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More than 200 years ago, Alexander von Humboldt reported that tropical plant species richness decreased with increasing elevation and decreasing temperature. Surprisingly, coordinated patterns in plant, bacterial, and fungal diversity on tropical mountains have not yet been observed, despite the central role of soil microorganisms in terrestrial biogeochemistry and ecology. We studied an Andean transect traversing 3.5 km in elevation to test whether the species diversity and composition of tropical forest plants, soil bacteria, and fungi follow similar biogeographical patterns with shared environmental drivers. We found coordinated changes with elevation in all three groups: species richness declined as elevation increased, and the compositional dissimilarity among communities increased with increased separation in elevation, although changes in plant diversity were larger than in bacteria and fungi. Temperature was the dominant driver of these diversity gradients, with weak influences of edaphic properties, including soil pH. The gradients in microbial diversity were strongly correlated with the activities of enzymes involved in organic matter cycling, and were accompanied by a transition in microbial traits towards slower-growing, oligotrophic taxa at higher elevations. We provide the first evidence of coordinated temperature-driven patterns in the diversity and distribution of three major biotic groups in tropical ecosystems: soil bacteria, fungi, and plants. These findings suggest that interrelated and fundamental patterns of plant and microbial communities with shared environmental drivers occur across landscape scales. These patterns are revealed where soil pH is relatively constant, and have implications for tropical forest communities under future climate change.

The elevational gradient in plant and animal diversity is one of the most widely documented patterns in ecology and, although no consensus explanation exists, many hypotheses have been proposed over the past century to explain these patterns. Historically, research on elevational diversity gradients has focused almost exclusively on plant and animal taxa. As a result, we do not know whether microbes exhibit elevational gradients in diversity that parallel those observed for macroscopic taxa. This represents a key knowledge gap in ecology, especially given the ubiquity, abundance, and functional importance of microbes. Here we show that, across a montane elevational gradient in eastern Peru, bacteria living in three distinct habitats (organic soil, mineral soil, and leaf surfaces) exhibit no significant elevational gradient in diversity ( r 2 < 0.17, P > 0.1 in all cases), in direct contrast to the significant diversity changes observed for plant and animal taxa across the same montane gradient ( r 2 > 0.75, P < 0.001 in all cases). This finding suggests that the biogeographical patterns exhibited by bacteria are fundamentally different from those of plants and animals, highlighting the need for the development of more inclusive concepts and theories in biogeography to explain these disparities.

The number of reforestation projects worldwide is increasing. In many cases funding is obtained through the claimed carbon capture of the trees, presented as immediate and durable, whereas reforested plots need time and maintenance to realise their carbon capture potential. Further, claims usually overlook the environmental costs of natural or anthropogenic disturbances during the forest’s lifetime, and greenhouse gas (GHG) emissions associated with the reforestation are not allowed for. This study uses life cycle assessment to quantify the carbon footprint of setting up a reforestation plot in the Peruvian Amazon. In parallel, we combine a soil carbon model with an above- and below-ground plant carbon model to predict the increase in carbon stocks after planting. We compare our results with the carbon capture claims made by a reforestation platform. Our results show major errors in carbon accounting in reforestation projects if they (1) ignore the time needed for trees to reach their carbon capture potential; (2) ignore the GHG emissions involved in setting up a plot; (3) report the carbon capture potential per tree planted, thereby ignoring limitations at the forest ecosystem level; or (4) under-estimate tree losses due to inevitable human and climatic disturbances. Further, we show that applications of biochar during reforestation can partially compensate for project emissions.

Understanding long-term trends in marine ecosystems requires accurate and repeatable counts of fishes and other aquatic organisms on spatial and temporal scales that are difficult or impossible to achieve with diver-based surveys. Long-term, spatially distributed cameras, like those used in terrestrial camera trapping, have not been successfully applied in marine systems due to limitations of the aquatic environment. Here, we develop methodology for a system of low-cost, long-term camera traps ( D ispersed E nvironment A quatic C ameras), deployable over large spatial scales in remote marine environments. We use machine learning to classify the large volume of images collected by the cameras. We present a case study of these combined techniques’ use by addressing fish movement and feeding behavior related to halos, a well-documented benthic pattern in shallow tropical reefscapes. Cameras proved able to function continuously underwater at deployed depths (up to 7 m, with later versions deployed to 40 m) with no maintenance or monitoring for over five months and collected a total of over 100,000 images in time-lapse mode (by 15 minutes) during daylight hours. Our ResNet-50-based deep learning model achieved 92.5% overall accuracy in sorting images with and without fishes, and diver surveys revealed that the camera images accurately represented local fish communities. The cameras and machine learning classification represent the first successful method for broad-scale underwater camera trap deployment, and our case study demonstrates the cameras’ potential for addressing questions of marine animal behavior, distributions, and large-scale spatial patterns.

Artisanal and small-scale gold mining (ASGM) is considered a leading cause of environmental degradation in the Amazon. Previous studies have only used deforestation to quantify total ASGM activity and have not considered that mining may occur multiple times in the same area. However, miners often revisit previously mined sites to extract additional gold, though the frequency and extent of this occurrence remains unquantified. This study is the first to quantify repeat ASGM in Madre de Dios, Peru, and to identify which factors best predict revisitation. We found that nearly two-thirds of total ASGM activity in this region is repeat mining. When repeat mining activity is accounted for, we found that 249 488 ha were mined from 1984–2021, which is 265% more than activity estimates based on deforestation due to initial ASGM alone. Random Forest modeling showed that the designation, region, size, and type of a mine were the most important predictors of repeat mining. We suggest that repeat mining must be considered for a more comprehensive view of ASGM activity and its environmental impacts.

Terrestrial carbon conservation can provide critical environmental, social, and climate benefits. Yet, the geographically complex mosaic of threats to, and opportunities for, conserving carbon in landscapes remain largely unresolved at national scales. Using a new high-resolution carbon mapping approach applied to Peróúúú, a megadiverse country undergoing rapid land use change, we found that at least 0.8 Pg of aboveground carbon stocks are at imminent risk of emission from land use activities. Map-based information on the natural controls over carbon density, as well as current ecosystem threats and protections, revealed three biogeographically explicit strategies that fully offset forthcoming land-use emissions. High-resolution carbon mapping affords targeted interventions to reduce greenhouse gas emissions in rapidly developing tropical nations. Significance Land use is a principal driver of carbon emissions, either directly through land change processes such as deforestation or indirectly via transportation and industries supporting natural resource use. To minimize the effects of land use on the climate system, natural ecosystems are needed to offset gross emissions through carbon sequestration. Managing this critically important service must be achieved tactically if it is to be cost-effective. We have developed a high-resolution carbon mapping approach that can identify biogeographically explicit targets for carbon storage enhancement among all landholders within a country. Applying our approach to Peróúú reveals carbon threats and protections, as well as major opportunities for using ecosystems to sequester carbon. Our approach is scalable to any tropical forest country.

Soil organic carbon (SOC) plays a critical role in major ecosystem processes, agriculture, and climate mitigation. Accurate SOC predictions are challenging due to natural variation, as well as variation in data sources, sampling design, and modeling approaches. The goal of this study was to (i) understand SOC stock distribution due to land use (restored prairie grass—PG; lawn grass—LG; and forest—F), and local topography, and (ii) assess the scalability of SOC stock predictions from the study site in North Carolina (Lat: 36°7′ N; Longitude: 80°16′ W) to the geographic extension of the Fairview soil series based on the US Soil Survey Geographic (gSSURGO) database. Overall, LG had the highest SOC stock (82 Mg ha−1) followed by PG (79 Mg ha−1) and forest (73.1 Mg ha−1). SOC stock decreased with the depth for LG and PG, which had about 60% concentrated on the surface horizon (0–23 cm), while forest had only 40%. The differences between measured SOC stocks and those estimated by gSSURGO and modeled based on land use for the Fairview series extent were comparable. However, subtracting maps of the uncertainty predictions based on the 90% confidence interval (CI) derived from the measured values and estimated gSSURGO upper and lower values (an estimated CI) resulted in a range from −17 to 41 Mg ha−1 which, when valued monetarily, varied from USD 33 million to USD 824 million for the Fairview soil series extent. In addition, the spatial differences found by subtracting the gSSURGO estimations from measured uncertainties aligned with the county administrative boundaries. The distribution of SOC stock was found to be related to land use, topography, and soil depth, while accuracy predictions were also influenced by data source.

Rapid 21st-century climate change may lead to large population decreases and extinction in tropical montane cloud forest species in the Andes. While prior research has focused on species migrations per se, ecotones may respond to different environmental factors than species. Even if species can migrate in response to climate change, if ecotones do not they can function as hard barriers to species migrations, making ecotone migrations central to understanding species persistence under scenarios of climate change. We examined a 42-year span of aerial photographs and high resolution satellite imagery to calculate migration rates of timberline--the grassland-forest ecotone-inside and outside of protected areas in the high Peruvian Andes. We found that timberline in protected areas was more likely to migrate upward in elevation than in areas with frequent cattle grazing and fire. However, rates in both protected (0.24 m yr(-1)) and unprotected (0.05 m yr(-1)) areas are only 0.5-2.3% of the rates needed to stay in equilibrium with projected climate by 2100. These ecotone migration rates are 12.5 to 110 times slower than the observed species migration rates within the same forest, suggesting a barrier to migration for mid- and high-elevation species. We anticipate that the ecotone will be a hard barrier to migration under future climate change, leading to drastic population and biodiversity losses in the region unless intensive management steps are taken.

Artisanal and small‐scale gold mining (ASGM), a wealth‐generating industry in many regions, is nonetheless a global challenge for governance and a threat to biodiversity, public health, and ecosystem integrity. In 2019, the Peruvian government mobilized a targeted, large‐scale armed intervention against illegal ASGM, which has caused deforestation and water resource degradation in this Tropical Biodiversity Hotspot. Before the intervention, the extent of waterbodies created by mining (mining ponds) was increasing by 33%–90%/year; after, they decreased by 4%–5%/year in targeted zones. Mining activity indicators showed 70%–90% abandonment. New mining activity accelerated in nearby areas outside the targeted area (pond area increases: 42%–83%; deforestation increases +3–5 km 2 /year). Far from intervention zones, mining remained stable during the study period. Our analysis demonstrates that targeted, large‐scale government intervention can have positive effects on conservation by stopping illegal mining activity and shifting it to permitted areas, thereby setting the stage for governance. Continued conservation efforts must further address the impacts of informal mining while (1) limiting environmental degradation by legal mining; (2) remediating former mining areas to reduce erosion and enable reforestation or alternative uses of the landscape; and (3) sustaining such efforts, as some miners began to return to intervention areas when enforcement relaxed in 2022.