealand lakes. The lake-specific nutrient concentrations reflected variation in factors including anthropogenic nutrient loads, hydrology, geology, elevation, climate, and lake and catchment morphology. Changes between reference and current concentrations were expressed to quantify the magnitude of anthropogenic eutrophication. Overall, there was a clear increase in lake trophic status, with the most common trophic status being oligotrophic under a reference state and mesotrophic under current conditions. The magnitude of departure from reference state varied considerably within the sample; however, on average, the mean TN concentration approximately doubled between reference and current states, whereas the mean TP concentration increased approximately 4-fold. This study quantified the extent of water quality degradation across lake types at a national scale, thereby informing ecological restoration objectives and the potential to reduce anthropogenic nutrient loads, while also providing a modeling framework that can be applied to lakes elsewhere.