Monitoring and conservation of the Critically Endangered Alaotran gentle lemur Hapalemur alaotrensis

The Alaotran gentle lemur Hapalemur alaotrensis is a Critically Endangered lemur, which exclusively inhabits the marshes around Lac Alaotra in northeast Madagascar. In the past decades the population of H. alaotrensis has experienced a dramatic decline due to poaching, habitat destruction and degradation. Surveys have been carried out periodically to follow the status of the population. Here we present the results of a survey carried out between May and June 2008 in the southwestern part of the marshes around Alaotra and discuss the key findings derived from the analysis of the data collected. Our study indicates that the probability of detecting the species in an area where it is present is very low and depends on factors that vary in space and time. These results stress the need to account for imperfect detection when monitoring this species, an issue especially relevant when reporting population trends. Our analyses also show that habitat fragmentation is a key determinant of habitat suitability for H. alaotrensis, with fragmented areas of marsh showing low suitability. Finally, our observations and analysis suggest that the protection provided by the local community to H. alaotrensis in Andreba is contributing to the conservation of this Critically Endangered species. This highlights the need to continue working on engaging the local communities in the conservation of the marshes at Lac Alaotra as a critical element to secure the future of H. alaotrensis. KEYWORDS: bandro, habitat suitability, habitat fragmentation, imperfect detection, Maxent

Cost-efficient effort allocation for camera-trap occupancy surveys of mammals

Camera-traps are increasingly used to survey threatened mammal species and are an important tool for estimating habitat occupancy. To date, cost-efficient occupancy survey effort allocation studies have focused on trade-offs between number of sample units (SUs) and sampling occasions, with simplistic accounts of associated costs which do not reflect camera-trap survey realities. Here we examine camera-trap survey costs as a function of the number of SUs, survey duration and camera-traps per SU, linking costs to precision in occupancy estimation. We evaluate survey effort trade-offs for hypothetical species representing different levels of occupancy (?) and detection (p) probability to identify optimal design strategies. We apply our cost function to three threatened species as worked examples. Additionally, we use an extensive camera-trap data set to evaluate independence between multiple camera traps per SU. The optimal number of sampling occasions that result in minimum cost decrease as detection probability increases, irrespective of whether the species is rare (? 0.5). The most expensive survey scenarios occur for elusive (p 10 km2), where the survey is conducted on foot. Minimum survey costs for elusive species can be achieved with fewer sampling occasions and multiple cameras per SU. Multiple camera-traps set within a single SU can yield independent species detections. We provide managers and researchers with guidance for conducting cost-efficient camera-trap occupancy surveys. Efficient use of survey budgets will ultimately contribute to the conservation of threatened and data deficient mammals

Conservation in the maelstrom of Covid‐19 – a call to action to solve the challenges, exploit opportunities and prepare for the next pandemic

As we sit in the vortex of the Covid‐19 outbreak, individual energies are focused on staying safe and juggling the personal, social and financial impacts of the pandemic and political responses to it. These impacts are profoundly re‐shaping our lives, with many commentators suggesting that ‘normality’ will be permanently redefined for all sectors of society. The future is not clear because the maelstrom is so intense that it is unlikely that the dust will settle any time soon. This pandemic will be one of the major game changers for humanity in the 21st century. The conservation impacts are set to be huge, and this is an understatement. It is remarkable how little past attention has been given to identifying the conservation impacts of human responses to pandemics and preparing for these, especially given considerable investment in global biodiversity and conservation‐focused horizon scanning exercises over the last decade (e.g. Sutherland et al., 2020). Conservation scientists, practitioners and policy‐makers must urgently address this lack of preparation and innovate solutions to confront the challenges arising from the radically altered economics, attitudes and behaviours imposed by Covid‐19. Our job is to think creatively and collaboratively with other sectors of society to ensure that recent progress in implementing effective conservation and protection of nature is not lost. We must also insist that conservationists contribute to re‐shaping the future post‐Covid‐19 world, to ensure that potential benefits to nature conservation and protection are realized. We identify three broad challenges and a diverse set of potential positive developments that require urgent attention and strategy development. We cannot afford to sit back and wait to see what happens as the new world emerges, or to be unprepared when the next pandemic hits

High carbon stock forests provide co-benefits for tropical biodiversity

1. Carbon-based policies provide powerful opportunities to unite tropical forest conservation with climate change mitigation. However, their effectiveness in delivering biodiversity co-benefits is dependent on high levels of biodiversity being found in high carbon areas. Previous studies have focussed solely on the co-benefits associated with Reducing Emissions from Deforestation and forest Degradation (REDD+) over large spatial scales, with few empirically testing carbon-biodiversity correlations at management unit scales appropriate to decision-makers. Yet, in development frontiers, where most biodiversity and carbon loss occurs, carbon-based policies are increasingly driven by commodity certification schemes, which are applied at the concession-level. 2. Working in a typical human-modified landscape in Southeast Asia, we examined the biodiversity value of land prioritised via application of REDD+ or the High Carbon Stock (HCS) Approach, the emerging land-use planning tool for oil palm certification. Carbon stocks were estimated via low- and high-resolution datasets derived from global or local level biomass. Mammalian species richness was predicted using hierarchical Bayesian multi-species occupancy models of camera-trap data from forest and oil palm habitats. 3. At the community level, HCS forest supported comparable mammal diversity to control sites in continuous forest, while lower carbon strata exhibited reduced species occupancy. 4. No association was found between species richness and carbon when the latter was estimated using coarse-resolution data. However, when using high-resolution, field validated biomass data, diversity demonstrated positive relationships with carbon for threatened and disturbance-sensitive species, suggesting sensitivity of co-benefits to carbon data sources and the species considered. 5. Policy implications. Our work confirms the potential for environmental certification and REDD+ to work in tandem with conservation to mitigate agricultural impacts on tropical forest carbon stocks and biodiversity, especially if this directs development to low carbon, low biodiversity areas

Implications of zero-deforestation commitments: forest quality and hunting pressure limit mammal persistence in fragmented tropical landscapes

Zero-deforestation commitments seek to decouple agricultural production and forest loss to improve prospects for biodiversity. However, the effectiveness of methods designed to meet these commitments is poorly understood. In a highly-fragmented tropical landscape dominated by oil palm, we tested the capacity for the High Carbon Stock (HCS) Approach to prioritise forest remnants that sustain mammal diversity. Patches afforded High Priority by HCS protocols (100 ha core area) provided important refuges for IUCN-threatened species and megafauna. However, patch-scale HCS area recommendations conserved only 35% of the mammal community. At least 3,000 ha would be required to retain intact mammal assemblages, with nearly ten times this area needed if hunting pressure was high. While current HCS protocols will safeguard patches capable of sustaining biodiversity, highly-fragmented tropical landscapes typical of zero-deforestation pledges will require thinking beyond the patch, towards strategically configured forest remnants at the landscape-level and enforcing strict controls on hunting

Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations

Tropical forest ecosystems are facing unprecedented levels of degradation, severely compromising habitat suitability for wildlife. Despite the fundamental role biodiversity plays in forest regeneration, identifying and prioritising degraded forests for restoration or conservation, based on their wildlife value, remains a significant challenge. Efforts to characterize habitat selection are also weakened by simple classifications of human-modified tropical forests as intact versus degraded, which ignore the influence that three-dimensional forest structure may have on species distributions. Here, we develop a framework to identify conservation and restoration opportunities across logged forests in Borneo. We couple high-resolution airborne Light Detection and Ranging (LiDAR) and camera trap data to characterize the response of a tropical mammal community to changes in three-dimensional forest structure across a degradation gradient. Mammals were most responsive to covariates that accounted explicitly for the vertical and horizontal characteristics of the forest, and actively selected structurally-complex environments comprising tall canopies, increased plant area index throughout the vertical column, and the availability of a greater diversity of niches. We show that mammals are sensitive to structural simplification through disturbance, emphasising the importance of maintaining and enhancing structurally-intact forests. By calculating occurrence thresholds of species in response to forest structural change, we identify areas of degraded forest that would provide maximum benefit for multiple high conservation value species if restored. The study demonstrates the advantages of using LiDAR to map forest structure, rather than relying on overly simplistic classifications of human-modified tropical forests, for prioritising regions for restoration

Data integration for large-scale models of species distributions

With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species’ potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise

Novel community data in ecology-properties and prospects

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce ‘novel community data’ as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning

Optimising monitoring efforts for secretive snakes: a comparison of occupancy and N-mixture models for assessment of population status

A fifth of reptiles are Data Deficient; many due to unknown population status. Monitoring snake populations can be demanding due to crypsis and low population densities, with insufficient recaptures for abundance estimation via Capture-Mark-Recapture. Alternatively, binomial N-mixture models enable abundance estimation from count data without individual identification, but have rarely been successfully applied to snake populations. We evaluated the suitability of occupancy and N-mixture methods for monitoring an insular population of grass snakes (Natrix helvetica) and considered covariates influencing detection, occupancy and abundance within remaining habitat. Snakes were elusive, with detectability increasing with survey effort (mean: 0.33 ± 0.06 s.e.m.). The probability of a transect being occupied was moderate (mean per kilometre: 0.44 ± 0.19 s.e.m.) and increased with transect length. Abundance estimates indicate a small threatened population associated to our transects (mean: 39, 95% CI: 20–169). Power analysis indicated that the survey effort required to detect occupancy declines would be prohibitive. Occupancy models fitted well, whereas N-mixture models showed poor fit, provided little extra information over occupancy models and were at greater risk of closure violation. Therefore we suggest occupancy models are more appropriate for monitoring snakes and other elusive species, but that population trends may go undetected