Reduced-Impact Logging for Climate Change Mitigation (RIL-C) Can Halve Selective Logging Emissions from Tropical Forests

Selective logging causes at least half of the emissions from tropical forest degradation. Reduced-impact logging for climate (RIL-C) is proposed as a way to maintain timber production while minimizing forest damage. Here we synthesize data from 61 coordinated field-based surveys of logging impacts in seven countries across the tropics. We estimate that tropical selective logging emitted 834 Tg CO2 in 2015, 6% of total tropical greenhouse gas emissions. Felling, hauling, and skidding caused 59%, 31%, and 10% of these emissions, respectively. We suggest that RIL-C incentive programs consider a feasible target carbon impact factor of 2.3 Mg emitted per Mg of timber extracted. Operational modifications are needed to achieve this target, such as reduced wood waste, narrower haul roads, and lower impact skidding equipment. Full implementation would reduce logging emissions by 44% (366 Tg CO2 year-1) and deliver 4% of the nationally determined contributions to the Paris Climate Agreement from tropical countries, while maintaining timber supplies

Overlapping Extractive Land Use Rights Increases Deforestation and Forest Degradation in Managed Natural Production Forests

Guyana manages an estimated 5.3 million hectares of old-growth tropical forests, 29% of its total forest area, for timber extraction. Individuals and companies can apply for time-limited leases that allocate access, management, and extraction rights for timber through a concession system. In many tropical regions, including Guyana, a lack of integrated land use planning often leads to overlapping extractive and forest use rights for logging and mining. Overlapping land rights in turn create uncertainty and limit investments toward sustainable forest management, affecting deforestation and forest degradation rates. In this study, we use matched fixed-effect and difference-in-differences panel data models to quantify the impact of establishing logging tenure on deforestation and forest degradation. We assess the impact of different tenure use allocations for Guyana, a high forest cover low deforestation country, utilizing a 31-year (1990–2020) remotely sensed annual time series dataset on deforestation and forest degradation. The rate of forest loss (deforestation plus degradation) in public forests managed by the State with no authorized use allocation activities were 0.062% per year. The issuance of timber concessions increases the probability of deforestation by 33.5% and forest degradation by 8.9% compared to unallocated state forests. Forests with overlapping use rights for timber and mining had a 156% and 19.1% higher probability of deforestation and degradation relative to unallocated public forests and forests where only timber harvesting was authorized, respectively. We conclude that overlapping land use allocations result in conflicting resource use strategies that ultimately will limit sustainability and climate goals related to reducing deforestation and degradation

Detecting Gold Mining Impacts on Insect Biodiversity in a Tropical Mining Frontier with SmallSat Imagery

Gold mining is a major driver of Amazonian forest loss and degradation. As mining activity encroaches on primary forest in remote and inaccessible areas, satellite imagery provides crucial data for monitoring mining-related deforestation. High-resolution imagery, in particular, has shown promise for detecting artisanal gold mining at the forest frontier. An important next step will be to establish relationships between satellite-derived land cover change and biodiversity impacts of gold mining. In this study, we set out to detect artisanal gold mining using high-resolution imagery and relate mining land cover to insects, a taxonomic group that accounts for the majority of faunal biodiversity in tropical forests. We applied an object-based image analysis (OBIA) to classify mined areas in an Indigenous territory in Guyana, using PlanetScope imagery with ~3.7 m resolution. We complemented our OBIA with field surveys of insect family presence or absence in field plots (n = 105) that captured a wide range of mining disturbances. Our OBIA was able to identify mined objects with high accuracy (\u3e90% balanced accuracy). Field plots with a higher proportion of OBIA-derived mine cover had significantly lower insect family richness. The effects of mine cover on individual insect taxa were highly variable. Insect groups that respond strongly to mining disturbance could potentially serve as bioindicators for monitoring ecosystem health during and after gold mining. With the advent of global partnerships that provide universal access to PlanetScope imagery for tropical forest monitoring, our approach represents a low-cost and rapid way to assess the biodiversity impacts of gold mining in remote landscapes

Sustained timber yield claims, considerations, and tradeoffs for selectively logged forests

What is meant by sustainability depends on what is sustained and at what level. Sustainable forest management, for example, requires maintenance of a variety of values not the least of which is sustained timber yields (STYs). For the 1 Bha of the world's forests subjected to selective or partial logging, failure to maintain yields can be hidden by regulatory requirements and questionable auditing practices such as increasing the number of commercial species with each harvest, reducing the minimum size at which trees can be harvested and accepting logs of lower quality. For assertions of STY to be credible, clarity is needed about all these issues, as well as about the associated ecological and economic tradeoffs. Lack of clarity about sustainability heightens risks of unsubstantiated claims and unseen losses. STY is possible but often requires cutting cycles that are longer and logging intensities that are lower than prescribed by law, as well as effective use of low-impact logging practices and application of silvicultural treatments to promote timber stock recovery. These departures from business-as-usual practices will lower profit margins but generally benefit biodiversity and ecosystem services

Use of logging roads by terrestrial mammals in a responsibly managed neotropical rainforest in Guyana

Selective logging is the most widespread use of tropical forests. Building logging roads facilitates access to previously remote rainforests, and so proper management is essential for ensuring biodiversity retention in logged landscapes. Terrestrial mammals often directly use logging roads (via movement corridors, hunting or foraging), making them vulnerable to poorly managed roads. Here we explore how the presence, arrangement and use of logging roads influence terrestrial mammal occupancy and detection within a Forest Stewardship Council (FSC) certified logged forest in Guyana. We compared camera trap data from20 natural ‘game’ trails in an unlogged area, with camera trap data from 23 sites set near to or on logging roads within the Iwokrama forest. Our findings showed high occupancy within logged areas with no statistically significant difference to unlogged areas. Higher detections were noted along secondary and feeder roads compared to skid trails and the natural trails in control areas. Additionally, our data showed a negative correlation between occupancy and distance to village for a scatter hoarding rodent, most likely driven by subsistence hunting by local communities. Our results indicate that proper road management geared towards the monitoring and guarded access of logging roads, can have a positive effect on terrestrial mammal occurrence within responsibly managed rainforests

Variable shifts in bird and bat assemblages as a result of reduced-impact logging revealed after 10 years

1. Selective logging is the most widespread driver of land-use change in biodiverse and carbon-rich tropical forests. However, the effects of selective logging on bio-diversity are less than those associated with other drivers of forest degradation. A suite of recent research has shown that reduced-impact logging (RIL) results in few or no changes to biological assemblages. But because this logging technique is relatively new, most studies have only considered short-term impacts. 2. We address this research gap by quantifying changes in biodiversity assemblage as a result of RIL over the longer term. We comprehensively sampled bird and bat assemblages pre-logged, 1 year after, and 10 years after RIL in Guyana, using a before-after control-impact (BACI) sampling design. We compared bird and bat assemblages in each timeframe, and additionally appraised the impact of time since logging, and the number of trees harvested across the suite of species which we further divided between different feeding guilds, disturbance sensitivity and vertical stratification of forest use. 3. We found that 1 year after logging only minor changes could be detected, but 10 years later richness had slightly declined in some groups, while others had shown complete recovery. Nectivorous and insectivorous birds, and carnivorous bats declined in richness, while carnivorous birds, showed a clear recovery to a state akin to pre-logging. This indicates that for some niches a subtle, but long-term relaxation effect may be occurring, whereby extinction debts are realized long after the initial disturbance, while other groups have either recovered or not changed after logging. 4. Assemblage changes were also predicted by vertical stratification of forest use, with avian species using the understorey and mid–upper levels of the forest being most affected. 5. Synthesis and applications: Our study demonstrates how best practice forestry and logging can maintain healthy vertebrate populations over the long term. Forestry concessions that adopt techniques of low-harvest RIL and are managed for their long-term timber provision through extension of regeneration times beyond 10 years after harvest, are likely to benefit from the ecosystem services provided by biodiversity, while also making a valuable contribution to the global conservation estate

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs

Unifying Community Detection Across Scales from Genomes to Landscapes

Biodiversity science encompasses multiple disciplines and biological scales from molecules to landscapes. Nevertheless, biodiversity data are often analyzed separately with discipline-specific methodologies, constraining resulting inferences to a single scale. To overcome this, we present a topic modeling framework to analyze community composition in cross-disciplinary datasets, including those generated from metagenomics, metabolomics, field ecology and remote sensing. Using topic models, we demonstrate how community detection in different datasets can inform the conservation of interacting plants and herbivores. We show how topic models can identify members of molecular, organismal and landscape-level communities that relate to wildlife health, from gut microbes to forage quality. We conclude with a future vision for how topic modeling can be used to design cross-scale studies that promote a holistic approach to detect, monitor and manage biodiversity

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs