National Forest Research Articles

Balancing Water Yield and Water Use Efficiency Between Planted and Natural Forests: A Global Analysis.

Climate warming is projected to affect hydrological cycle in forest ecosystems and makes the forest-water relationship more controversial. Currently, planted forests are gaining more public attention due to their role in carbon sequestration and wood production relative to natural forests. However, little is known about how the global patterns and drivers of water yield and water-use efficiency (WUE) differ between planted and natural forests. Here, we conduct a global analysis to compare water yield and WUE in planted and natural forests using 946 observations from 112 published studies. The results showed that global average water yield coefficient was 0.29 for planted forests and 0.34 for natural forests. Planted forests exhibited lower water yield coefficient (p < 0.05) in three climatic regions (arid, dry subhumid, and humid regions), but higher (p < 0.01) WUE only in arid region, compared with natural forests. Both water yield coefficient and WUE in planted forests were significantly lower (p < 0.05) than that in natural forests for stand characteristic groups (stand density, average tree height, leaf area index [LAI], and basal area). Additionally, stand density within the ranging between 1000 to 2000 stem ha-1 can maximize the water yield and WUE in planted and natural forests. Water yield coefficient in planted forests was primarily controlled by the factors related to tree growth (i.e., tree height, DBH), while that of natural forest mainly affected by stand structure (i.e., LAI, stand density, DBH). WUE in planted forest was more sensitive to climate than in natural forests. This work highlights the critical role of natural forests in water supply and the importance of tree species selection and stand management (e.g., stand density adjustment) in plantations in future forest restoration policies and climate change mitigation.

Tree Height–Diameter Model of Natural Coniferous and Broad-Leaved Mixed Forests Based on Random Forest Method and Nonlinear Mixed-Effects Method in Jilin Province, China

Objective: The purpose of this article was to use the Random Forest method and nonlinear mixed-effects method to develop a model for determining tree height–diameter at breast height (DBH) for a natural coniferous and broad-leaved mixed forest in Jilin Province and to compare the advantages and disadvantages of the two methods to provide a basis for forest management practice. Method: Based on the Chinese national forest inventory data, the Random Forest method and nonlinear mixed-effects method were used to develop a tree height–DBH model for a natural coniferous and broad-leaved mixed forest in Jilin Province. Results: The Random Forest method performed well on both the fitting set and validation set, with an R2 of 0.970, MAE of 0.605, and RMSE of 0.796 for the fitting set and R2 of 0.801, MAE of 1.44 m, and RMSE of 1.881 m for the validation set. Compared with the nonlinear mixed-effects method, the Random Forest model improved R2 by 33.83%, while the MAE and RMSE decreased by 67.74% and 66.44%, respectively, in the fitting set; the Random Forest model improved R2 by 9.88%, while the MAE and RMSE decreased by 14.38% and 12.05%, respectively, in the validation set. Conclusions: The tree height–DBH model constructed based on the Random Forest method had higher prediction accuracy for a natural coniferous and broad-leaved mixed forest in Jilin Province and had stronger adaptability for higher-dimensional data, which can be used for tree height prediction in the study area.

Fungal Footprints: Soil Fungal Communities in Black Walnut and Red Oak Forests

Soil fungal communities are critical for forest ecosystem functions in the Central Hardwood Region (CHR) of the USA. This evaluation, which took place in 2022–2023, investigates the influence of Juglans nigra (BW, black walnut) and Quercus rubra (NRO, Northern red oak) on soil properties and fungal community structures across three CHR sites. The objectives of this study are to investigate how the fungal communities identified beneath J. nigra and Q. rubra serve to influence biodiversity and soil health within hardwood plantations. Soils from two locations in Indiana and one in Michigan were examined and assessed for variations in fungal composition and diversity. Soil fungal communities were characterized using Illumina high-throughput sequencing while multivariate analysis was applied to analyze patterns in these fungal communities. These data provided insights into how environment, location, and tree species affect fungal community structure. Results indicate that J. nigra soils exhibited higher carbon (0.36%, 1.02%, 0.72%), nitrogen (25%, 29%, 56%), and pH (0.46, 1.08, 1.54) levels than Q. rubra soils across all three sites and foster greater fungal diversity. Specifically, J. nigra was associated with increased Ascomycota diversity, whereas Q. rubra supported a higher prevalence of Basidiomycota. Basidiomycota were negatively correlated with carbon and pH, while Ascomycota showed positive correlations with these variables. These findings highlight how crucial it is to understand how different tree species influence fungal communities and, consequently, how they influence forest soil health. Our findings serve to improve forest management practices by emphasizing the importance of fungal communities in maintaining the function and resilience of an ecosystem. Our study underscores that grasping these specific interactions is essential for effective forest management, especially when considering how to use fungal communities to boost plant growth. This work focuses on hardwood plantations rather than either agricultural ecosystems, monocultures, or native forests, thus filling a gap in the current literature where many studies are limited to specific fungal groups such as mycorrhizae. In future research, it is important to examine a wider range of tree species. This will deepen our understanding of fungal community dynamics and their impact on maintaining healthy forest ecosystems. Our hardwood plantation focus also notes the potential for adaptive forest management as environmental conditions change.

A practical framework for applied forestry assisted migration

Recent and projected changes in climate over this century pose an unprecedented threat to the health, diversity, and productivity of forest ecosystems. Forests have migrated and adapted to long-term changes in climate over thousands to millions of years; however, natural migration rates and adaptive responses of tree populations cannot match the rapid pace of current climate change. Consequently, more climate-informed approaches to reforestation are needed as current reforestation strategies using local seed sources may no longer be adequate to meet forest management objectives. Assisted migration is a climate change adaptation technique that can help maintain the ecosystem services and economic value that forests provide. Forestry assisted migration (FAM) focusses on the movement of populations of widespread, commercially, or ecologically important forest tree species within or just beyond their current ranges as a way to maintain forest productivity and health in the face of climate change. Although the forestry community recognizes FAM as a reforestation tool, guidance for planning and implementation of FAM is lacking and a framework that provides this guidance can prove useful to land managers with limited time and resources available who want to undertake FAM. We developed a practical framework (the FAM Framework) to provide a structured approach to ensure the most important considerations and best available science are utilized by land managers wanting to implement FAM on their land base. The FAM Framework incorporates multiple factors for the application of FAM in four sequential phases: assessment and analysis, climate-based plant material selection, seed procurement and deployment, and documentation and monitoring. The FAM Framework was tested by developing an assisted migration plan for the Superior National Forest, Minnesota (MN), and lessons learned from the development of this specific plan were used to revise and improve the FAM Framework for suitability across all lands. While originally designed to meet the needs of National Forest System land managers, it is relevant and applicable across the spectrum of land ownership because it incorporates consideration of critical elements in planning and implementing FAM on any landscape while facilitating adaptive management for active learning and future implementation.

Global potential for natural regeneration in deforested tropical regions.

Extensive forest restoration is a key strategy to meet nature-based sustainable development goals and provide multiple social and environmental benefits1. Yet achieving forest restoration at scale requires cost-effective methods2. Tree planting in degraded landscapes is a popular but costly forest restoration method that often results in less biodiverse forests when compared to natural regeneration techniques under similar conditions3. Here we assess the current spatial distribution of pantropical natural forest (from 2000 to 2016) and use this to present a model of the potential for natural regeneration across tropical forested countries and biomes at a spatial resolution of 30 m. We estimate that an area of 215 million hectares-an area greater than the entire country of Mexico-has potential for natural forest regeneration, representing an above-ground carbon sequestration potential of 23.4 Gt C (range, 21.1-25.7 Gt) over 30 years. Five countries (Brazil, Indonesia, China, Mexico and Colombia) account for 52% of this estimated potential, showcasing the need for targeting restoration initiatives that leverage natural regeneration potential. Our results facilitate broader equitable decision-making processes that capitalize on the widespread opportunity for natural regeneration to help achieve national and global environmental agendas.

Runoff Change Characteristics and Response to Climate Variability and Human Activities Under a Typical Basin of Natural Tropical Rainforest Converted to Monoculture Rubber Plantations

Climate variability and human activities are major influences on the hydrological cycle. However, the driving characteristics of hydrological cycle changes and the potential impact on runoff in areas where natural forests have been converted to rubber plantations on a long-term scale remain unclear. Based on this, the Mann–Kendall (MK) and Pettitt breakpoint tests and the Double Mass Curve method were employed to identify the variation characteristics and breakpoints of precipitation (P), potential evapotranspiration (ET0), and runoff depth (R) in the Wanquan River Basin (WQRB) during the 1970–2016 period. The changes in runoff attributed to P, ET0, and the catchment characteristics parameter (n) were quantified using the elastic coefficient method based on the Budyko hypothesis. The results revealed that the P and R in the WQRB exhibited statistically insignificant decreasing trends, while ET0 displayed a significant increasing trend (p &lt; 0.05). The breakpoint of runoff changes in the Jiabao and the Jiaji stations occurred in 1991 and 1983, respectively. The runoff changes show a negative correlation with both the n and ET0, while exhibiting a positive correlation with P. Moreover, it is observed that P and ET0 display higher sensitivity towards runoff changes compared to n. The decomposition analysis reveals that in the Dingan River Basin (DARB), human activities account for 53.54% of the runoff changes, while climate variability contributes to 46.46%. In the Main Wanquan River Basin (MWQRB), human activities contribute to 46.11%, whereas climate variability accounts for 53.89%. The research findings suggest that runoff is directly reduced by climate variability (due to decreased P and increased ET0), while human activities indirectly contribute to changes in runoff through n, exacerbating its effects. Rubber forest stands as the prevailing artificial vegetation community within the WQRB. The transformation of natural forests into rubber plantations constitutes the primary catalyst for the alteration of n in the WQRB. The research findings provide important reference for quantifying the driving force of hydrological changes caused by deforestation, which is of great significance for sustainable management of forests and water resources.

Light-demanding canopy tree species do not indicate past human disturbance in the Yangambi rainforest (Democratic Republic of the Congo)

Key messageIn a former paper, we investigated whether the presence of light-demanding tree species in the forest canopy of the Yangambi Biosphere Reserve (central Congo basin) might be a result of past human disturbances (Luambua et al., Ecol Evol 11:18691–18707, 2021). We focussed on the spatial distribution of the most abundant light demanders, but this approach did not yield conclusive results. In the present study, we focus on all species in the forest and conclude that light demanders are not a transient feature of successional tropical forests but an intrinsic component of old-growth forests in Yangambi.ContextCentral African rainforests are characterised by an abundance of light-demanding tree species, which are aggregated in the canopy but underrepresented in the understorey. A popular explanation is that these forests are recovering from slash-and-burn farming activities preceding the relocation of settlements during the colonial era. In a former paper, we showed that the abundance of light-demanding tree species in the Yangambi Biosphere Reserve (central Congo basin) cannot be unambiguously attributed to past human disturbances, using an approach that focused on the spatial distribution of the most abundant light demanders (Luambua et al., Ecol Evol 11:18691–18707, 2021).AimsAs the former study was inconclusive, the present study aims to further test the assumptions behind the ‘recovery from human disturbance hypothesis’, by considering all species in the forest of Yangambi. We addressed four specific research questions: (i) do light demanders occur in large ‘pockets’ occupying large areas of forest? (ii) Are light demanders abundant? (iii) Do they exhibit a regeneration deficit? (iv) Is species composition in pockets of light demanders different from the surrounding forests?MethodsWe identified the location and size of pockets of light demanders in several transects cumulating to 50 km. We installed permanent inventory plots within and outside these pockets and calculated the diameter and age distributions of light demanders within each pocket. We assessed whether pockets of light demanders are different from surrounding forests, using plot clustering analysis.ResultsOur results showed that light demanders were aggregated, but the pockets were small, scarce, and represent a minor fraction of the total forest area. Furthermore, light demanders were not abundant, even in pockets where they were aggregated. Their age distributions did not show a regeneration deficit. Finally, species composition in pockets of light demanders did not differ substantially from surrounding forests where they were scarce or absent.ConclusionsWe conclude that light-demanding canopy species do not indicate past human disturbance in Yangambi and that they are an intrinsic component of old-growth forests rather than a transient feature of successional forests. Our insights show that the large carbon sink observed in mature forests in this region is not driven by successional forest dynamics.

Soil Seed Banks Dynamics and Restoration Potential of Some Selected Forest Reserves in Southwest, Nigeria

This research investigated the regeneration potential of soil seed-bank along three soil depths in three secondary forest communities within Southwest Nigeria, for a better understanding of the potentials of the soil seed banks in facilitating succession towards a more natural forest of native tree species in International Institute of Tropical Agriculture (IITA) Forest Ibadan, Elephant Forest reserve Omo and Emerald Forest in Ikoyi Nigeria. Eight temporary plots of 20m by 40m using systematic line transect were laid in each forest. Soil samples were taken at three depths of 0–5 cm, 5–10 cm and 10–15cm and the seed bank composition was determined under a greenhouse condition. The results show that IITA forest has an abundance of 93 species with the highest in soil depth of 5-10 (35) and least exists at 10-15cm (24). The species evenness ranged from 0.92 to 0.96, with an average value of 0.94. Emerald forest had a total of 74 tree species with 0-5 cm depth having the highest species abundance (34), while depth of 5-10 cm (21) exhibit the least species abundance. At the forest, results of Species diversity indices show that at 0-5 cm depth 2.47 index value was recorded, a value much higher than what was recorded at 5-10 cm (2.40) and 10-15cm (2.36) respectively. The result of Elephant Forest reserve shows that a total of 87 tree species were recorded with 0-5 cm depth having the highest species abundance (40) followed by 5-10 cm (27), 10-15 (26) respectively. The Shannon Wiener index for Elephant Forest shows that 2.28 were recorded at 0-5 cm depth, 1.40 at 5-10 cm depth, and 1.70 at 10-15cm depth respectively. The soil seed bank could help in determining the status of regeneration potential of the three forests investigated. However, high dominance of tree species in the soil seed banks implies that the forest is disturbed and there is likelihood of tree species succeeding and dominating the forest ecosystem.

Extreme events and ichthyofauna: case report of a neotropical river

The increasing frequency and intensity of extreme weather events and their impact on aquatic ecosystems and fish species is concerning. This manuscript reports and analyzes two events, a drought in 2019 and a flood in 2024, providing valuable insights into the consequences of these events. The rescue of 269 individuals of 19 fish species during the 2019 drought highlights the significant impact of the extreme conditions on the ichthyofauna. Rising temperatures, isolation, and habitat fragmentation must have posed severe challenges for the fish species during this period. On the other hand, the observation of 53 dead individuals of 5 species during the 2024 flood indicates the detrimental effects of this event on the fish population. The association of mortality and dispersal of several species with the existing dam further underscores the complexity of the challenges faced by fish during extreme flood events. The correlation between rainfall, river regime, and the impact of land use and occupation provides an important context for understanding the dynamics of these extreme events. The low rainfall during the 2019 drought and the gradual increase in rainfall between 2022 and 2024 leading to the flood demonstrate the significant role of precipitation patterns in shaping the outcomes for fish species. Additionally, the analysis of land use and occupation, particularly the substantial increase in urbanization in the drainage basin over the last 30 years, highlights the human-induced factors contributing to the stress on aquatic ecosystems. Both extreme floods and droughts have significant implications for fish species. Extreme floods can alter riverbeds, cause direct mortality, and disrupt isolated populations, while extreme droughts can lead to fish kills, and habitat fragmentation, and exacerbate environmental stressors. This analysis emphasizes the urgent need for comprehensive measures to mitigate the impact of extreme weather events on aquatic ecosystems and fish species. Addressing factors such as land use and occupation, water management, and climate change adaptation strategies is crucial for promoting the resilience of fish populations in the face of ongoing environmental challenges. Keywords: drought, Ipanema National Forest, rainfall.

Examination of the Management of State Land by Local Authorities in the Context of Unauthorized Settlement: A Study of Forest No. 31 in Kabwe, Located in Zambia&amp;apos;s Central Province

Excision National Forest No. 31, Illegal Settlement, State Land, Local Area Plan and Encroachment

Bamboo Forests: Unleashing the Potential for Carbon Abatement and Local Income Improvements

Bamboo forests exhibit a unique efficient growth pattern that makes them invaluable in reducing atmospheric CO2 levels. Additionally, bamboo forests offer a diverse range of products, thus holding the potential to bolster local income. Despite these benefits, the comprehensive assessment of bamboo forests’ potential in both carbon abatement and improving local income enhancement has been hindered by the absence of a detailed bamboo biomass map. In this study, we address this gap by amalgamating a bamboo aboveground biomass (AGB) map covering three prominent producing provinces in southern China, utilizing multi-source remote sensing datasets. The results not only demonstrate a satisfactory consistency with China’s Ninth National Forest Inventory but also provide a more detailed spatial distribution. Based on this AGB estimation, we project an approximately threefold potential increase in annual bamboo culm harvest from existing bamboo forests. This represents a significant opportunity for expanding carbon abatement efforts, elevating local income levels, and facilitating the production of bamboo-derived biofuels. Furthermore, the adoption of an optimized management strategy has the potential to further enhance bamboo production. This study generates the first high-resolution bamboo AGB map and underscores the substantial potential of China’s bamboo forests in contributing to carbon sequestration and improving local income. The favorable income generated for local residents can serve as a compelling incentive for the implementation of sustainable forest management practices, offering a promising pathway toward achieving carbon-related objectives within the forestry sector and providing necessary support for forestry designation projects.

National Forest City Policy and Urban Ecological Resilience: Evidence from 292 Cities in China

The process of sustainable urban development faces complex and severe environmental problems. Therefore, enhancing urban ecological resilience (UER) has become an urgent and critical goal. In this study, the establishment of national forest cities (NFCs) in China is regarded as an exogenous shock event, and the impact of NFCs on UER and its mechanisms are investigated based on data from 292 cities spanning 2003 to 2021 using a difference-in-difference method. It is found that NFCs can significantly enhance UER, and this conclusion holds after a series of robustness tests. Mechanism analysis shows that NFCs can effectively strengthen environmental regulations, upgrade industrial structures, promote green innovation, and thus enhance UER. Heterogeneity analysis indicates that the effect of NFC on UER is more significant in low-carbon non-pilot cities, cities with higher levels of industrial development, and cities in central and western China. Spatial spillover analysis shows that NFCs can effectively improve the ecological resilience of neighboring cities. Therefore, NFCs should be continuously implemented and optimized to establish a long-term mechanism for urban forests to enhance ecological resilience.

Short-term conservation education influences Ugandan adolescents' knowledge, attitudes and investment decisions.

Environmental education research methods often focus on measuring changes in people's attitudes toward conservation. While attitudes are an important indicator of change, it is critical to target incentivised behaviour because conservation efforts often involve behavioural changes that are costly to one's self (e.g., reducing water use, purchasing pricier alternatives). In the present study, we measured both attitudes and behaviours in a short-term conservation education program near the primate-rich Kibale National Forest in Western Uganda. Adolescents ( N = 59) participated in a three-hour curriculum over three weeks integrated into an after-school wildlife club. After almost 30 years of successful primate conservation education in this region, we chose a novel taxonomic group (bats) for this study. Our pre-registered study had two conditions: an experimental condition, in which students learned about bats as an important local pollinator species, and a control condition, in which students learned about the moon. Only the experimental condition emphasised conservation's delayed benefits. We compared attitudes, knowledge, and behaviours pre- and post- curriculum. To capture behaviour, we employed an investment task in which participants could invest their own resources in a 'fund' to support work relating to bats or the moon, depending on condition. Across both conditions, participants showed positive shifts in attitudes and knowledge from pre- to post-measures and showed increased investments in bat- and moon-related funds. These findings reveal that short-term conservation education influences adolescents' investment decisions as well as their attitudes and knowledge. Our method can easily be edited for conservation education of any species including endangered primates.

Anthropogenic Extremely Low Volatility Organics (ELVOCs) Govern the Growth of Molecular Clusters Over the Southern Great Plains During the Springtime

AbstractNew particle formation (NPF) often drives cloud condensation nuclei concentrations and the processes governing nucleation of molecular clusters vary substantially in different regions. The growth of these clusters from ∼2 to &gt;10 nm diameters is often driven by the availability of extremely low volatility organic vapors (ELVOCs). Although the pathways to ELVOC formation from the oxidation of biogenic terpenes are better understood, the mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are less well understood. We integrate measurements and detailed regional model simulations to understand the processes governing NPF and secondary organic aerosol formation at the Southern Great Plain (SGP) observatory in Oklahoma and compare these with a site within the Bankhead National Forest (BNF) in Alabama, southeast USA. During our two simulated NPF event days, nucleation rates are predicted to be at least an order of magnitude higher at SGP compared to BNF largely due to lower sulfuric acid (H2SO4) concentrations at BNF. Among the different nucleation mechanisms in WRF‐Chem, we find that the dimethylamine (DMA) + H2SO4 nucleation mechanism dominates at SGP. We find that anthropogenic ELVOCs are critical for explaining the growth of particles observed at SGP. Treating organic particles as semisolid, with strong diffusion limitations for organic vapor uptake in the particle phase, brings model predictions into closer agreement with observations. We also simulate two non‐NPF event days observed at the SGP site and show that low‐level clouds reduce photochemical activity with corresponding reductions in H2SO4 and anthropogenic ELVOC concentrations, thereby explaining the lack of NPF.

Research on the Registration of Aerial Images of Cyclobalanopsis Natural Forest Based on Optimized Fast Sample Consensus Point Matching with SIFT Features

The effective management and conservation of forest resources hinge on accurate monitoring. Nonetheless, individual remote-sensing images captured by low-altitude unmanned aerial vehicles (UAVs) fail to encapsulate the entirety of a forest’s characteristics. The application of image-stitching technology to high-resolution drone imagery facilitates a prompt evaluation of forest resources, encompassing quantity, quality, and spatial distribution. This study introduces an improved SIFT algorithm designed to tackle the challenges of low matching rates and prolonged registration times encountered with forest images characterized by dense textures. By implementing the SIFT-OCT (SIFT omitting the initial scale space) approach, the algorithm bypasses the initial scale space, thereby reducing the number of ineffective feature points and augmenting processing efficiency. To bolster the SIFT algorithm’s resilience against rotation and illumination variations, and to furnish supplementary information for registration even when fewer valid feature points are available, a gradient location and orientation histogram (GLOH) descriptor is integrated. For feature matching, the more computationally efficient Manhattan distance is utilized to filter feature points, which further optimizes efficiency. The fast sample consensus (FSC) algorithm is then applied to remove mismatched point pairs, thus refining registration accuracy. This research also investigates the influence of vegetation coverage and image overlap rates on the algorithm’s efficacy, using five sets of Cyclobalanopsis natural forest images. Experimental outcomes reveal that the proposed method significantly reduces registration time by an average of 3.66 times compared to that of SIFT, 1.71 times compared to that of SIFT-OCT, 5.67 times compared to that of PSO-SIFT, and 3.42 times compared to that of KAZE, demonstrating its superior performance.

Predictive Modelling of Land Cover Changes in the Greater Amanzule Peatlands Using Multi-Source Remote Sensing and Machine Learning Techniques

The Greater Amanzule Peatlands (GAP) in Ghana is an important biodiversity hotspot facing increasing pressure from anthropogenic land-use activities driven by rapid agricultural plantation expansion, urbanisation, and the burgeoning oil and gas industry. Accurate measurement of how these pressures alter land cover over time, along with the projection of future changes, is crucial for sustainable management. This study aims to analyse these changes from 2010 to 2020 and predict future scenarios up to 2040 using multi-source remote sensing and machine learning techniques. Optical, radar, and topographical remote sensing data from Landsat-7, Landsat-8, ALOS/PALSAR, and Shuttle Radar Topography Mission derived digital elevation models (DEMs) were integrated to perform land cover change analysis using Random Forest (RF), while Cellular Automata Artificial Neural Networks (CA-ANNs) were employed for predictive modelling. The classification model achieved overall accuracies of 93% in 2010 and 94% in both 2015 and 2020, with weighted F1 scores of 80.0%, 75.8%, and 75.7%, respectively. Validation of the predictive model yielded a Kappa value of 0.70, with an overall accuracy rate of 80%, ensuring reliable spatial predictions of future land cover dynamics. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, they do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the understudied GAP region, offering critical insights for developing targeted conservation strategies. Additionally, the methodological framework, which combines optical, radar, and topographical data with machine learning, provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands that is applicable to other regions facing similar environmental challenges.

Crop-raiding by wildlife and cropland abandonment as feedback from nature-based solutions: Lessons from case studies in China and Nepal

Abstract Conservation efforts under the nature-based solutions (NbS) framework aim at better management of ecosystems and improvement of human well-being. Policies targeting forest-based livelihoods align well with the NbS principles, but their social-ecological outcomes are often confounded by complex human-environment interactions. In this study, we identify one major feedback effect of the ecosystem dynamic on people’s livelihoods based on datasets collected from two study areas in China and Nepal. Our methodology integrates satellite remote sensing, household surveys, and statistical models to investigate households’ cropland abandonment decisions under the influence of crop-raiding by wildlife. Results show that cropland parcels that have experienced crop-raiding are more likely to be abandoned in the following years. The more damage the crops have suffered on a given parcel, the more likely it is that the parcel will be abandoned. Parcels in proximity to natural forests, farther away from the house location, and with poorer access to paved roads bear a higher risk of being abandoned. These effects are robust and consistent after controlling for multiple parcel features and household characteristics at different levels and using the dataset from each study area separately. We conclude that policymakers need to consider this undesirable feedback of the ecological system to the livelihoods of local people to better achieve co-benefits for ecosystems and human society.

Canting Expedition: Herpetofauna Diversity in the Mendolo Village, Lebakbarang, Pekalongan

Central Java is an area that has natural forests with quite high biodiversity potential, one of which is Mendolo Village, Lebakbarang, Pekalongan. The diversity of herpetofauna species is one of its potential biodiversity. Data collection on herpetofauna in Mendolo Village has not yet been carried out, even though this village is in direct contact with natural forests with great potential. The aim of this research is to reveal the diversity of herpetofauna types at this location. The method used is VES (Visual Encounter Survey). The data obtained was then analyzed using the Shannon-Wiener Diversity Index. There were 23 species of reptiles and 16 species of amphibians, with a Diversity Index value of 2.942 for reptile types and 2.28 for amphibians. The conclusion that can be drawn is that the diversity of herpetofauna species in Mendolo Village is in the quite high category.

Understanding the effect of cropping system on soil health at the Northwestern Ontario Agricultural Research Station in Canada

Anthropogenic activities impact soil in varying degrees, from preserving natural landscapes to intensive agriculture which among the farm practices that impact the soil are the cropping systems. Information on cropping systems and soil impacts in northern territories is still missing. This study assesses the effect of different cropping systems on soil health -physical, chemical and biological soil properties and indicators of soil health - at the Lakehead Agricultural Research Station [LUARS] in northern Ontario, Canada. The study compares three cropping systems (perennial crops-pasture, grass, and annual crops -wheat, barley, corn, soybeans) and two forest areas (conifer plantation and naturally regenerating mixed wood forest) at LUARS. Soil samples were collected at different depths and analyzed for various indicators using the Cornell Soil Health Assessment framework. The results showed the soil health scores varied among cropping systems, with natural forest and perennial crops-pasture having higher scores compared to annual crops -wheat, barley, corn, soybeans. Soil organic matter was found to be lowest in annual crops -wheat, barley, corn, soybeans, while aggregate stability was highest in natural forests. The study also identifies the soil health gap, which represents the difference between the health of a particular cropping system and a benchmark. The soil health gap analysis can help farmers implement practices to improve soil health and increase the resilience and sustainability of agroecosystems. Overall, this study emphasizes the importance of understanding the effect of cropping systems on soil health and provides insights into potential strategies for improving farm practices.

Evaluation and Prediction of Ecological Benefits in Song-Liao River Basin

The evaluation and prediction of ecological benefits are significant for regional resource development planning and path designing. This study established a novel ecological benefits evaluation system by integrating macro-ecosystem structure, Ecosystem service index (ESI), and ecological quality index (EQI). Based on this system, this study evaluated the spatiotemporal characteristics and changing trend of ecological benefits in Song-Liao River Basin (SRB) from 1990 to 2020. The results show that the macro-ecosystem structure in Song-Liao River Basin remains stable, and the ecosystem service and ecological quality generally show a trend of first decline and then increase. The average growth rates of ESI and EQI were 0.6% and 0.4%, respectively, during 1990–2020. The ecological benefits of natural areas with widely distributed forest areas are higher, while those of areas with frequent human activities are lower. The prediction model based on machine learning has achieved good modeling effect, which shows that the ecological benefits of SRB will be on the rise in the future. Based on the evaluation results, we suggest that more environmental protection policies on the basis of maintaining the existing development plan should be promoted to reduce the contradiction between human and nature in the development process. For the abundant natural forests in this area, reasonable forest management should be carried out to improve the carbon-fixation capacity of vegetation, and a Methodology for managing natural forests should be constructed to make full use of the existing carbon sinks. For the new afforestation project being promoted, carbon-sink afforestation projects of CCER (Chinese Certified Emission Reduction) should be promoted to realize the synergy between economic development and environmental protection.