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

Abstract

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 prioritizing 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 vs. degraded, which ignore the influence that three-dimensional (3D) 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 3D 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, emphasizing 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 prioritizing regions for restoration.

The impact of logging on vertical canopy structure across a gradient of tropical forest degradation intensity in Borneo

“…The sensitivity of LiDAR‐based PAD distributions to logging‐driven changes in canopy structure will facilitate landscape‐level descriptions of forest condition in high‐biomass tropical forests. LiDAR mapping can therefore facilitate management of these forests by helping prioritise conservation and restoration efforts in a manner that maximises the benefits to ecosystem services (Deere et al., 2020). The dominant drivers of degradation (timber logging, fuelwood extraction, fire) vary from region to region (Hosonuma et al., 2012), with potentially distinct impacts on canopy structure (e.g.…”

Ten golden rules for reforestation to optimize carbon sequestration, biodiversity recovery and livelihood benefits

“…Non-forested peatlands contain an even higher amount of SOC, which would be released into the atmosphere if trees were planted there (Brancalion & Chazdon, 2017;Crane, 2020;NCC, 2020). Similarly, lands covered by snow at high latitudes reflect an important quantity of sun radiation due to the high albedo, providing a cooling effect on the planet that would not be compensated for by the amount of carbon slowly captured by trees grown in those cold climates (Bala et al, 2007;Betts, 2000 (Deere et al, 2020).…”

Life in the Canopy: Using Camera-Traps to Inventory Arboreal Rainforest Mammals in Borneo

“…Our trials deploying a second canopy camera-trap did not yield much improvement to new species detections (Figure 4 and Supplementary Figure 3); however, they were limited to a small subset of trees and a shorter sampling period. It is worth noting that the gains in unique species detections from additional canopy camera-traps came from unlogged forest locations, which makes sense in the context of the greater height and structural complexity -and therefore larger potential sampling area -of unlogged forest canopies (Deere et al, 2020). Canopy cameratrapping as a sampling method is in its infancy, and forest canopies present a much more complex sampling space than the forest floor.…”

“…However, these findings should be viewed in the context of the relative habitat quality of our logged forest locations, which underwent selective logging 10 years prior to sampling and have been regenerating since that time. It is possible that there is a threshold of disturbance beyond which most arboreal species cannot persist (Deere et al, 2020), and that this threshold had not been met in our study system. It is also critical to note that our logged forest sampling area is subject to hunting levels which are very low in the regional context .…”

“…Louisa experienced multiple rounds of logging between 1978 and 2008, but has since been formally protected, whereas the unlogged forest at Maliau Basin has experienced very little disturbance. Our logged forest sampling area was characterised by lower canopy height and reduced canopy cover, with fewer canopy pathways and more canopy gaps than our unlogged forest sampling area (Deere et al, 2020). Camera-trap locations in both unlogged and logged forest covered similar elevations (average 482 m, range 225-933 m).…”