Population Status of a Cryptic Top Predator: An Island-Wide Assessment of Tigers in Sumatran Rainforests

Large carnivores living in tropical rainforests are under immense pressure from the rapid conversion of their habitat. In response, millions of dollars are spent on conserving these species. However, the cost-effectiveness of such investments is poorly understood and this is largely because the requisite population estimates are difficult to achieve at appropriate spatial scales for these secretive species. Here, we apply a robust detection/non-detection sampling technique to produce the first reliable population metric (occupancy) for a critically endangered large carnivore; the Sumatran tiger (Panthera tigris sumatrae). From 2007–2009, seven landscapes were surveyed through 13,511 km of transects in 394 grid cells (17×17 km). Tiger sign was detected in 206 cells, producing a naive estimate of 0.52. However, after controlling for an unequal detection probability (where p = 0.13±0.017; ±S.E.), the estimated tiger occupancy was 0.72±0.048. Whilst the Sumatra-wide survey results gives cause for optimism, a significant negative correlation between occupancy and recent deforestation was found. For example, the Northern Riau landscape had an average deforestation rate of 9.8%/yr and by far the lowest occupancy (0.33±0.055). Our results highlight the key tiger areas in need of protection and have led to one area (Leuser-Ulu Masen) being upgraded as a ‘global priority’ for wild tiger conservation. However, Sumatra has one of the highest global deforestation rates and the two largest tiger landscapes identified in this study will become highly fragmented if their respective proposed roads networks are approved. Thus, it is vital that the Indonesian government tackles these threats, e.g. through improved land-use planning, if it is to succeed in meeting its ambitious National Tiger Recovery Plan targets of doubling the number of Sumatran tigers by 2022

Accurate Measurement of Tropical Forest Canopy Heights and Aboveground Carbon Using Structure From Motion

Unmanned aerial vehicles are increasingly used to monitor forests. Three-dimensional models of tropical rainforest canopies can be constructed from overlapping photos using Structure from Motion (SfM), but it is often impossible to map the ground elevation directly from such data because canopy gaps are rare in rainforests. Without knowledge of the terrain elevation, it is, thus, difficult to accurately measure the canopy height or forest properties, including the recovery stage and aboveground carbon density. Working in an Indonesian ecosystem restoration landscape, we assessed how well SfM derived the estimates of the canopy height and aboveground carbon density compared with those from an airborne laser scanning (also known as LiDAR) benchmark. SfM systematically underestimated the canopy height with a mean bias of approximately 5 m. The linear models suggested that the bias increased quadratically with the top-of-canopy height for short, even-aged, stands but linearly for tall, structurally complex canopies (&gt;10 m). The predictions based on the simple linear model were closely correlated to the field-measured heights when the approach was applied to an independent survey in a different location ( R 2 = 67% and RMSE = 1.85 m), but a negative bias of 0.89 m remained, suggesting the need to refine the model parameters with additional training data. Models that included the metrics of canopy complexity were less biased but with a reduced R 2 . The inclusion of ground control points (GCPs) was found to be important in accurately registering SfM measurements in space, which is essential if the survey requirement is to produce small-scale restoration interventions or to track changes through time. However, at the scale of several hectares, the top-of-canopy height and above-ground carbon density estimates from SfM and LiDAR were very similar even without GCPs. The ability to produce accurate top-of-canopy height and carbon stock measurements from SfM is game changing for forest managers and restoration practitioners, providing the means to make rapid, low-cost surveys over hundreds of hectares without the need for LiDAR.</jats:p

Monitoring early-successional trees for tropical forest restoration using low-cost UAV-based species classification

Peer reviewed: TrueAcknowledgements: We thank Rhett Harrison for his significant input into grant writing. We are grateful to Dr. Tuomo Valkonen, whose early attempt to classify species without delineating trees was unsuccessful but paved the way for the development of more sophisticated approaches. We wish to thank all partners at Hutan Harapan for their help with managing the UAV and tree data collection at Hutan Harapan. We particularly wish to thank Adi, Agustiono, and Dika for their support with UAV flying and data collection. We are also very grateful for the support from members of Universitas Jambi who supported the logistics of our collaboration.Logged forests cover four million square kilometers of the tropics, capturing carbon more rapidly than temperate forests and harboring rich biodiversity. Restoring these forests is essential to help avoid the worst impacts of climate change. Yet monitoring tropical forest recovery is challenging. We track the abundance of early-successional species in a forest restoration concession in Indonesia. If the species are carefully chosen, they can be used as an indicator of restoration progress. We present SLIC-UAV, a new pipeline for processing Unoccupied Aerial Vehicle (UAV) imagery using simple linear iterative clustering (SLIC)to map early-successional species in tropical forests. The pipeline comprises: (a) a field verified approach for manually labeling species; (b) automatic segmentation of imagery into “superpixels” and (c) machine learning classification of species based on both spectral and textural features. Creating superpixels massively reduces the dataset's dimensionality and enables the use of textural features, which improve classification accuracy. In addition, this approach is flexible with regards to the spatial distribution of training data. This allowed us to be flexible in the field and collect high-quality training data with the help of local experts. The accuracy ranged from 74.3% for a four-species classification task to 91.7% when focusing only on the key early-succesional species. We then extended these models across 100 hectares of forest, mapping species dominance and forest condition across the entire restoration project.</jats:p

Avifauna recovers faster in areas less accessible to trapping in regenerating tropical forests

Tropical forest restoration stands to deliver important conservation gains, particularly in lowland Southeast Asia, which has suffered some of the world's highest rates of recent forest loss and degradation. This promise, however, depends on the extent to which biodiversity at forest restoration sites continues to be exposed to threats. A key knowledge gap concerns the extent to which biodiversity recovery in naturally regenerating tropical forests is impacted by trapping for the multi-million-dollar wildlife trade. Here, we use a repeated survey dataset to quantify rates of avian community recovery under forest regeneration, at a flagship restoration site in the lowland rainforests of Sumatra, Indonesia. We show that over a decade, forest regeneration was associated with significant abundance increases for 43.8 % of bird species. However, the apparent negative impacts of trade-driven trapping on avian populations also intensified: the proportion of species dependent on very remote forests increased from 5.4 % to 16.2 %. Moreover, the overall accessibility of the forest increased. We found that 14 % of species did not recover as fast as predicted based on the observed forest regeneration over the study period. We found trapping to disproportionately impact species targeted for trade: compared to opportunistically trapped species, twice more species showed increased abundance only in very remote forests. Our results highlight the potential for rapid avifaunal recovery in regenerating tropical forests, but also emphasize the urgency of tackling the serious threat of wildlife trade to Southeast Asia's biodiversity.We gratefully acknowledge the funding support from the joint AEC-OBC Conservation Grant (No. P1250) provided by the Oriental Bird Club and the Ecology Arboriculture Landscape, Sir Philip Reckitt Educational Trust travel grant, and European Commission’s Joint Master’s Degree Fellowship (FPA 2023 – 0224/ 532524-1-FR-2012-1-ERA MUNDUS-EMMC)

The road to recovery: a synthesis of outcomes from ecosystem restoration in tropical and sub-tropical Asian forests

Current policy is driving renewed impetus to restore forests to return ecological function, protect species, sequester carbon and secure livelihoods. Here we assess the contribution of tree planting to ecosystem restoration in tropical and sub-tropical Asia; we synthesize evidence on mortality and growth of planted trees at 176 sites and assess structural and biodiversity recovery of co-located actively restored and naturally regenerating forest plots. Mean mortality of planted trees was 18% 1 year after planting, increasing to 44% after 5 years. Mortality varied strongly by site and was typically ca 20% higher in open areas than degraded forest, with height at planting positively affecting survival. Size-standardized growth rates were negatively related to species-level wood density in degraded forest and plantations enrichment settings. Based on community-level data from 11 landscapes, active restoration resulted in faster accumulation of tree basal area and structural properties were closer to old-growth reference sites, relative to natural regeneration, but tree species richness did not differ. High variability in outcomes across sites indicates that planting for restoration is potentially rewarding but risky and context-dependent. Restoration projects must prepare for and manage commonly occurring challenges and align with efforts to protect and reconnect remaining forest areas. The abstract of this article is available in Bahasa Indonesia in the electronic supplementary material. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.ISSN:0962-8436ISSN:1471-2970ISSN:0080-462

The road to recovery: a synthesis of outcomes from ecosystem restoration in tropical and sub-tropical Asian forests.

Current policy is driving renewed impetus to restore forests to return ecological function, protect species, sequester carbon and secure livelihoods. Here we assess the contribution of tree planting to ecosystem restoration in tropical and sub-tropical Asia; we synthesize evidence on mortality and growth of planted trees at 176 sites and assess structural and biodiversity recovery of co-located actively restored and naturally regenerating forest plots. Mean mortality of planted trees was 18% 1 year after planting, increasing to 44% after 5 years. Mortality varied strongly by site and was typically ca 20% higher in open areas than degraded forest, with height at planting positively affecting survival. Size-standardized growth rates were negatively related to species-level wood density in degraded forest and plantations enrichment settings. Based on community-level data from 11 landscapes, active restoration resulted in faster accumulation of tree basal area and structural properties were closer to old-growth reference sites, relative to natural regeneration, but tree species richness did not differ. High variability in outcomes across sites indicates that planting for restoration is potentially rewarding but risky and context-dependent. Restoration projects must prepare for and manage commonly occurring challenges and align with efforts to protect and reconnect remaining forest areas. The abstract of this article is available in Bahasa Indonesia in the electronic supplementary material. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'

Summary of Sumatra-wide field survey effort for each landscape.

<p>*I = global priority; II = regional priority; III = long-term priority.</p>1<p>Kerinci Seblat National Park and Batang Hari Protection Forest and their surrounding forests.</p>2<p>Bukit Barisan Selatan National Park and Bukit Balai Rejang Selatan.</p>3<p>Pasir Pangaraian, Giam Siak, Duri, Balaraja, Tapung.</p>4<p>Tesso Nilo, Bukit Bungkuk, Bukit Rimbang-Baling, Bukit Batabuh, Bukit Tigapuluh, Kerumutan.</p>5<p>Dangku, Bukit Duabelas, Berbak.</p