Greg Distiller’s research while affiliated with University of Cape Town and other places

It has become clear that state-owned protected areas (PAs) are insufficient in preserving the world’s spatially heterogenous biodiversity. Private land conservation could contribute significantly to national conservation goals, without further burdening state resources. In South Africa, legislation has been introduced to incentivise private landowners to contribute to national biodiversity goals. In this study, we used camera trap arrays and hierarchical multi-species occupancy modelling to evaluate the impact of land-use on mammal (body mass >0.5 kg) diversity in the drylands of South Africa. Four hundred and fifty-one camera traps were deployed across a statutory PA, private PA and a neighbouring group of farmlands, covering ~2096 km2. Although trophic species richness were similar across all three land-uses, occurrence and detection probabilities of larger (>20 kg) species were low in the farmlands and highest in the private PA. In contrast, smaller species had higher occurrence probabilities in the farmlands, where large predators and megaherbivores have been extirpated. Differences in species-specific occurrence probabilities were primarily driven by land-use context, as opposed to fine-scale habitat attributes. These results highlight how a land-use matrix incorporating statutory PAs, private PAs and well-managed rangelands can benefit wildlife conservation, as long as these land-uses are included in carefully developed regional conservation planning.

The world is firmly cemented in a notitian age (Latin: notitia, meaning data) – drowning in data, yet thirsty for information and the synthesis of knowledge into understanding. As concerns over biodiversity declines escalate, the volume, diversity and speed at which new environmental and ecological data are generated has increased exponentially. Data availability primes the research and discovery engine driving biodiversity conservation. South Africa (SA) is poised to become a world leader in biodiversity conservation. However, continent-wide resource limitations hamper the establishment of inclusive technologies and robust platforms and tools for biodiversity informatics. In this perspectives piece, we bring together the opinions of 37 co-authors from 20 different departments, across 10 SA universities, 7 national and provincial conservation research agencies, and various institutes and private conservation, research and management bodies, to develop a way forward for biodiversity informatics in SA. We propose the development of a SA Biodiversity Informatics Hub and describe the essential components necessary for its design, implementation and sustainability. We emphasise the importance of developing a culture of cooperation, collaboration and interoperability among custodians of biodiversity data to establish operational workflows for data synthesis. However, our biggest challenges are misgivings around data sharing and multidisciplinary collaboration. We recommend a system that is free, user friendly, functional, stable, integrative and designed to cater for different data access agreement levels. Sharing data through this pipeline will directly advance the science and practice of conservation, giving multiple stakeholders and decision-makers access to valuable biodiversity data to support research and biodiversity conservation.

Abundance estimates of cetaceans are often acquired through capture‐recapture analysis of photographically identified individuals. An alternative method, using capture‐recapture of individually distinct signature whistles detected from acoustic underwater recording units, has recently been demonstrated. Here we investigate the effect of array configuration (1–3 hydrophones within 0.45 km2) and recording duty cycles (six variations of 33%, 50%, or 66% sampling periods) on the detection rate of dolphin signature whistles. Twenty‐one signature whistle types were identified and used to create capture histories for each hydrophone and all potential array configurations. Open population models were used to estimate capture probabilities and precision for all data sets. The effect of different duty cycles on detectability were investigated by artificially applying six duty cycles to the continuously recorded data. Results demonstrate that location is more important than redundancy in small‐scale arrays, even with detection distances as small as 750 m, and that duty cycling can increase survey durations without decreasing detectability. To acoustically sample intermittent signals of dispersed populations, it is more effective to space hydrophones further apart, in known high‐use areas. This study provides insight into the application of capture‐recapture to signature whistles, improving methods for long‐term, noninvasive monitoring of elusive delphinids.

Effective conservation requires understanding the processes that determine population outcomes. Too often, we assume that protected areas conserve wild populations despite evidence that they frequently fail to do so. Without large‐scale studies, however, we cannot determine what relationships are the product of localized conditions versus general patterns that inform conservation more broadly. Leopards’ (Panthera pardus) basic ecology is well studied but little research has investigated anthropogenic effects on leopard density at broad scales. We investigated the drivers of leopard density among 27 diverse protected areas in northeastern South Africa to understand what conditions facilitate abundant populations. We formulated 10 working hypotheses that considered the relative influence of bottom‐up biological factors and top‐down anthropogenic factors on leopard density. Using camera‐trap survey data, we fit a multi‐session spatial capture–recapture model with inhomogenous density for each hypothesis and evaluated support using an information theoretic approach. The four supported hypotheses indicated that leopard density is primarily limited by human impacts, but that habitat suitability and management conditions also matter. The proportion of camera stations that recorded domestic animals, a proxy for the extent of human impacts and protected area effectiveness, was the only predictor variable present in all four supported models. Protected areas are the cornerstone of large felid conservation, but only when the human–wildlife interface is well managed and protected areas shelter wildlife populations from anthropogenic impacts. To ensure the long‐term abundance of large carnivore populations, reserve managers should recognize the ineffectiveness of “paper parks” and promote contiguous networks of protected areas that offer leopards and other large mammal populations greater space and reduced human impacts.

Dramatic population declines of African wild dogs (Lycaon pictus) led to a managed metapopulation approach for wild dog conservation in South Africa. Monitoring the survival and habitat use of packs reintroduced into protected areas (PAs) is an essential part of adaptive management and improving the health and, ultimately, the survival of the metapopulation. Our study describes the territoriality and habitat selection of a pack of wild dogs reintroduced into Manyoni Private Game Reserve (219 km2) in northern KwaZulu-Natal, South Africa. Despite being introduced into a small PA, the pack only utilized half their available space (121 km2) and avoided the central areas of the reserve. Post hoc analysis of African lion (Panthera leo) localities suggested competitive avoidance was a strong factor in shaping the habitat usage of the pack; however, further research is required. Habitat selection also varied seasonally and with denning. Ultimately, we showed that spatio-temporal analyses can help identify high-risk areas within wild dog territories, such as hotspots of activity along fencelines. These analyses can then be used to increase targeted management of these areas, such as improving the maintenance of well-used fencelines, which is an important consideration for the sustained success of the metapopulation across small PAs.

Effective conservation, particularly of threatened species, requires an understanding of both abiotic and biotic drivers of distribution. In the case of one of Africa’s most endangered mammals, the riverine rabbit Bunolagus monticularis , only environmental covariates of presence have been used to provide coarse predictions of their distribution. Two potential competitors, namely scrub hare Lepus saxatilis and cape hare L. capensis , have significant (>90%) range overlap with the riverine rabbit, yet little is known about how these species interact. We used multi-species occupancy models, which model co-occurrence as a function of environmental variables, to assess the spatial response of riverine rabbits to both species of hare in Sanbona Wildlife Reserve, South Africa. We also examined temporal overlap between riverine rabbits and hares. Camera trapping data were collected from 150 camera traps distributed in clusters of 5 cameras at 30 independent sites, covering 223.24 km ² . Contrary to prior studies, we found that riverine rabbits were not restricted to riparian habitat, and that their occurrence was conditional on hare absence and was negatively affected by terrain ruggedness. Whilst hare occurrence was independent of terrain ruggedness, it was negatively affected by rabbit presence. Activity patterns revealed high temporal overlap between hares and rabbits (Δ = 0.828, CI = 0.745-0.940); however, neither species co-occurred at any given site. Our results suggest that conservation management has greatly underestimated the importance of competition with other lagomorphs in understanding riverine rabbit occurrence.

• Quantifying the distribution of daily activity is an important component of behavioral ecology. Historically, it has been difficult to obtain data on activity patterns, especially for elusive species. However, the development of affordable camera traps and their widespread usage has led to an explosion of available data from which activity patterns can be estimated. • Continuous‐time spatial capture–recapture (CT SCR) models drop the occasion structure seen in traditional spatial and nonspatial capture–recapture (CR) models and use the actual times of capture. In addition to estimating density, CT SCR models estimate expected encounters through time. Cyclic splines can be used to allow flexible shapes for modeling cyclic activity patterns, and the fact that SCR models also incorporate distance means that space–time interactions can be explored. This method is applied to a jaguar dataset. • Jaguars in Belize are most active and range furthest in the evening and early morning and when they are located closer to the network of trails. There is some evidence that females have a less variable pattern than males. The comparison between sexes demonstrates how CT SCR can be used to explore hypotheses about animal behavior within a formal modeling framework. • SCR models were developed primarily to estimate and model density, but the models can be used to explore processes that interact across space and time, especially when using the CT SCR framework that models the temporal dimension at a finer resolution.

The pyjama shark Poroderma africanum (family Scyliorhinidae) is endemic to coastal waters of South Africa but its population characteristics are poorly known. This study aims to estimate baseline demographic parameters for P. africanum in Mossel Bay. We applied mark-recapture methods following Pollock’s robust design (PRD) and Cormack–Jolly–Seber (CJS) models, using five-year tag-recapture data and one-year acoustic-telemetry data, respectively. Estimates of abundance, survival, capture probabilities and temporary emigration were obtained using these models. The PRD model indicated random temporary emigration (0.955 period–1 [95% CI 0.755–0.993]), constant survival, and season-varying capture and recapture probabilities with a negative behavioural response to first capture (β = −5.34 [−6.89 to −3.80]). Abundance estimates ranged from 11 (10.01–13.21) to 53 (52.05–56.82) sharks in Mossel Bay. The CJS model indicated constant survival (0.271 y–1 [95% CI 0.0–0.75]) and sex-independent probabilities of being captured at least once annually (1.0 y–1 for both sexes). This study provides the first demographic information for the management of this population. Further studies should utilise larger sample sizes and more complex models, and investigate specific management options.

The global decline of large carnivores demands effective and efficient methods to monitor population status, particularly using non‐invasive methods. Density is among the most useful metrics of population status because it is directly comparable across space and time. Unfortunately, density is difficult to measure reliably, especially for mobile, cryptic species. Recently, efforts have turned to approximating density based on its relationship to more readily estimable indices of occurrence. However, the relationship between density and such indices is contingent on several key assumptions that field studies often violate. Recent research has shown that these relationships are unreliable where sampling units are not independent, as is often the case when estimating density or occurrence of large carnivores. Here, we use the largest data set thus far collected for leopards (Panthera pardus)—88 camera‐trap surveys undertaken in 24 protected areas between 2013 and 2018—to explore how density and other population characteristics relate to parameter estimates in occupancy and Royle–Nichols abundance models. We show how home‐range size confounds underlying relationships, with larger home ranges inflating the proportion of area used (PAU) and resulting in double counting in abundance models. Relativizing estimates of occupancy and abundance by home‐range size improved their relationship with density, but the relationship remained weak and largely uninformative for management. Our findings illustrate the pitfalls of using the PAU or abundance as implicit proxies for density and highlight the challenges of assessing population status for wide‐ranging, cryptic species across fragmented landscapes.