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Rising temperatures can affect stomatal and nonstomatal control over photosynthesis, through stomatal closure in response to increasing vapor pressure deficit (VPD), and biochemical limitations, respectively. To explore the independent effects of temperature and VPD, we conducted leaf-level temperature-response measurements while controlling VPD on three tropical tree species. Photosynthesis and stomatal conductance consistently decreased with increasing VPD, whereas photosynthesis typically responded weakly to changes in temperature when a stable VPD was maintained during measurements, resulting in wide parabolic temperature-response curves. We have shown that the negative effect of temperature on photosynthesis in tropical forests across ecologically important temperature ranges does not stem from direct warming effects on biochemical processes but from the indirect effect of warming, through changes in VPD. Understanding the acclimation potential of tropical trees to elevated VPD will be critical to anticipate the consequences of global warming for tropical forests.

The combination of machine learning models with satellite imagery is becoming a popular data-modeling tool for biomass prediction, supporting land cover management. This study aims to select the most suitable model to estimate tropical forest aboveground biomass in Vietnam, helping to manage and monitor changes in biomass at regional and local scales. The study identified the optimal model for estimating forest aboveground biomass and minimizing the number of input variables while achieving satisfactory model performance. A total of 59 input variables, including topography, texture features, and vegetation indices, from satellite data were used in four non-parametric algorithms and a conventional parametric model, Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Multiple Linear Regression (MLR) to predict biomass and evaluate changes aboveground biomass over 10 years in two tropical forests in Vietnam. The results indicated that all models had good estimation performance with R2 ranging from 0.615 to 0.754. For RF, MLR, and XGBoost, vegetation indices contributed the highest model weights, occupying 77.71% – 92.48%. For ANN and SVM, textural and topographic features were the majority of the model weights (73.74 – 96.36%). The RF model performed the best using 59 variables (R2 = 0.754, MAE = 78.5 Mg·ha−1, and %RMSE = 13.57%) and ten variables (R2 = 0.745, MAE = 85.8 Mg·ha−1, and %RMSE = 16.17%). The biomass map using the RF and ten variables achieved a good degree of fitting of 0.76, so it was suitable for managing and monitoring forest biomass in Vietnam. The results indicated a sharp decrease in the areas of dense and very dense forests from 2013 to 2021 and a gradual increase in 2023.

We used 11 years of census data from 450 seedling quadrats established in a 20-ha forest dynamics plot to study seedling dynamics in tree species of a tropical seasonal rainforest in Xishuangbanna, southwestern China. We found that overall seedling recruitment rate and relative growth rate were higher in the rainy season than in the dry season. Both the recruitment rate of seedlings from canopy tree species (two species) and the relative growth rate of seedlings from understory species (nine species) were higher in the rainy season than in the dry season. However, in the rainy season, the recruitment rate of seedlings was higher for canopy tree species than for understory tree species. In addition, relative growth rate of seedlings was higher in the canopy species than in understory seedlings in the dry season. We also observed that, in both rainy and dry seasons, mortality rate of seedlings was higher for canopy species than for understory species. Overall, canopy tree species appear to have evolved a flexible strategy to adapt to the seasonal changes of a monsoon climate. In contrast, understory tree species seem to have adopted a conservative strategy. Specifically, these species mainly release seedlings in the rainy season and maintain relatively stable populations with a lower mortality rate and recruitment rate in both dry and rainy seasons. Our study suggests that canopy and understory seedling populations growing in forest understory may respond to future climate change scenarios with distinct regeneration strategies.

This study presents novel findings on the Psocoptera (Insecta) fauna of Vietnam, contributing to the understanding of biodiversity in the region. Psocoptera specimens were collected from Tam Dao National Park during October 2023, adding 19 new species to the existing list. These discoveries include species previously unknown to Vietnam and some new to the Indochina Peninsula and continental Asia. Material examination and species identification were conducted following established methodologies, with specimens deposited at the National Museum of Natural History, Sofia, Bulgaria. The findings underscore the importance of continued research efforts in documenting and understanding the psocid fauna of Vietnam, particularly in tropical forest ecosystems.

Coconut farming contributes to the livelihoods of millions of people in tropical countries but is less frequently considered as a threat to biodiversity compared to other palm commodities such as oil palm. The expansion of coconut farming alongside other smallholder agriculture in Sulawesi, Indonesia, is of potential concern as the region is a centre of species endemism. We studied bird diversity and community structure in forests, coconut palm plantations and mixed farmland in Gorontalo Province, northern Sulawesi. Forest and non-forest sites supported similar numbers of species overall, but compared to agricultural areas, forest sites had communities that were more diverse and more even (i.e. different species were present at similar abundances). We found far fewer endemic species in agricultural areas compared to forests, and the communities in palm plantations and mixed farmland sites were dominated by generalist birds, with few indicator taxa. Nevertheless, there was a higher number of endemic species in coconut palm plantations than in mixed farmland sites. These findings mirror patterns of biotic homogenization documented elsewhere in the Wallacea centre of endemism, and imply that coconut palm plantations have comparable biodiversity value to other farmland systems. Increased protection of lowland forests and improved management of coconut farms could be important for supporting the conservation of the endemic birds of Sulawesi in the long term, but this warrants further study.

Forest above-ground biomass (AGB) is one of the critical measures of forest resources. Therefore, it is crucial to identify a reliable method to estimate the AGB, especially in the tropics, where forest ecosystems are exposed to several depleting factors, including deforestation, climate change and replacing natural forests with palm oil tree plantations. We investigated the digital elevation data over the forest and uses an artificial intelligence-based approach to develop a method for quick and cost-effective assessment of the AGB. The study was conducted in the tropical peatland rainforest of Brunei Darussalam. The Shuttle Radar Topography Mission (SRTM) elevation data product and Light Detection and Ranging (LiDAR) digital elevation data were used. A linear regression (LR) model and three different machine learning (ML) algorithms, i.e., Random Forest (RF), Artificial Neural Network (ANN) and Support Vector Machines (SVM), were tested and compared. As model inputs, the SRTM elevation and distance from the peat dome’s center, a feature of a peatland swamp forest, were used. ML methods were trained on the samples taken from the LiDAR elevations. The validation results showed that the SVM was the best method to predict AGB in the study area with R2 = 0.70, RMSE = 83.65 Mg ha-1, and MAE = 74.43 Mg ha-1, which in relative terms corresponds to approximately 6% of the AGB of the forest of interests. This study demonstrated the potential of ML algorithms in AGB estimation based on canopy height derived from the InSAR-based DEM in tropical forests.

Agroforestry is increasingly promoted to support biodiversity conservation by increasing tree cover in agricultural landscapes, but the extent to which landscape context affects how benefits accrue remains uncertain. We used shade-coffee systems to ask how the proximity and extent of forest and forest-agriculture mosaic in the landscape influenced bird communities in 160 coffee plantations that differed in coffee plant density and shade tree richness and abundance in two departments of Colombia with differing regional forest cover. Our findings suggest that regional forest cover and landscape conditions can mediate the response of birds to local habitats on plantations. Avian richness and community completeness was positively related to the amount of forest-agriculture mosaic within landscapes surrounding coffee plantations only within the comparatively forested department of Antioquia (mean 32 % regional forest cover), particularly where plantations had high richness and abundance of trees. In the largely deforested department of Cauca (mean 1 %), neither distance to forest nor cover by forest-agriculture mosaics explained avian richness and community completeness, both of which were positively related only to local tree richness and abundance. We show that biodiversity benefits from increasing habitat quality at local and landscape scales, and habitat quality within plantations becomes increasingly influential as the amount of habitat in the broader landscape declines. Our results emphasize the role of landscape context in conservation planning to promote biodiversity in coffee-growing regions.

Abstract Forest and landscape restoration are increasingly popular nature‐based solutions to mitigate climate change and safeguard biodiversity. Restoration planning and monitoring implies that a reference ecosystem has been defined to which the restored site can be compared, but how to best select such reference? We tested three different potential natural vegetation (PNV) maps of the same areas in Kenya and Uganda for their utility as ecological references with independent data that were not used when those maps were made. These independent datasets included presence observations of woody species from 76 sites in forest reserves in Kenya and Uganda, and classification of surveyed species into a system that included “forest‐only” and “nonforest‐only” ecological types. Our tests show that (1) the three vegetation maps largely agree on the environmental envelopes/ranges within which forests occur. (2) There are large differences in how well the maps predict the presence of forest‐only species. (3) Two maps, based on empirical observations (V4A and White), predict forest types well, whereas the third, based on climate envelopes only (NS), performs poorly. (4) A large area in Uganda is potentially in one of two alternative stable states. We conclude that it is possible to evaluate the utility of PNV maps at a more detailed scale than the level of biome and ecoregion. This indicates that it is possible to map PNV at scales required for reference for restoration and management of forest vegetation. We recommend that empirically based maps of potential natural vegetation are used in restoration planning (biome and PNV maps based on climate envelopes alone may be unreliable tools) as a baseline model for predicting the distribution of reference ecosystems under current and future conditions. It could conveniently be done by deconstructing the existing biome maps, supported by rapid botanical surveys.

Tree-related microhabitats (TreMs) describe the microhabitats that a tree can provide for a multitude of other taxonomic groups and have been proposed as an important indicator for forest biodiversity. So far, the focus of TreM studies has been on temperate forests, although the tropics provide a large forest area, with different types of forest and a high diversity of tree species, some of them with exceptionally high numbers of TreMs. In this study, TreMs in the lowland tropical forests of the Chocó (Ecuador) and in the mountain tropical forests of Mount Kilimanjaro (Tanzania) were surveyed. Our results extend the existing typology of TreMs of Larrieu et al. (2018) to include tropical forests and enabled a comparison of the relative recordings and diversity of TreMs between tropical and temperate forests. A new TreM form, Root formations, and three new TreM groups, concavities build by fruits or leaves, dendrotelms, and root formations, were established. In total, 15 new TreM types in five different TreM groups were specified. The relative recordings of most TreMs were similar between tropical and temperate forests. However, ivy and lianas, and ferns were more common in the lowland rainforest than in temperate forests, and bark microsoil, limb breakage, and foliose and fruticose lichens in tropical montane forest than in lowland rainforest. Mountain tropical forests hosted the highest diversity for common and dominant TreM types, and lowland tropical forest the highest diversity for rare TreMs. Our extended typology of tree-related microhabitats can support studies of forest-dwelling biodiversity in tropical forests. Specifically, given the ongoing threat to tropical forests, TreMs can serve as an additional tool allowing rapid assessments of biodiversity in these hyperdiverse ecosystems.

Habitat loss and fragmentation in tropical regions are major threats to the persistence of endangered Malay tapir (Tapirus indicus). The Malay tapir distribution is largely constrained to fragmented habitats inside protected areas. However, it is unclear how the spatial patterns of habitat fragmentation affect its relative abundance. Here, we investigated the effects of habitat fragmentation on Malay tapir relative abundance in Thailand. We first quantified the spatial patterns of habitat fragmentation within nine of Thailand’s protected areas. Second, we assessed the relationship of fragmentation metrics and relative abundance of Malay tapirs. Third, we identified the relative importance of the fragmentation metrics in explaining relative abundance. We found that tapir abundance remained unexpectedly high in the Southern forest complex despite the fact that tapir habitats were significantly more fragmented there than in the protected area in the western forest complex (p < 0.05). Additionally, we found a significantly negative relation with clumpiness index (R2 = 0.51, p < 0.05). This suggests that other factors may also be influencing their populations, so that the Southern protected areas provide preferred habitat with higher relative proportions of moist evergreen forest, large habitat patch size, precipitation, and elevation. It highlights the importance of interconnected habitat for tapirs, and the benefit of conservation efforts in small, less recognized protected areas.

Urbanization is resulting in habitat loss and fragmentation around the world, but its effects on biodiversity remain poorly understood. We investigated how the increase of urban cover surrounding nine Brazilian Atlantic forest reserves (14 ha - 1058 ha) affects the taxonomic, functional and phylogenetic diversity of bird communities, considering forest and non-forest species separately. Using a multi-scale local landscape approach, we estimated the percentage of urban cover in circular buffers of varying radii (200–1000 m). We calculated 10 complementary metrics of bird diversity and modelled them against the percentage of urban cover using generalized additive models. Urbanization had a negative, non-linear impact on the taxonomic diversity of bird communities, with a sharp decrease of up to 50 % in the effective number of rare, typical and dominant species in landscapes with 20–40 % of urbanization. This decrease was not restricted to forest species (urban avoiders), but also affected non-forest ones (urban utilizers and dwellers). The impact of urbanization on functional and phylogenetic diversity were less evident, suggesting that the vulnerability to urbanization has a weak phylogenetic and phenotypic signal. We conclude that urbanization impacts a broad spectrum of bird clades and traits and drastically reduce the taxonomic diversity of bird communities.

Selective logging can impact tree composition and the long-term sustainability of forests. Studying the ecological consequences of logging practices is crucial for guiding forest management strategies aiming at maintaining ecological integrity and supporting landscape-level conservation goals. We investigated the consequences of very low-intensity selective logging in multiple tree life stages across a logged forest chronosequence in Gabon. We found that species composition differed between logged and unlogged forests at all life stages (seedlings, saplings, and adults), which were most pronounced in the understory of older forests (logged 10 years prior) compared to unlogged areas. However, logging explained a small portion of the variation in species composition (

The Atlantic Forest is a global biodiversity hotspot and a significant provider of ecosystem services to 65% of the Brazilian population. Due to being highly threatened, it is protected by federal law 11,428/2006, which establishes forest use restrictions based on native vegetation successional stages in the Atlantic Forest, with more advanced stages receiving more protection. The classification parameters are established at the state level. However, the parameters employed to classify forest fragments in different successional stages are subjective and imprecise, negatively impacting environmental permitting and related offset policies. Here, we critically assessed the major limitations in applying the 11,428/2006 law and presented alternatives for establishing a more transparent, applicable, legally safe, and effective protocol for identifying the conservation value of forest fragments. We also highlight problems related to sampling, indicators, and methodologies and present guidelines for revising the parameters for applying the Atlantic Forest law and associated state-level resolutions. We suggest an inclusive two-step analysis based on vegetation structure, forest cover history, biodiversity, ecosystem services (social), and landscape indicators. By employing a more technological approach and transferring part of the assessment responsibility to the state-level environmental agencies instead of allowing self-declared reports by landowners, our proposal focuses on the potential for evaluating ecological integrity among different successional classes by forest types. As nearly 90% of the remaining Brazilian Atlantic Forest is located within private lands, improving this legal instrument is essential for protecting the vulnerable biodiversity of this unique and threatened biome.

Scorpions are an important predator group in the habitats where they live, due to their voracity. However, their predatory habits are not well recorded, particularly in Amazonian species. Here we report four intraspecific predation events involving Tityus metuendus Pocock, 1987. In all cases, larger individuals acted as predators of smaller ones. These are the first reports of cannibalism involving scorpions in the Brazilian Amazon. Our findings are important to allow a better understanding of intraspecific interactions in tropical scorpion assemblages.

ABSTRACT: Brazil's Amazon region contains the largest tropical forest resource in the world. About 1,300,000 ha has been exploited each year without planning. To improve the current practice, a computer program has been developed to investigate various management operations. BRAMA - an interactive expert system, simulates management activities and stand growth for timber production. The system agrees very closely with the existing knowledge of tropical forest management, that requires complex and extensive data. This software is written In VS FORTRAN as a forest management planning tool.

Understanding disturbances that are of significant significance requires a critical focus on preventing forest degradation and addressing problems related to vegetation loss. Hence, the primary objective of this work was to examine the structure of species and the patterns of regeneration at various density gradients within the Achanakmar-Amarkantak Biosphere Reserve in India. This study involved the selection of one closed site (CS) and one open site (OS) from both the Mixed Sal Forest (MSF) and the Pure Sal Forest (PSF). In order to ascertain population structure and regeneration status, plants were classified into seedlings, saplings, and adults based on their Girth at breast height (GBH). The results of our study revealed that the population density of seedlings, saplings, and trees was higher in MSFCS (49250, 980, and 920 ind/ha) compared to PSFCS (41500, 740, 890 ind/ha), MSFOS (16750, 580, and 370 individuals ind/ha), and PSFOS (9750, 180, and 334 ind/ha). Both forests exhibited a reverse-J shaped curve in the CS and an interrupted reverse-J shaped curve in the OS of overall tree species. Nevertheless, the distribution curve at the species level displayed diverse patterns. For instance, Shorea robusta displayed irregular shapes in the OS of both forests, while Terminalia tomentosa displayed a bell-shaped GBH density distribution population curve across all the sites. Differences in regeneration status were observed among different tree species. At the four sites, 18.75% of the species showed good regeneration, 21.87% showed fair regeneration, and a substantial portion, 35.94%, displayed poor to no regeneration. Additionally, 23.44% of the species showed new regeneration. Among these species, Diospyros melanoxylon and Syzygium cumini showed strong regeneration capabilities, while Shorea robusta shown moderate regeneration potential. In the future, the population structure, dominance, and richness of the present tree community may undergo changes. Hence, it is imperative to conduct study on the survival of seedlings and use appropriate management techniques in order to guarantee the long-term viability of the forests.

The tropical forest plays an important role in ecosystem services, yet anthropological activities have changed the ecological conditions. Thus, this research was designed to reveal the species richness and diversity in secondary forests, including lifeform alteration. The 50 perpendicular plots were placed in both forests, with 25 for each. The study revealed that the secondary forest represents a stage of ecological succession in which species richness and diversity decreased. Additionally, the composition of life forms in the secondary forest changed, with dominant herbs indicating a more dynamic vegetation due to shifting ecological conditions. Species classified as Threatened have disappeared due to human activities in the forest. However, the secondary forest has provided a habitat for certain species, including those with conservation status, such as Threatened or Extinct, to thrive and colonize. Approximately 15.7% of species exclusively thrive in secondary forests, including Antiaropsis uniflora C.C.Berg. Therefore, to promote sustainable forest management, this study suggests monitoring the species in secondary forests, particularly since the use of forests has traditionally been determined by local communities, including in restricted forest areas. Moreover, the local government could officially designate traditional forest use, thereby allowing restricted forests to be conserved as old-growth forests.

Precise and prompt information on forest disturbances in the tropics is critical to support law enforcement and protect tropical forests. In 2023, medium resolution ALOS-2 ScanSAR data (∼100 m spatial resolution) was made available for Southeast Asia, marking the first freely accessible large-area L-Band dataset. We assessed its potential for large-area forest disturbance mapping and its combination with high-resolution C-band Sentinel-1 data (∼20 m spatial resolution). We mapped forest disturbances in Sumatra, Indonesia for the year 2021 based on ALOS-2 ScanSAR data and Sentinel-1 data separately, and subsequently combined the mapped disturbances. Forest disturbances detected by both C-band and L-band SAR using a probabilistic change algorithm were combined at the product level by merging both sets of detections. The added benefit of combining both sensors was particularly evident in higher detection rates, as indicated by an improved producer accuracy (78.9 ± 11.9 %) compared to detections based on single sensor ALOS-2 ScanSAR (40.8 ± 6.3 %) and Sentinel-1 data (63.3 ± 9.6 %). Both combined and single sensor detections showed negligible false detections. ALOS-2 ScanSAR showed advantages for overcoming limited capability of Sentinel-1 to detect large-sized disturbance events characterized by post-disturbance tree remnants, occurring at locations with large-scale agricultural clearings. The medium resolution of approximately 100 m restricts the detection capability of ALOS-2 ScanSAR data for small-scale disturbances, resulting in missed detections. ALOS-2 ScanSAR detections showed a delay of up to 17.8 days compared to detections based solely on Sentinel-1 data. Combining ALOS-2 ScanSAR and Sentinel-1-based disturbances resulted in improved detection timeliness, with an average improvement of up to 16.5 days compared to Sentinel-1-based detections. Furthermore, we observed improved detection rates for our ALOS-2 ScanSAR-based detections compared to those of the ALOS-2 ScanSAR-based JICA-JAXA Forest Early Warning System in the Tropics (JJ-FAST) forest disturbance alerting product. This suggests that the potential of ALOS-2 ScanSAR data in operational forest monitoring systems is not currently fully realized. Comparing the SAR-based disturbance detections from this study with existing optical-based forest disturbance products (GFC and GLAD-L) suggested improved detection accuracies by overcoming sensor-specific omission errors when using combined SAR and optical data. The demonstrated potential of L-Band ALOS-2 ScanSAR data for improving operational forest monitoring efforts using C-band radar and optical satellites is expected to be amplified by upcoming L-Band satellite missions like NiSAR (2024) and ROSE-L (2028), which will provide freely accessible L-Band data with higher spatial resolution.

The assessment of environmental sustainability is of utmost importance for the forests and plantations in Borneo, given the critical need for environmental protection through the identification and mitigation of potential risks. This study was conducted to assess the environmental sustainability of tropical forest and plantations landscape, a case study in northern Sabah, Malaysian Borneo. Applications of the latest high-resolution multi-sensor remote sensing and geospatial MCDA are cost-effective and useful for large-scale environmental sustainability assessment. The land use land cover (LULC) of the study area was mapped with synergistic use of Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical and high-resolution PlanetScope satellite imageries, resulting in overall accuracy of 87.24%. Five sustainability indicator layers: slope erosion protection, river buffer, landscape connectivity and quality, high conservation value (HCV), and water turbidity were developed from the LULC map, ancillary datasets of SRTM, and forest operation basemap with reference to standards from the Environment Protection Department (EPD), Roundtable on Sustainable Palm Oil (RSPO), and Forest Management Plan (FMP) for the analysis using multi-criteria decision analysis (MCDA) model. The results revealed that overall, the study areas are in the high sustainability category at 61%, medium at 31%, and low at only 8%. We analyzed the environmental sustainability of five land use boundaries, and the results showed that Industrial Tree Plantations (ITP) and Village Reserve are mostly in the high category. Meanwhile, oil palm plantations, rubber plantations, and forest reserve (FR) are the majority in the medium category. Both oil palm and rubber plantations are a majority in the medium class due to monocropping land use type having low landscape connectivity and quality individual sustainability indicator layer. The study presented the concept of use of multi-sensor remote sensing for LULC mapping with geospatial MCDA for environmental sustainability assessment useful to stakeholders for improving the management plan also contributing toward the progress of achieving UNSDGs and addressing REDD+.

Co-management is a promising forest governance strategy that integrates local communities’ traditional rights and forest dependencies while aiming to improve forest cover and ecosystem health. Bangladesh, facing high deforestation rates and limited per capita forest area, has implemented co-management initiatives since 2003 to restore forest cover and support the livelihoods of forest-dependent communities. While the socio-economic impacts of co-management are well studied, its effects on forest cover remain underexplored. This study addresses that gap by using three common spectral vegetation indices (NDVI, EVI, and MSAVI), calculated from Landsat 7 data, to analyze forest cover changes in five major protected areas under co-management. The results indicated that dense forest cover (41–71%) was initially prevalent in these areas, but a significant decline occurred between 2004 and 2015, with slope values ranging from −3.7 to −0.96. In contrast, the non-co-managed control site exhibited a much smaller decline (slope: −0.48 to −0.62) across all indices. Notable increases in agricultural land and forest–agriculture mosaics were also observed in the protected areas under co-management. Global Forest Watch data further confirmed substantial forest cover loss, particularly in CWS (158.77 ha) and SNP (0.49 ha). These findings highlight the need to reassess co-management strategies to address ongoing forest degradation.

Butterfly wing scales feature complex nanostructures that influence wing coloration and various mechanical and optical properties. This configuration plays a key role in ecological interactions, flight conditions, and thermoregulation, facilitated by interactions with environmental electromagnetic energy. In tropical forests, butterflies occupy distinct vertical habitats, experiencing significant light and temperature variations. While wing nanostructures have been widely studied, their variation across different vertical flight preferences remains underexplored. This study investigates the wing nanostructures of 12 tropical butterfly species from the Nymphalidae family, focusing on their optical, morphological, and thermal properties across different forest strata. We analyzed the optical response through diffuse reflectance in the UV, Vis, and NIR ranges, correlating these findings with nanostructural configuration and thermal stability using thermogravimetric analysis (TGA). Our results reveal a significant correlation between flight stratification and wing optical responses, alongside distinct nanostructural features within each stratum. This study demonstrates the variability in butterfly wing nanostructures along the vertical stratification of the forest to cope with environmental conditions, raising new questions for future research on eco-evolutionary flight and thermal adaptations. Additionally, this underscores the importance of understanding how these structural adaptations influence butterfly interactions with their environment and their evolutionary success across different forest strata.

Mapping forest canopy height is critical for climate modeling and forest management, and tropical forests present unique challenges for remote sensing due to their dense vegetation and complex structure. The advent of ICESat-2 and GEDI, two advanced lidar datasets, offers new opportunities for improving canopy height estimation. In this study, we used footprint-level canopy height products from ICESat-2 and GEDI, combined with features extracted from Landsat-8, PALSAR-2, and FABDEM products. The AutoGluon stacking ensemble learning algorithm was employed to construct inversion models, generating 30 m resolution continuous canopy height maps for the tropical forests of Puerto Rico. Accuracy validation was performed using the high-resolution G-LiHT airborne lidar products. Results show that tropical forest canopy height inversion remains challenging, with all models yielding relative root mean square errors (rRMSE) exceeding 0.30. The stacking ensemble model outperformed all base learners, and the GEDI-based map had slightly higher accuracy than the ICESat-2-based map, with RMSE values of 4.81 and 4.99 m, respectively. Both models showed systematic biases, but the GEDI-based model exhibited less underestimation for taller canopies, making it more suitable for biomass estimation. The proposed approach can be applied to other forest ecosystems, enabling fine-resolution canopy height mapping and enhancing forest conservation efforts.

Advances in sequencing technologies and bioinformatics have led to breakthroughs in the study of virus biodiversity. Millipedes (Diplopoda, Myriapoda, Arthropoda) include more than 12,000 extant species, yet data on virus diversity in Diplopoda are scarce. This study aimed to explore the virome of the millipedes collected in the Dong Nai Biosphere Reserve in Vietnam. We studied 14 species of millipedes and managed to assemble and annotate the complete coding genomes of 16 novel viruses, the partial coding genomes of 10 more viruses, and several fragmented viral sequences, which may indicate the presence of about 54 more viruses in the studied samples. Among the complete and partial genomes, 27% were putative members of the order Picornavirales. Most of the discovered viruses were very distant from the viruses currently present in the relevant databases. At least eight viruses meet the criteria to be recognized as a new species by the International Committee on Taxonomy of Viruses, and, for two of them, a higher taxonomic status (genus and even family) can be suggested.

Abstract Protected areas (PAs) are central to sustainability targets, yet few evaluations explore outcomes for both conservation and development, or the trade‐offs involved. We applied counterfactual analyses to assess the extent to which PAs maintained forest cover and influenced well‐being across >31,000 villages in Sumatra and Kalimantan, Indonesia. We examined multidimensional aspects of well‐being, tracking education, health, living standards, infrastructure, environment, and social cohesion in treatment and control villages between 2005 and 2018. Overall, PAs were effective at maintaining forest cover compared to matched controls and were not detrimental to well‐being. However, impacts were highly heterogeneous, varying by island and strictness of protection. While health, living standards, and infrastructure aspects of well‐being improved, education access, environmental conditions, and social cohesion declined. Our analysis reveals the contexts through which individual PAs succeed or fail in delivering multiple benefits and provides insights into where further on‐ground support is needed to achieve conservation and development objectives.

Abstract Understanding how tropical forests respond to abiotic environmental changes is critical for preserving biodiversity, mitigating climate change, and maintaining ecosystem services in the coming century. To evaluate the relative roles of the abiotic environment and human disturbance on Central African tree community composition, we employ tree inventory data, remotely sensed climatic data, and soil nutrient data collected from 30 1‐ha plots distributed across a large‐scale observational experiment in forests that had been differently impacted by logging and hunting in northern Republic of Congo. We show that the composition of Afrotropical plant communities at this scale responds to human disturbance more than to climate, with particular sensitivities to hunting and distance to the nearest village (a proxy for other human activities, including tree‐cutting and gathering). These findings contrast neotropical predictions, highlighting the unique ecological, evolutionary, and anthropogenic history of Afrotropical forests.

Abstract Fires were historically rare in tropical forests of West and Central Africa, where dense vegetation, rapid decomposition, and high moisture limit available fuels. However, increasing heat and drought combined with forest degradation and fragmentation are making these areas more susceptible to wildfires. We evaluated historical patterns of Moderate Resolution Imaging Spectroradiometer active fires in African tropical forests from 2003 to 2021. Trends were mostly positive, particularly in the northeastern and southern Congo Basin, and were concentrated in areas with high deforestation. Year‐to‐year variation of fires was synchronized with increasing temperature and vapor pressure deficit. There was anomalously high fire activity across the region during the 2015–2016 El Niño. These results contrast with the drier African woodlands and savannas, where fire has been decreasing. Further attention to fires in African tropical forests is needed to understand their global impacts on carbon dynamics and their local implications for biodiversity and human livelihoods.

Abstract El Niño/Southern Oscillation (ENSO) is the main climate mode that drives the interannual variability in climate and consequently vegetation greenness. While widespread green‐up has been reported and examined in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used four remote sensing‐based leaf area index (LAI) products to investigate changes in vegetation greenness during the 2015/16 El Niño in tropical Asia. We found a strong green‐up during the 2015/16 El Niño in tropical Asia, with its regional average LAI stronger than that of tropical America. The drivers for the green‐up vary across the region, with radiation being the main driver for continental tropical Asia, and temperature and soil water anomalies in the west and east parts of maritime tropical Asia, respectively. These findings provide important insights into the response of tropical Asia's vegetation to extreme climate anomalies.

Abstract Synthesising knowledge on carbon stocks is an essential tool for understanding the potential of forests to store carbon and its drivers. However, such a synthesis needs to be constructed for the Atlantic Forest due to various methodological approaches and biogeographic heterogeneity. Thus, here we conducted a bibliographic search (2000 to 2021) on carbon stocks in the biomass and necromass of Atlantic Forest ecosystems to understand the variation in stocks and their explanatory variables. Drivers included spatial (altitude, forest size) and climatic (precipitation and temperature) variables, and successional stages. Based on the information in 46 articles, biomass exhibited the highest carbon stock (96%), in Mature Forests (MF), with an average of 125.34±40.3 MgC.ha-1, whereas Secondary Forests (SF) stored 82.7±38.2 MgC.ha-1. The carbon in the necromass varied from 1.63 to 11.47 MgC.ha-1, with SF exhibiting 3.90±2.73 MgC.ha-1 and MF 4.31±2.82 MgC.ha-1. Only average annual precipitation and successional stage positively explained the carbon in Atlantic Forest. This research clarifies the function and potential of Atlantic Forest fragments for storing carbon and reinforces need for conserving mature forest patches throughout the biome since one hectare of mature forest can store almost twice as much carbon as one hectare of secondary young patches.

Abstract Tropical forest phenology directly affects regional carbon cycles, but the relation between species‐specific and whole‐canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large‐scale impacts of human‐induced climate change. Ground‐based long‐term (1937–1956) phenological observations of 140 tropical tree species are recovered, species‐specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand‐level canopy dynamics. High phenological variability within and across species and in climate–phenology relationships is observed. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species‐specific decoupling in time along a bi‐modal seasonality. The majority of the species remain evergreen, although central African forests experience relatively low rainfall. Annually a maximum of 1.5% of the canopy is in leaf senescence or leaf turnover, with overall phenological variability dominated by a few deciduous species, while substantial variability is attributed to asynchronous events of large and/or abundant trees. Our results underscore the importance of accounting for constituent signals in canopy‐wide scaling and the interpretation of remotely sensed phenology signals.

Here, we examine the effects of wildfires on the soil seed bank of a terra firme forest in the eastern Amazon. This seed bank is described via community-level attributes across forest stands exposed to wildfires once or twice, as well as across unburned, old-growth forest stands. A total of 2345 seeds germinated (837.5 seeds/m2). Across all three forest habitats, the soil seed bank was dominated by a small set of light-demanding species, with two to three species accounting for over 80% of all seeds. On the other hand, the seed bank of all habitats completely lacked seeds from the old-growth flora. Wildfires posed no effects relative to seed density and species richness. However, fire (1) reduced beta diversity, (2) caused an 8% increase in herb abundance and a 4% increase in the number of seeds produced by short-lived pioneers, and (3) resulted in a slight impact on taxonomic species composition. Our results suggest that the soil seed bank, while exhibiting high seed densities, is naturally species poor and, thus, relatively resistant to the first fire events. This implies that the recovery of fire-degraded forests will rely on vertebrate-dispersed seeds coming from any remaining well-preserved old-growth forest stands that are present in the landscape and are highly vulnerable to fire.

Invasive species are one of the five main causes of biodiversity loss, along with habitat destruction, overexploitation, pollution, and climate change. Numbers and species of invasive organisms represent one of the first barriers to overcome in ecological conservation programs since they are difficult to control and eradicate. Due to the lack of records of invasive exotic species in Panama, this study was necessary for identifying and registering the documented groups of invasive species of the Chordates and Arthropod groups in Panama. This exhaustive search for invasive species was carried out in different bibliographic databases, electronic portals, and scientific journals which addressed the topic at a global level. The results show that approximately 141 invasive exotic species of the Arthropoda and Chordata phyla have been reported in Panama. Of the 141 species, 50 species belonged to the Arthropoda phylum and 91 species belonged to the Chordate phylum. Panamanian economic activity could facilitate the introduction of alien species into the country. This study provides the first list of invasive exotic chordate and arthropod species reported for the Republic of Panama.

The logging intensity often does not take into account the spatial heterogeneity of the forest volume of commercial native species in the Brazilian Amazon. This study aims to evaluate the spatio-temporal heterogeneity distribution by assessing logging intensity and its effects on the volumetric stock and abundance of commercial species, with a focus on sustainable management practices. This study was conducted in the Saracá-Taquera National Forest in the Brazilian Amazon. Forest inventory data, elevation, and PlanetScope satellite images were integrated into a geographic information system. The information was aggregated into regular 1-hectare cells for the times before, during, and after logging (t0, t1, and t2). The unsupervised classification algorithm k-means with four clusters was used to analyze heterogeneity. Before logging, areas with higher commercial volumes were distant from water bodies, while areas with lower elevation had lower wood stocks. Logging intensity was generally low, concentrating on a few trees per hectare. Logging in the study area revealed a heterogeneous spatial distribution by intensifying in areas with the highest wood stocks. These results suggest that, in addition to the recommended logging intensity according to legislation, forest heterogeneity should be considered by the manager, promoting adaptive strategies to ensure the conservation of forest resources.

Launched in 2015, the large-scale initiative Indonesian Biodiversity Discovery and Information System (IndoBioSys) is a multidisciplinary German-Indonesian collaboration with the main goal of establishing a standardised framework for species discovery and all associated steps. One aspect of the project includes the application of DNA barcoding for species identification and biodiversity assessments. In this framework, we conducted a large-scale assessment of the insect fauna of the Mount Halimun-Salak National Park which is one of the largest tropical rain-forest ecosystems left in West Java. In this study, we present the results of processing 5,034 specimens of Phoridae (scuttle flies) via DNA barcoding. Despite limited sequencing success, we obtained more than 500 clusters using different algorithms (RESL, ASAP, SpeciesIdentifier). Moreover, Chao statistics indicated that we drastically undersampled all trap sites, implying that the true diversity of Phoridae is, in fact, much higher. With this data release, we hope to shed some light on the hidden diversity of this megadiverse group of flies.

IntroductionTerrestrial mammals play a pivotal role in tropical forest ecosystems, representing a rich and functionally diverse component of these biomes. However, they confront formidable threats globally, such as hunting, habitat loss, and fragmentation, amidst the expansion of human-altered landscapes in tropical regions. Understanding the impacts of these changes on mammal communities is crucial for designing effective conservation interventions. Northeast India's tropical forests, a biodiversity hotspot, host a diverse array of mammalian fauna. The primary challenge faced by these species involves anthropogenic activities leading to the shrinkage and fragmentation of forested habitats.MethodologyIn this study, we conducted systematic camera trapping in Mehao Wildlife Sanctuary (WLS) to assess mammal status and distribution. Employing single-season occupancy models, we evaluated factors influencing mammalian species' detection probability and spatial utilization within the landscape. ResultsThe study documented 27 mammalian species, with 12 identified as "threatened" on the IUCN Red List. Species like clouded leopard, marbled cat, Gongshan muntjac, red goral, Mishmi takin, and sambar were recorded but observed infrequently. Notably, we reported the Asiatic brush-tailed porcupine's first sighting in Mehao. Our findings revealed that undisturbed forest habitats were preferred by all species. Mainland serow dominated most of the sanctuary's area, followed by northern red muntjac, yellow-throated marten, and masked palm civet.DiscussionThe response of mammalian species to ecological and anthropogenic covariates varied significantly, underscoring the necessity for species-specific management strategies alongside a landscape-scale conservation approach. These outcomes emphasize the urgency of managing and safeguarding rare and elusive mammalian species within and around Mehao WLS.

Bark conductance to water vapor (gbark) is an important determinant of drought tolerance in tropical plants. Examining species differences in bark conductance can provide useful information about the resilience of tropical trees to ongoing climate change. Values of gbark are positively related to stem photosynthetic rate in desert species, showing that increased stem photosynthesis capacity is associated with increased bark conductance to water vapor. We determined whether stem morphometric traits, bioclimatic variables (e.g., temperature and precipitation), and shared evolutionary history help explain variation in gbark among tropical plant species. We surveyed 94 species (90 trees and 4 liana species) from lowland and mid-elevation forests in Panama and estimated gbark, stem diameter, specific stem area, bark thickness, sapwood area, and bark and wood density. Climate data were extracted from CHELSA 2.1 and Instituto de Meteorología e Hidrología de Panamá. Phylogenetic signal was estimated using Blomberg’s K statistic and Pagel’s λ. Bark conductance decreased with an increase in bark thickness and relative bark thickness, and was positively related to mean annual precipitation and mean annual temperature. We also determined the temperature response of gbark of six plant species (five trees and one liana) from a lowland forest. In all six species, gbark decreased as air temperature increased from 20 to 50°C. There was a significant phylogenetic signal in gbark, with closely related species resembling each other more than distantly related species. We conclude that interspecific differences in gbark of Neotropical tree species depend on all three factors studied: stem morphometry, climate, and evolutionary history.

ABSTRACT Bird droppings are an unusual food resource for coprophagous insects and used mostly by opportunistic decomposers. Among them, dung beetles feed mainly on dung, although the species differ in their trophic plasticity. Here we report a record of a dung beetle, Canthidium cf. gracilipes, reaching and manipulating the dropping of a passeriform bird, Dendrocincla fuliginosa (Dendrocolaptidae). The behavior was observed in an urban forest fragment located in the Amazonian city of Manaus, Brazil. Two hours after the bird defecated, the dung beetle reached the dropping and started manipulating them with its fore- and hindlegs. It did not eat the dung, though. For a clear understanding of the relationships between bird droppings and Amazonian dung beetles, it will be important to perform standardized experiments with a wide variety of native dung and carrion types.

Abstract Coats-of-arms representing municipal counties express local patterns of rural economics, natural resource and land use, features of the natural capital, and the cultural heritage of either aborigines or colonists. We reconstruct the subnational economic and political timeline of the world’s largest tropical country using municipal coats-of-arms to reinterpret Brazil’s historical ecology. We assessed all natural resource, biophysical, agricultural, and ethnocultural elements of 5,197 coats-of-arms (93.3%) distributed throughout Brazil. We extracted socioenvironmental co-variables for any municipality to understand and predict the relationships between social inequality, environmental degradation, and the historical ecology symbology. We analyzed data via ecological networks and structural equation models. Our results show that the portfolio of political-administrative symbology in coats-of-arms is an underutilized tool to understand the history of colonization frontiers. Although Brazil is arguably Earth’s most species-rich country, generations of political leaders have historically failed to celebrate this biodiversity, instead prioritizing a symbology depicted by icons of frontier conquest and key natural resources. Brazilian historical ecology reflects the relentless depletion of the natural resource capital while ignoring profound social inequalities. Degradation of natural ecosystems is widespread in Brazilian economy, reflecting a legacy of boom-and-bust rural development that so far has failed to deliver sustainable socioeconomic prosperity.

Abstract Seasonality is one of the main characteristics of a tropical dry forest that affects the structure of ecological communities. In this context, we evaluated the seasonal diversity of ferns and insects in the tropical dry forest of Morelos, Mexico, to determine whether a relationship exists between the presence of each of these two groups. Hill’s numbers indicated differences in the diversity of both groups according to season. In the rainy season, we recorded the highest diversity of ferns, with 6,471 individuals. In contrast, in the dry season, we recorded only 293 individuals. Regarding the insects, we collected 723 individuals in the rainy season and 171 individuals in the dry season. The order Orthoptera was the most abundant (50%). The best-represented functional group according to feeding guild was that of chewing herbivores. Correlation analysis revealed a positive relationship between insect and fern abundances since, for both groups, the minimum abundance was presented in the dry season and the maximum abundance in the rainy season. We recorded 12 orders of insects associated with eight ferns in the rainy season. Seasonal studies that consider different biological groups are necessary to understand how changes in resource availability shape temporal patterns of species diversity.

Wood basic density (WD) plays a crucial role in estimating forest biomass; moreover, improving wood-density estimates is needed to reduce uncertainties in the estimates of tropical forest biomass and carbon stocks. Understanding variations in this density along the tree trunk and its impact on biomass estimates is underexplored in the literature. In this study, the vertical variability of WD was assessed along the stems of large trees that had a diameter at breast height (DBH) ≥ 50 cm from a dense ombrophilous forest on terra firme (unflooded uplands) in Acre, Brazil. A total of 224 trees were sampled, including 20 species, classified by wood type. The average WD along the stem was determined by the ratio of oven-dry mass to saturated volume. Five models were tested, including linear and nonlinear ones, to fit equations for WD, selecting the best model. The variation among species was notable, ranging from 0.288 g cm−3 (Ceiba pentandra, L., Gaertn) to 0.825 g cm−3 (Handroanthus serratifolius, Vahl., S. Grose), with an average of 0.560 g cm−3 (±0.164, standard deviation). Significant variation was observed among individuals, such as in Schizolobium parahyba var. amazonicum (H. ex D.), which ranged from 0.305 to 0.655 g cm−3. WD was classified as low (≤0.40 g cm−3), medium (0.41–0.60 g cm−3), and high (≥0.61 g cm−3). The variability in WD along the stem differs by wood type. In trees with low-density wood, density shows irregular variation but tends to increase along the stem, whereas it decreases in species with medium- and high-density wood. The variation in WD along the stem can lead to underestimations or overestimations, not only in individual trees and species but also in total stocks when estimating forest biomass. Not considering this systematic bias results in significant errors, especially in extrapolations to vast areas, such as the Amazon.

Capturing birds of tropical rainforest canopies is important for answering many questions in ecology, evolution, and conservation, but canopy birds are often out of reach when using conventional mist-netting methods. Some methods exist to mist-net canopy birds, but modifications needed for target-capturing large frugivores are not well documented. Here, we describe a canopy netting method for capturing large, fruit-eating birds in rainforests. The methods presented here emphasize a large net area, maneuverability of netting, and collapsibility for safely preventing the escape of captured birds. During three different projects in the rainforests of Cameroon, this technique has resulted in the successful capture of hornbills (Bucerotidae), turacos (Musophagidae), and fruit pigeons (Columbidae). We recommend this technique for canopy bird research and encourage documentation of any modifications.

Deforestation is perhaps the greatest threat to tropical biodiversity. Anyway, extensive areas in the tropics have naturally regenerated and become secondary forests, which might mitigate biodiversity loss. However, evidence about the value of secondary forests for biodiversity conservation is still controversial. To establish the conservation value of secondary forests in the tropical Andes, we compared bird species richness, abundance, and composition between old and mature secondary forests using camera traps for two consecutive years. Our results suggest that old and mature secondary forests are similar in species richness and abundance to mature secondary forests, but these habitats significantly differ in species composition. Old secondary forests harbored some species highly specialized to mature forests (e.g., ant-following insectivorous birds: Myrmeciza longipes, Gymnopithys bicolor, Formicarius analis, and Dendrocincla fuliginosa) that are highly sensitive to habitat disturbance. Additionally, old secondary forests constitute suitable habitat for several species with decreasing populations, which could become of conservation importance in the long run. We consider that old secondary forests surrounded by mature forests can contribute to conserving understory birds, one of the most susceptible groups, negatively affected by tropical forest loss and degradation. Therefore, strategies for habitat biodiversity protection in this region should also include old secondary forests.

Spatially and timely accurate information about tropical forest disturbances is crucial for tracking critical forest changes, supporting forest management, and enabling law enforcement activities. In recent years, forest disturbance monitoring and alerting using cloud-penetrating Synthetic Aperture Radar (SAR) imagery has proven effective at national and pan-tropical scales. Related detection approaches mostly rely on detecting post-disturbance altered backscatter values in C or L-band SAR backscatter time series. Some disturbances are characterized by post-disturbance tree remnants or debris. For the time periods where these kinds of remnants remain present at the surface, the SAR backscatter values can be similar to those of stable forest. This can cause omission errors and delayed detection and it is considered a key shortcoming of current backscatter-based approaches. We hypothesized that despite fairly stable backscatter values, different orientation and arrangement of tree remnants leads to an altered heterogeneity of neighboring pixel values and that this can be quantified by textural features. We assessed six uncorrelated Gray-Level Co-Occurrence Matrix (GLCM) textural features using dense Sentinel-1C-band SAR time series. Forest disturbances, based on each GLCM feature using a pixel-based probabilistic change detection algorithm, were compared against results from forest disturbances mapped based only on backscatter data. We studied the impact of speckle-filtering on GLCM features and GLCM kernel sizes. We developed a method to combine backscatter and GLCM features, and we evaluated its robustness for a variety of natural and human-induced forest disturbance types across the Amazon Biome. Out of the six tested GLCM features GLCM Sum Average (SAVG) performed best. GLCM features derived from non-speckle filtered and speckle-filtered backscatter data did not show a noticeable impact on accuracy. A combination of backscatter and GLCM SAVG resulted in a reduced omission error of up to 36% and an improved timeliness of detections by average of to 30 days, with individual detection showing even higher improvements on a pixel level. The method was found to be robust across a variety of forest disturbance types. The largest reduction of omission errors and greatest improvement of timeliness was evident for sites with large unfragmented disturbance patches (e.g., large-scale clearings, fires and mining). For increasing GLCM kernel sizes, we observed a trade-off between reduced omission errors combined with improved timeliness and increasing commission errors. A kernel size of 5 was found to provide the best trade-off for reducing omission errors and improving timeliness while not introducing commission errors. The results emphasize that combining SAR-based textural features and backscatter can overcome omission errors caused by post-disturbance tree remnants or debris. This can help to improve the consistency and timelines of short (C-band) and long wavelength (L-band) based operational SAR disturbance monitoring and alerting. Result maps can be visualized via: https://johannesballing.users.earthengine.app/view/forest-disturbance-texture.

ABSTRACT Tropical forests are three-dimensional with the presence of numerous micro-environments formed by horizontal and vertical gradients. Such micro-environments can affect the nesting preference of organisms, including the trap-nesting Hymenoptera. Bees and wasps are key elements in ecosystems and are considered as sensitive to environmental changes, and trap-nests sampling methodology is widely used in their ecological and conservation studies. However, many uncertainties remain about nesting site preferences. From this perspective, our aim is to assess the diversity descriptors of trap-nesting Hymenoptera in different micro-environments. The sampling was conducted on three micro-environments (canopy, understory and treefall gaps) replicated on ten permanent plots within a Brazilian Atlantic forest hotspot. In each micro-environment, we installed trap-nest stations made by a set of twenty bamboo artificial nests. We found 762 brood cells from ten wasp and five bee species. The rarefaction curves indicate the lower species richness in understory stations, while treefall gaps and canopy stations were not significantly different. We analyzed abundance, mortality and parasitism rates using generalized linear models, but only abundance varies significantly among micro-environments. Our data indicates that trap-nesting Hymenoptera prefer to nest in micro-environments with higher exposure of sunlight. Canopy and treefall gap assemblages are consistently more abundant and diverse than understory probably due the higher temperature and lower humidity. On the other hand, mortality, parasitism rates, and the species composition were similar among environments. Our hypothesis is that the species composition was not affected as these species have a foraging range that encompasses nearby micro-environments.

Mapping of deforestation, forest degradation, and recovery is essential to characterize country-level forest change and formulate mitigation actions. Previous studies have mainly used a simple forest/non-forest classification after forest disturbance to identify deforestation and forest degradation. However, a more flexible approach that is applicable to different forest conditions is desirable. In this study, we examined an approach for mapping deforestation, forest degradation, and recovery using disturbance types and tree canopy cover estimates from annual Landsat time-series data from 1988 to 2020 across Cambodia. We developed models to estimate both disturbance types and tree canopy cover based on a random forest algorithm using predictor variables derived from a trajectory-based temporal segmentation approach. The estimated disturbance types and canopy cover in each year were then used in a rule-based classification of deforestation, forest degradation, and recovery. The producer’s and user’s accuracies ranged from 59.1% to 72.9% and 60.8% to 91.6%, respectively, for the forest change classes of mapping deforestation, forest degradation, and recovery. The approach developed here can be adjusted for different definitions of deforestation, forest degradation, and recovery according to research objectives and thus has the potential to be applied to other study areas.

Mapping the spatial distribution of soil organic carbon (SOC) in lands covered by tropical forests is important to understand the relationship and dynamics of SOC in this type of ecosystem. In this study, the Random Forest (RF) algorithm was used to map SOC stocks of topsoil (0–15 cm) in forest lands of the Dominican Republic. The methodology was developed using geospatial datasets available in the Google Earth Engine (GEE) platform combined with a set of 268 soil samples. Twenty environmental covariates were analyzed, including climate, topography, and vegetation. The results indicate that Model A (combining all 20 covariates) was only marginally better than Model B (combining topographic and climatic covariates), and Model C (only combining multispectral remote sensing data derived from Landsat 8 OLI images). Model A and Model B yielded SOC mean values of 110.35 and 110.87 Mg C ha−1, respectively. Model A reported the lowest prediction error and uncertainty with an R2 of 0.83, an RMSE of 35.02 Mg C ha−1. There was a strong dependence of SOC stocks on multispectral remote sensing data. Therefore, multispectral remote sensing proved accurate to map SOC stocks in forest ecosystems in the region.

The present study was accomplished to assess and compare tree diversity, carbon stock, and to find the relationship between carbon stock and tree diversity in scientifically and conventionally managed community forests (CFs) of Kanchanpur District, Nepal. A total of 94 sample plots were overlaid with a systematic random sampling method (51 plots in scientifically managed Singhapur CF and 43 plots were established in conventionally managed Kalika CF). The height and DBH of each tree were measured to calculate biomass and carbon stock. Shannon-Wiener and Simpson’s indexes were calculated for tree diversity. The data were pooled and analyzed using MS Excel and SPSS software. The values were statistically compared using a t-test. The total carbon stock and tree diversity were higher in scientifically managed CF (207.58 tons/ha and H= 0.97) than conventionally managed CF (183.72 tons/ha and H=0.85). Shorea robusta has a major contribution on total carbon stock in both CFs (Kalika: 66.34% and Singhapur: 70.43%) followed by Terminalia tomentosa (Kalika: 24.65% and Singhapur: 13.36%). The t-test did not show any significant difference for the mean values of carbon stocks and tree diversity between the CFs at a 5% level of significance. However, carbon stock showed a weak but positive relationship with species richness and negative with evenness. The result of the study recommends managing forests scientifically for increased tree diversity leading to enhanced carbon deposition.

Forests play a crucial role in quantifying global carbon storage and detecting climate change in the form of aboveground biomass (AGB), which introduces an approach to study carbon cycle, ecology, and biodiversity. The monitoring and estimation of forest AGB are considered very important and of practical value. As we know, forest AGB relates with height, density and diameter at breast height, and how to relate the ecophysical parameters with remote sensing images is vital for forest AGB estimation. In this paper, we aim to explore structure parameters about forest density and height, extracted by tomographic SAR (TomoSAR) techniques, for further improving the precision of AGB estimation models. Firstly, vertical structure profiles are constructed via TomoSAR, and the structure features are extracted. Secondly, the correlation between these features and the in-situ forest maximum height, tree density, and average AGB in plot scale is analyzed. Thirdly, the 8-fold cross-validation and step-wise regression methods were utilized to construct the tropical forest AGB models. Finally, the results of these models have been presented and analyzed. Based on the analysis, it indicates that “Model 7” is the most effective model, and its performance at both plot and pixel scales indicates a high level of accuracy for predicting forest AGB. These findings suggest that the proposed method can be effectively applied to tropical forested areas and has good scalability.

Phytochemical diversity is an effective plant defensive attribute, but much more research has focused on genetic and environmental controls of specific defensive compounds than phytochemical diversity per se. Documenting plasticity in phytochemical richness and plant chemical composition as opposed to individual compounds is important for understanding plant defense. This study outlines a multi-site transplant experiment in Cerrado gallery forests in central Brazil, utilizing Piper arboreum (Piperaceae), a prevalent and widespread neotropical shrub. Clones from four distinct populations were planted either at their origin site or in a different forest. Secondary metabolite composition varied between populations initially and then changed after transplanting. Interestingly, clones with chemical profiles that were distinct from the populations where they were introduced experienced reduced specialist chrysomelid herbivory compared to clones that were more chemically similar to the existing P. arboreum populations where they were planted. Specialist Lepidoptera herbivory also declined in clones transplanted to a new forest, but this change could not be ascribed to chemical profiles. In contrast, generalist herbivory was unaffected by chemical dissimilarity and transplanting. This research adds to the expanding body of evidence suggesting that phytochemical diversity is a dynamic trait exerting unique effects on different herbivore guilds.