Land Use Change Research Articles

Improving the efficiency of aerial surveys for monitoring North American beaver population dynamics

Context The North American beaver (Castor canadensis) was extirpated from much of its range in the US in the 1800s due to fur trapping and change in land use. However, the species has recolonised much of its former range, including the US state of Ohio. Since 2013, the Ohio Division of Wildlife (ODOW) has monitored trends in beaver colony density via aerial surveys of 40 km × 40 km plots classified as low, medium, or high suitability based on the amount of wetland. Nonetheless, the current classification system may miss important correlates of beaver colony density. Aims Our study aimed to (1) identify predictors of beaver colony density (number of colonies inferred from aerial counts of lodges) across Ohio, and (2) develop a model-based classification system to improve the efficacy of monitoring efforts. Methods To predict beaver colony density in Ohio we used an aerial survey dataset of 54 plots (40 km × 40 km) collected by ODOW annually between 2013 and 2020, along with a suite of environmental, anthropogenic, and climate variables in a mixed effects modelling framework. Key results Beaver colony density was positively associated with wetland and reclaimed surface mine areas and inversely associated with the proportion of agricultural lands. There was a negative interaction between wetland and surface mines; in general, beaver colony density increased with wetland and surface mine area. However, in plots with wetland area >1000 ha, beaver colony density was weakly negatively associated with surface mine area. Using median and interquartile ranges of model-averaged predicted beaver colony density, we developed a new classification of low, moderate and high suitability for both the survey plots and the entire state of Ohio. We found that eastern Ohio had high suitability, while the central and western parts of the state had lower suitability for C. canadensis. Conclusions Our approach to identifying predictors for beaver colony density at broad spatial scales highlights the importance of reclaimed surface mines and wetlands for beaver populations, while the model-based habitat classification provides ODOW additional information for monitoring and beaver management decisions. Implications Improved C. canadensis monitoring at the landscape scale using habitat classifications that consider local conditions can both improve annual survey cost-effectiveness and facilitate the sustainable management of this recovering species.

Analysis of Spatiotemporal Predictions and Drivers of Carbon Storage in the Pearl River Delta Urban Agglomeration via the PLUS-InVEST-GeoDetector Model

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA.

Dynamics System Modeling of Declining Agricultural Land Area Potentially Causing Jakarta Flood Disaster

The change or evolution of land use in the DKI Jakarta area has caused various environmental problems in the city that have an impact on disasters that occur from time to time. The conversion of agricultural land that has a relatively high ability to absorb water into built-up land has reduced the water absorption capacity because the built-up area is increasingly impermeable which is at risk of causing flood disasters. This research focuses on a simple dynamic system modeling approach to understand the cause-and-effect relationship of the decline in agricultural land area in the DKI Jakarta area. The method used in this research is a qualitative-based dynamic system, dynamic system is a method that can be used to form structures and predict behavior and feedback. Dynamic system modeling using Powersim Studi 10 Express software uses time specifications ranging from 2020 to 2070. The results of the dynamic system model of agricultural land decline can be said to be valid, where the dominant structure formed is Negative Feedback (Balancing Loop) with Exponential Decay behavior and Average Means Error (AME) test results obtained a value of 29.6%

Artificial Intelligence in Aspect of Deforestation and Plantation Sustainability: Bibliometric Approach

This study examines the application of Artificial Intelligence (AI) in addressing deforestation and promoting sustainability in plantations using a bibliometric approach. Deforestation, a critical global issue, results from agricultural expansion, plantation development, and land-use changes, leading to significant environmental degradation. AI has been proposed as a powerful tool to monitor and manage deforestation more effectively, offering solutions such as satellite imagery analysis and predictive models. Through a bibliometric analysis spanning the last decade (2013–2023), this study uses VOSviewer to visualize co-citation networks, identifying key research trends and clusters related to AI in deforestation and plantation sustainability. The findings reveal that research is concentrated in regions like Indonesia and Brazil, where AI technologies like machine learning are employed to predict deforestation and enhance resource management. Emerging research areas include the integration of AI with the Internet of Things (IoT) and blockchain for improved data management and sustainability practices. This analysis provides insights into the growing role of AI in mitigating deforestation and offers recommendations for future research, including addressing ethical challenges and regulatory frameworks to further enhance sustainable plantation management.

Grassland or Cropland? Land Use Dilemma and Ecological Solutions in Inner Mongolia

ABSTRACTInner Mongolia plays a critical role in both ecological conservation and food provision in China. However, some researchers have argued that focusing on and improving only one side of the equation necessarily threatens the functionality of the opposite side. To address this problem, we compared a “business‐as‐usual” scenario (BAU) with a “sustainable land use planning” scenario (SLU) constructed by simulating spatiotemporal changes in croplands and grasslands in Inner Mongolia from 2020 to 2030. Additionally, we analyzed the changes in ecosystem services and protein supply associated with changes in land use. We found that, in the BAU scenario, grasslands would decrease by 1.85% over the simulation period, while croplands would increase by 9.94%, with ecosystem services decreasing under both land uses. In contrast, land use changes over the same period in the SLU scenario are more significant, with increases of 11.33% and 2.78% in grassland and cropland, respectively, but, in this case, with ecosystem services increasing under both land uses. Moreover, protein supply increased under both scenarios, but SLU scenario can provide 33% more protein than the BAU scenario. The interconversion of cropland and grassland is the main type of land conversion in the study region, while cropland, grassland, and bare land show a triangular cycle of conversion. In addition, the implementation of scenario planning can realize multiple dividend for cultivation, livestock, and ecology in Inner Mongolia.

Nature's Contributions to People: Systematic Mapping of Studies and Inventory of Methodologies and Indicators for Quantifying Hydrological Ecosystem Services

Objective: Evaluate the estimation of nature's contributions to people - NCP (i.e. ecosystem services - ES) through bibliographic mapping and systematization of methodologies, tools and indicators of hydrological ecosystem services (HES). Theoretical Framework: Predatory exploitation of ecosystems is causing increasingly severe impacts on humanity. Accelerated by population growth, changes in land use and the decoupling of measures recommended by science from those adopted by nations, climate change is triggering alterations in the global hydrological cycle. Adaptation strategies depend on the production of information on the supply and flow of HES. Method: Consultation of the Web of Science, Scopus and Science Direct databases, and systematic bibliographic mapping (2014-2024), with bibliometric analysis in the VOSviewer software, and recording of information on NCP, ES, metrics, methodologies for quantifying HES and respective indicators. Results and Discussion: A total of 743 abstracts were analyzed and 196 articles were selected. Of these, 103 estimated HES, with a predominance of studies on a river basin scale. Seventy-nine indicators were mapped, mostly biophysical, associated with water flow regulation and water quality. China was the most represented country in terms of mapped area. The most widely used models were InVEST and SWAT. Research Implications: Systematization of information for users interested in mapping and quantifying HES, with an indication of established aspects, methods, and knowledge gaps. Originality/Value: Mapping based on HES indicators, aggregation of studies under different ES frameworks and provision of a dynamic results panel, with spatialization of studies and various data filtering possibilities.

Land use dynamics and ecosystem service valuation in the Sanmenxia Reservoir wetland of the Yellow River

The Sanmenxia Reservoir wetland (SRW) serves as a critical ecological buffer in the middle reaches of the Yellow River. Ongoing population growth and changes in land use have placed significant pressure on the wetland’s ecosystems. However, existing research has yet to establish a spatiotemporal analysis method to assess the impact of land use change on the ecosystem service value (ESV). This gap hinders the precise regulation and sustainable development of land resources. To gain a comprehensive understanding of the land use dynamics and ecological functions of the SRW, this study introduced a refined ESV evaluation method. This method revised the equivalent factors from spatial, temporal, and hydrological perspectives, with an emphasis on the impact of sediment discharge. Furthermore, the Patch-level Land Use Simulation (PLUS) model was employed to project the land use structure in 2030, and the corresponding ESV was analyzed. The study revealed the following: (1) Cropland constituted the primary land type in the SRW. Over the last two decades, the build-up area exhibited the most significant single land use dynamics, with the transformation of bare land to cropland spanning the widest range and largest area. (2) From 2000 to 2020, the ESV increased by 0.64 billion CNY, with the water body contributing almost all the increase. (3) The projected ESV for 2030 is 2.94 billion CNY, indicating an increase in ecological functions in the near future. Policy makers should recognizethe impact of land use change on ESV and implement measures to rebalance land use structure. While ensuring the preservation of cropland and the protection of lives and property, it is advisable to consider expanding the water body area to facilitate comprehensive sustainable development within SRW.

RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension

Abstract. The reduction of in situ observations over the last few decades poses a potential risk of losing important information in regions where local effects dominate the climatology. Reanalyses face challenges in representing climatologies with highly localized effects, especially in regions with complex orography. Empirical downscaling methods offer a cost-effective and easier-to-implement alternative to dynamic downscaling methods and can partially overcome the aforementioned limitations of reanalyses by taking into account the local effects through statistical relationships. This article introduces RASCAL (Reconstruction by AnalogS of ClimatologicAL time series), an open-source Python tool designed to extend time series and fill gaps in observational climate data, especially in regions with limited long-term data and significant local effects, such as mountainous areas. Employing an object-oriented programming style, RASCAL's methodology effectively links large-scale circulation patterns with local atmospheric features using the analog method in combination with principal component analysis (PCA). The package contains routines for preprocessing observations and reanalysis data, generating reconstructions using various methods, and evaluating the reconstruction's performance in reproducing the time series of observations, statistical properties, and relevant climatic indices. Its high modularity and flexibility allow fast and reproducible downscaling. The evaluations carried out in central Spain, in mountainous and urbanized areas, demonstrate that RASCAL performs better than the ERA20C and ERA20CM reanalysis, as expected, in terms of R2, standard deviation, and bias. When analyzing reconstructions against observations, RASCAL generates series with statistical properties, such as seasonality and daily distributions, that closely resemble observations. This confirms the potential of this method for conducting robust climate research. The adaptability of RASCAL to diverse scientific objectives is also highlighted. However, as with any other method based on empirical training, this method requires the availability of sufficiently long-term data series. Furthermore, it is susceptible to disruption caused by changes in land use or urbanization processes that might compromise the homogeneity of the training data. Despite these limitations, RASCAL's positive outcomes offer opportunities for comprehensive climate variability analyses and potential applications in downscaling short-term forecasts, seasonal predictions, and climate change scenarios. The Python code and the Jupyter Notebook for the reconstruction validation are publicly available as an open project.

Shallow drainage of agricultural peatlands without land-use change: have your peat and eat it too

IntroductionDrainage for agricultural purposes is one of the main drivers of peatland degradation, leading to significant greenhouse gas (GHG) emissions, biodiversity loss, and soil eutrophication. Rewetting is a potential solution to restore peatlands, but it generally requires a land-use shift to paludiculture or nature areas.MethodsThis study explored whether three different water level management techniques (subsoil irrigation, furrow irrigation, and dynamic ditch water level regulation) could be implemented on dairy grasslands to yield increases in essential ecosystem services (vegetation diversity and soil biogeochemistry) without the need to change the current land use or intensity. We investigated vegetation diversity, soil biogeochemistry, and CO2 emission reduction in fourteen agricultural livestock pastures on drained peat soils in Friesland (Netherlands).ResultsAcross all pastures, Shannon-Wiener diversity was below 1, and the species richness was below 5. The plant-available phosphorus (P) was consistently higher than 3 mmol L−1. None of the water level management (WLM) techniques enhanced vegetation diversity or changed soil biogeochemistry despite a notable increase in water table levels. The potential for CO2 emission reduction remained small or even absent. Indicators of land-use intensity (i.e., grass harvest and fertilization intensity), however, showed a strong negative correlation with vegetation diversity. Furthermore, all sites’ total and plant-available P and nitrate exceeded the upper threshold for species-rich grassland communities.DiscussionIn conclusion, our research suggests that incomplete rewetting (i.e., higher water tables while maintaining drainage) while continuing the current land use does neither effectively mitigate GHG emissions nor benefit vegetation diversity. Therefore, we conclude that combining WLM and reducing land-use intensity is essential to limit the degradation of peat soils and restore more biodiverse vegetation.

Spatiotemporal Eolution and Prediction of Ecosystem Service Value in Taihang Mountains Based on MCCA Land Use Scenario Simulation

Ecosystem service value （ESV） is an important indicator related to regional ecological well-being, and understanding its evolution can provide references for regional ecological civilization construction and sustainable development. The Taihang Mountains, an important ecological security barrier in North China, were taken as an example. Based on land use data from 2000 to 2020, this study revealed the changes in land use and ecosystem service value in the Taihang Mountains and conducted multi-scenario simulations of ESV in 2035. Additionally, the land use transfer matrix, improved equivalent factor method, and mixed-cell cellular automata model were used. The results showed that： ① From 2000 to 2020, the main land use types in the Taihang Mountains were cropland, forest land, and grassland. The area of cropland and grassland significantly decreased, whereas the area of forest land and construction land remained stable. The scale of land use transfer was 2.06×104 km2, with a high intensity of transfer from cropland and grassland to other areas, mainly guided by ecological construction. ② The ecosystem service functions in the Taihang Mountains were mainly dominated by regulation services, and the overall ESV showed a stable upward trend, increasing by 1.51×1010 RMB from 2000 to 2020. The spatial distribution of ESV was uneven, and the polarization phenomenon was evident, with high-value areas concentrated in the high-altitude areas in the northern and central-southern parts and low-value areas mostly located in the flat foothills and central plateaus on both sides. They were greatly influenced by human activities. ③ By 2035, compared with that in 2020, the ESV in the Taihang Mountains was projected to increase by 5.37 billion RMB in the natural growth scenario, 4.34 billion RMB in the urban development scenario, and 7.64 billion RMB in the ecological tourism scenario, mainly due to the conversion from cropland and grassland to forest land. The natural growth scenario showed a high intensity of spatial transformation of ESV, the urban development scenario experienced severe ESV loss in cropland, and the ecological tourism scenario showed a significant increase in ESV, which was an effective path for promoting green development in the Taihang Mountains. The research results can provide scientific references for the healthy management and sustainable development of the ecosystem in the Taihang Mountains.

Detecting Land-Use Changes in Greater Kandy Development Area

As urban growth became a threat to Kandy city, the Urban Development Authority (UDA) has introduced a new concept called the “Greater Kandy Development Area (GKDA)” to control and manage the rapid urban growth, as well as to minimize its’ impacts towards the environment. This study examines the land use/ land cover changes in GKDA, in selected time periods using GIS and Remote Sensing techniques. Findings demonstrate that dynamic patterns of urban expansion cause progressive growth in built-ups and lowering in non-built-ups. In 2005, there were only 16.9 percent of built-up areas in GKDA but, it has increased up to 40 percent in 2020. 81.7 percent of non-built-up areas in 2005, has reduced up to 58.8 percent. As population growth happened inside the city limits, land use changes also happened within. These changes create clustered as well as sprawl development patterns.

Simulating Changes in Ecosystem Carbon Storage and Analyzing Influencing Factors in the Central Zhejiang under the Background of LUCC

Central Zhejiang is the key ecological function area of Zhejiang Province and an important part of the Qiantang River ecological corridor. Conducting simulations of ecosystem carbon storage changes and analyzing influencing factors under land-use changes in this region is of significant importance for achieving the goals of "peak carbon" and "carbon neutrality" at an early stage. This study, based on the land use data of five periods from 1980 to 2020 in central Zhejiang, coupled the GeoSOS-FLUS and the InVEST model to analyze the spatiotemporal changes in carbon storage in the region over time and project for the year 2030. The study also explored the impact of socio-economic and natural factors on changes in carbon storage. The results showed that： ① Between 1980 and 2020, urban construction land in the Zhejiang Central Region increased by 289.91%, with cultivated land and forest land being the main sources, leading to a 3% decrease in ecosystem carbon storage, amounting to 588.88×104 tons. ② High-value areas of carbon storage in the Zhejiang Central Region were concentrated in P'an-an County, Jinyun County, Wuyi County, and other areas. ③ Under the two different scenarios of natural development and ecological protection, carbon storage in the research area was projected to decrease by 1.05% and 0.05%, respectively, by 2030 compared to that in 2020. ④ Natural factors dominated the distribution of carbon storage, but their influence was gradually decreasing over time. The impact of socio-economic factors was increasing, and the combined effect of socio-economic and natural factors far outweighed the influence of a single factor on carbon storage distribution. These findings can serve as a scientific reference and guide for mitigating carbon loss in ecosystems, promoting ecosystem protection, facilitating sustainable social development, and achieving the "dual carbon" goals in Zhejiang and other regions nationwide.

Recurrent wildfires alter forest structure and community composition of terra firme Amazonian forests

Abstract Wildfires associated with land-use and climate change have considered a key driver to the Amazon forest collapse. However, achieving a detailed understanding of how human-related disturbances impact forest successional trajectories needs comprehensive information spanning forest strata. Here, we investigate the impact of recurrent wildfires on forest structure, species diversity, and composition, making a comprehensive assessment of the regenerating, understory, and canopy tree communities in a sustainable use reserve in the eastern Amazon. Plant communities were described across 16 forest stands (old-growth, burned once and twice) sampling a total of 3620 individuals and 326 tree and palm species. Wildfires affected all attributes of forest structure. Aboveground biomass decreased by 44% in forest burned once, and 71% in twice-burned forest stands. Forest canopy was the most affected strata after the second fire, with a 44%-decrease compared to unburned forest. The same pattern emerged for basal area, which decreased by an average of 27.5% after the first fire and 53.8% following the second fire event. Overall, plant communities experienced a 50%-loss of species richness after two fires, including both dominant and rare species. Plant communities also became more dissimilar as fire events accumulated, with 58%–61% increase in species dissimilarity following two fires events. As wildfires reoccured, the old-growth forests of our focal landscape were converted into a mosaic of regenerating forest stands dominated by local short-lived pioneers (i.e. low-biomass early-regenerating forest stands) and a few tree species less sensitive to fire. Our findings highlight the urgent need to secure a resilient future for Amazonian forests with actions needed to support local livelihoods whilst reducing the prevalence of ignitions sources and allowing forest recovery.

Changing windstorm characteristics over the US Northeast in a single model large ensemble

Abstract Extreme windstorms pose a significant hazard to infrastructure and public safety, particularly in the highly populated US Northeast (NE). However, the influence climate change and changing land use will have on these events remains unclear. A large ensemble generated using the Max-Planck Institute (MPI) Earth system model is used to generate projections of NE windstorms under different shared socioeconomic pathways (SSPs) and to attribute changes to projected land use land cover (LULC) change, externally forced changes and internal climate variability. To reduce the influence of coarse grid cell resolution and uncertainties in surface roughness lengths, windstorms are identified using simultaneous widespread exceedance of local 99th percentile 10 m wind speeds (U99). Projected declines in forest cover in the NE and the resulting reductions in surface roughness length under SSP3-7.0 lead to projections of large increases in U99 and derived windstorm intensity and scale. However, these projected changes in regional LULC under SSP3-7.0 are unprecedented in a historical context and may not be realistic. After corrections are applied to remove the influence of LULC on wind speeds, regionally averaged U99 exhibit declines for most of the single model initial-condition large ensemble (SMILE) members which are broadly proportional to the radiative forcing and global air temperature increase in the SSPs, with a median value of −0.15 ms−1 °C−1. While weak cyclones are projected to decline in frequency in the NE, intense cyclones and the resulting windstorms and indices of socioeconomic loss do not. Where present, significant trends in these loss indices are positive, and some MPI SMILE members generate future windstorms that are unprecedented in the historical period.

Assessing the Sustainability Impact of Land-Use Changes and Carbon Emission Intensity in the Loess Plateau

Assessing the Sustainability Impact of Land-Use Changes and Carbon Emission Intensity in the Loess Plateau

Species traits, landscape quality and floral resource overlap with honeybees determine virus transmission in plant-pollinator networks.

Emerging infectious diseases pose a threat to pollinators. Virus transmission among pollinators via flowers may be reinforced by anthropogenic land-use change and concomitant alteration of plant-pollinator interactions. Here, we examine how species' traits and roles in flower-visitation networks and landscape-scale factors drive key honeybee viruses-black queen cell virus (BQCV) and deformed wing virus-in 19 wild bee and hoverfly species, across 12 landscapes varying in pollinator-friendly (flower-rich) habitat. Viral loads were on average more than ten times higher in managed honeybees than in wild pollinators. Viral loads in wild pollinators were higher when floral resource use overlapped with honeybees, suggesting these as reservoir hosts, and increased with pollinator abundance and viral loads in honeybees. Viral prevalence decreased with the amount of pollinator-friendly habitat in a landscape, which was partly driven by reduced floral resource overlap with honeybees. Black queen cell virus loads decreased with a wild pollinator's centrality in the network and the proportion of visited dish-shaped flowers. Our findings highlight the complex interplay of resource overlap with honeybees, species traits and roles in flower-visitation networks and flower-rich pollinator habitat shaping virus transmission.

Assessing Land Use Ecological-Social-Production Functions and Interrelationships from the Perspective of Multifunctional Landscape in a Transitional Zone between Qinghai-Tibet Plateau and Loess Plateau

Investigating the evolution and drivers of multifunctional land use is essential for sustainable land management and regional biological conservation. This research focuses on the Hehuang Valley, where we developed an “ecological-social-production” evaluation system for assessing land use multifunctionality from the perspective of multifunctional landscape. Leveraging Geographic Information System technologies, we conducted a quantitative analysis of spatiotemporal variations in multifunctional land use across the valley in recently twenty years. Correlation coefficients were employed to identify trade-offs and synergies among various land use functions. Additionally, geographical detector and grey relational analysis models were utilized to pinpoint the factors influencing spatiotemporal changes in land use functions during the specified period. The results showed that: (1) During the period, the overall multifunctionality of land use in the Hehuang Valley exhibited an increasing trend. The economic production function of the land showed the highest growth, while the ecological and social functions showed lower growth. (2) In most areas of the Hehuang Valley, there was a positive correlation between social and economic production functions and a negative correlation between social and ecological functions, as well as between economic production and ecological functions. (3) Natural conditions were the main factors of spatial variation of land use comprehensive functions, but human factors, including land use intensity and the rate of farmland conversion to non-agricultural uses, were the primary drivers of temporal changes in multifunctional land use. The findings provide valuable references and scientific support for policymakers in optimizing land use and multifunctional landscape conservation.

Climate and Land Use Change Pressures on Food Production in Social-Ecological Systems: Perceptions from Farmers in Village Tank Cascade Systems of Sri Lanka

Climate and land use change pressures are critical to food production in Social-Ecological Systems (SESs). This study assessed farmers’ perceptions of the pressures of climate and land use changes alongside their impacts on food production in Mhahakanumulla Village Tank Cascade System (MVTCS), a SES maintained by traditional agricultural land use systems in the dry zone of Sri Lanka. This study used both rating and ranking scale questions to quantify farmers’ perceptions. The tobit regression model was employed to evaluate how farmer perception was influenced by socio-economic factors. The results showed that most of the farmers had experienced that the climate of the MVTCS area had changed over time, and they perceived variability of rainfall patterns as the most prominent and influential climate change. The increased cost of production, wildlife damage, and land degradation were ranked by the farmers as the most impactful factors of food production due to climate change. The farmers rated deforestation and land clearing as the most influential and impactful changes in land use, while wildlife damage and land degradation ranked as the highest impacts on food production due to land use changes. Among the socio-economic determinants, training and income/profit positively influenced farmer perceptions of the severity of both climate and land use change. The level of farmer’s adaptation to climate change had a negative association with their perception of the severity of climate change. Household size negatively influenced the perceptions of the severity of climate change while positively influencing perceptions of land use change impacts. Among the spatial determinants, farm size and downstream locations of MVTCS positively influenced perceptions of the severity of both climate and land use change. Thus, the effectiveness of adaptation strategies towards climate and land use change pressures depends on how well they are understood by the farmers. The study findings provide helpful insights for formulating localized land use policies and climate change adaptation strategies in these globally important landscapes with a combination of both top-down and bottom-up approaches.

Anthropogenic effects and ecosystem services of tropical highland forests in Ethiopia

Despite the significant direct and indirect benefits that forests, particularly tropical highland forests, provide to local communities, they are facing severe degradation primarily due to population growth and rapid land-use changes. This has made it difficult for policymakers to effectively manage these forests due to a lack of comprehensive current forest research data. Therefore, the primary objective of this study was to examine the anthropogenic impacts on forest ecosystems and the ecosystem services (11ecosystem services,ESs) they provide, as well as to understand local perspectives on management of natural forests. For collecting disturbance indicators and other environmental data, 12 transect lines by 150 meter interval between each of the two consecutive parallel transects and 40 quadrats (20 m x 20 m size each) by 100 m interval were laid out in 145 ha total forest land size of the five study sites of three districts. However, for questionnaire-based data, 266 respondents were participated. As revealed in the results, the majority of households (about 78 %) relied on mixed farming and had ≤ 1 ha of land with 5.6 average family size. Besides, 74.3 % of the households used forest products for cooking food and getting energy to their homes due to little or no electricity, or other energy sources in rural communities. Nearly 85 % of the households also obtained timber from natural forests. Tree cutting, grazing, cultivation, and fires were the major anthropogenic factors leading to deforestation and loss of ecosystem services and biodiversity of the studied forest ecosystems. Disturbance assessment indicated that almost all forest patches, excluding one in the eastern subregion of the study area, were severely impacted. This suggests a widespread degradation of Ethiopia's forests. However, various ESs, mainly regulating and habitat services, followed by provisioning ones, were delivered from these sites. Hence, soil erosion controlling, flood protecting, and soil fertility regulating services were some of the most services provided by the forests. Likewise, being shelter and nursery sites for biota were the other most important habitat service. The raw materials including grass for fodder, medicinal plants, timber, fuel wood, and water for livestock watering and domestic uses were the major provisioning services provided. Thus, more than 93 % of the households had a great interest for the protection and continuity of the present forest patches in the future. Briefly, despite being heavily degraded due to anthropogenic factors, these natural forests still provided various ecological, social, and economic services to the local people; thereby the people were interested in protecting and conserving them. Thus, for restoring degraded forest areas of the zone, community-based participatory conservation strategies were recommended.

Devastation of the cerrado of mato grosso do sul and the advance of arenization in the pardo river watershed

Despite the significant biodiversity in the Cerrado, the process of occupation, subsequent economic cycles, and intensification of agriculture in a predatory manner have caused profound alterations in this biome. This study analyzed changes in land use and land cover in the Cerrado of Mato Grosso do Sul between 1985 and 2022 by mapping and also investigating the formation and dynamics of sand dunes in the Bauru sedimentary basin, focusing on the Pardo River watershed. MapBiomas Network data, collection 8, were used for land use and land cover analysis. Arenization foci cartography was conducted using brightness index 2 based on Sentinel-2 satellite images in Sentinel Application Platform software. The historical analysis of land use and cover in the Cerrado of Mato Grosso do Sul revealed a rapid transformation of the landscape, with a drastic reduction of native vegetation and an intensification of large-scale monocultures. Between 1985 and 2022, the Cerrado of Mato Grosso Sul lost 4.6 million hectares of native vegetation (forest formations, savannahs, grasslands, and wetlands), representing 24.54% of this territory. Recent changes in land use include pasture-soybean and pasture-eucalyptus. In the Pardo River watershed, arenization foci cover an area of 17,834.34 hectares, with varying dimensions ranging from less than 1 hectare to 376.41 hectares. The arenization process occurs in different slope compartments, such as the base, slope, and interfluves. The physical and chemical characteristics of Quartzipsamments, such as low organic carbon content in soil, are associated with high rates of surface exposure and weakened load-dependent structures, leading to degradation. Arenization occurs where natural vegetation has been suppressed and soil has been depleted by poorly managed production processes.