[Temporal and Spatial Variation Characteristics of Carbon Storage in the Source Region of the Yellow River Based on InVEST and GeoSoS-FLUS Models and Its Response to Different Future Scenarios]

Regional land use change is the main cause of carbon storage changes in ecosystems. Predicting the impact of future land use changes on carbon storage is of great significance for the sustainable development of carbon storage functions. In recent years, under the combined action of natural and human factors, the land use in the source region of the Yellow River has changed significantly, and its carbon storage function has also changed accordingly. This study combined InVEST and GeoSoS-FLUS models to evaluate land use change and its impact on carbon storage in the source region of the Yellow River from 2000 to 2020 and from 2020 to 2040 under different scenarios. The results showed that:① from 2000 to 2020, the carbon storage in the source region of the Yellow River showed an overall upward trend, with a total increase of 11.59×10⁶ t. ② Over the past 20 years, the land use changes in the source region of the Yellow River included mainly the increase in the area of low-coverage grassland, construction land, and wetland and the decrease in the area of high-coverage grassland, medium-coverage grassland, and unused land, as well as the large-scale reduction of unused land and the reduction of grassland. The increase in the area of wetlands was the main reason for the increase in carbon storage. ③ Under the natural change scenario in 2040, the ecosystem carbon storage in the source region of the Yellow River was 871.34×10⁶ t, an increase of 3.92×10⁶ t compared with that in 2020. Under the ecological protection scenario, carbon storage increased significantly, with an increase of 13.53×10⁶ t compared with that in 2020. The results of this study can provide a scientific reference for the decision-making of land use management and the sustainable development of carbon storage function in the source region of the Yellow River.

Responses of soil greenhouse gas emissions to land use conversion and reversion-A global meta-analysis

Exploring the responses of greenhouse gas (GHG) emissions to land use conversion or reversion is significant for taking effective land use measures to alleviate global warming. A global meta-analysis was conducted to analyze the responses of carbon dioxide (CO₂ ), methane (CH₄ ), and nitrous oxide (N₂ O) emissions to land use conversion or reversion, and determine their temporal evolution, driving factors, and potential mechanisms. Our results showed that CH₄ and N₂ O responded positively to land use conversion while CO₂ responded negatively to the changes from natural herb and secondary forest to plantation. By comparison, CH₄ responded negatively to land use reversion and N₂ O also showed negative response to the reversion from agricultural land to forest. The conversion of land use weakened the function of natural forest and grassland as CH₄ sink and the artificial nitrogen (N) addition for plantation increased N source for N₂ O release from soil, while the reversion of land use could alleviate them to some degree. Besides, soil carbon would impact CO₂ emission for a long time after land use conversion, and secondary forest reached the CH₄ uptake level similar to that of primary forest after over 40 years. N₂ O responses had negative relationships with time interval under the conversions from forest to plantation, secondary forest, and pasture. In addition, meta-regression indicated that CH₄ had correlations with several environmental variables, and carbon-nitrogen ratio had contrary relationships with N₂ O emission responses to land use conversion and reversion. And the importance of driving factors displayed that CO₂ , CH₄ , and N₂ O response to land use conversion and reversion was easily affected by NH₄ ⁺ and soil moisture, mean annual temperature and NO₃ ^- , total nitrogen and mean annual temperature, respectively. This study would provide enlightenments for scientific land management and reduction of GHG emissions.

Optimization of Spatial Land Use Patterns with Low Carbon Target: A Case Study of Sanmenxia, China

Land use change is an important factor in atmospheric carbon emissions. Most of the existing studies focus on modeling the land use pattern for a certain period of time in the future and calculating and analyzing carbon emissions. However, few studies have optimized the spatial pattern of land use from the perspective of the impact of carbon emission constraints on land use structure. Therefore, in this study, the effects of land use change on carbon emissions from 1990 to 2020 were modeled using a carbon flow model for Sanmenxia, Henan, China, as an example. Then, the land use carbon emission function under the low carbon target was constructed, and the differential evolution (DE) algorithm was used to obtain the optimized land use quantity structure. Finally, the PLUS model was used to predict the optimal spatial configuration of land use patterns to minimize carbon emissions. The study produced three major results. (1) From 1990 to 2020, the structural change of land use in Sanmenxia mainly occurred between cultivated land, forest land, grassland and construction land. During this period of land use change, the carbon emissions from construction land first increased and then decreased, but despite the decrease, carbon emissions still exceeded carbon sinks, and the carbon metabolism of land use was still far from equilibrium. (2) Between 2010 and 2020, the area of cultivated land began to decrease, and the area of forest land rapidly increased, and land-use-related carbon emissions showed negative growth. This showed that the structural adjustment of energy consumption in Sanmenxia during the period decreased carbon emissions in comparison with the previous period. (3) A comparison of predicted optimized land use patterns with land use patterns in an as-is development scenario showed a decrease in construction land area of 23.05 km² in 2030 with a steady increase in forest land area and a decrease in total carbon emission of 20.43 t. The newly converted construction land in the optimized land use pattern was concentrated in the ribbon-clustered towns built during urban expansion along the Shaanling basin of the Yellow River and the Mianchi-Yima industrial development area.

Spatial-Temporal Changes and Simulation of Land Use in Metropolitan Areas: A Case of the Zhengzhou Metropolitan Area, China

Metropolitan areas are the main spatial units sustaining development. Investigating internal factor changes in metropolitan areas are of great significance for improving the quality of development in these areas. As an emerging national central city of China, Zhengzhou has experienced rapid urban expansion and urbanization. In this study, principal component analysis and the model and Geodetector model were used to comprehensively analyze the influencing factors of land use change in Zhengzhou from 1980 to 2015. Based on the CA-Markov model, we improved the accuracy of multi-criteria evaluation of suitability factors and simulated land use change in 2015. The results show that land use conversions in the study area between 1980 and 2015 were frequent, with the areas of farmland, woodland, grassland, water, and unused land decreasing by 5.00%, 17.12%, 21.59%, 18.31%, and 94.48%, respectively, while construction land increased by 53.61%. The key influences on land use change are the urbanization and growth of residential or non-agricultural populations. In 2035, the area of farmland in the study area will decrease by 11.09% compared with that in 2015 and construction land will increase by 38.94%, while the area of other land use types will not significantly change. Zhengzhou, as the center city, forms a diamond-shaped core development area of Zhengzhou-Kaifeng-Xinxiang-Jiaozuo, while Xuchang is considered an independent sub-center uniting the surrounding cities for expansion. With its radiation power of unipolar core development for many years and the developmental momentum of Zhengzhou-Kaifeng integration, Zhengzhou city jointly drives the economic development of the surrounding cities. The protection of farmland and control of the expansion of construction land are the major challenges for the Zhengzhou metropolitan area to achieve sustainable development.

Ecosystem Health Responses of Urban Agglomerations in Central Yunnan Based on Land Use Change

Land use change in urban agglomerations is gradually becoming a major cause and a key factor of global environmental change. As a consequence of the interaction between land use and ecological processes, the transformation in natural ecosystem structure and function with human activity disturbances demands a systematic assessment of ecosystem health. Taking the Central Yunnan urban agglomeration, undergoing transition and development, as an example, the current study reveals the typical land use change processes and then emphasizes the importance of spatial heterogeneity of ecosystem services in health assessment. The InVEST model-based ecosystem service assessment is incorporated into the ecosystem health evaluation, and hotspot analysis is performed to quantitatively measure the ecosystem health response degree to land use according to spatial latitude. The study had three major findings: First, the urban land expansion in the urban agglomeration of central Yunnan between 1990 and 2020 is the most significant. Further, the rate of the dynamic change of urban land is 16.86%, which is the highest among all land types. Second, the ecosystem health of the central Yunnan urban agglomeration is improving but with obvious spatial differences, showing a trend of increasing from urban areas to surrounding areas, with the lowest ecosystem health level and significant clustering in the areas where the towns are located. The ecosystem health level is mainly dominated by the two classes of ordinary and well grades, and the sum of the two accounts for 63.35% of the total area. Third, the process of land transfer, mutual transfer between forest and grassland, and conversion from cropland to forest land contributed the most to the improvement of ecosystem health across the study area. Furthermore, the conversion from cropland and grassland to urban land is an important cause of the sustained exacerbation of ecosystem health. Significantly, the study provides a scientific reference for maintaining ecosystem health and formulating policies for macro-control of land in the urban agglomerations of the mountain plateau.

Peatland Loss in Southeast Asia Contributing to U.S. Biofuel's Greenhouse Gas Emissions

Land use change (LUC) induced by biofuel production could lead to greenhouse gas (GHG) emissions, which potentially increase biofuel's carbon intensity. Among the sources of LUC-related emissions for soy biodiesel, the contribution from peatland loss to agricultural plantations in Southeast Asia remains uncertain. Here, we analyzed LUC in Malaysia and Indonesia and modeled its impacts on the GHG emissions of soy biodiesel produced in the United States. It shows that oil palm plantations have more than doubled over 2001-2016 and the area of palm-on-peatlands (PoP) has expanded 3.7 times. Over new palm plantations, the share of PoP is about 19% regardless of time and location and the emission factor (EF) for peatland-to-palm conversion is estimated to be 41.5 Mg CO₂ ha^-1 yr^-1. With these updates on PoP and EF, the contribution of peatland loss (0.7-5.1 g CO₂e MJ^-1) to biodiesel emissions is only 40-65% of previous estimates, which reduces discrepancies among model simulations used by different agencies. Based on emerging evidence on LUC and related carbon changes, our analysis reexamines regional peatland loss and its impacts on LUC emissions modeling and provides new insights into the estimation of LUC impacts on biofuels' carbon intensity.

Predicting range shifts of the giant pandas under future climate and land use scenarios

Understanding and predicting how species will respond to global environmental change (i.e., climate and land use change) is essential to efficiently inform conservation and management strategies for authorities and managers. Here, we assessed the combined effect of future climate and land use change on the potential range shifts of the giant pandas (Ailuropoda melanoleuca) in Sichuan Province, China. We used species distribution models (SDMs) to forecast range shifts of the giant pandas by the 2050s and 2070s under four combined climate and land use change scenarios. We also compared the differences in distributional changes of giant pandas among the five mountains in the study area. Our SDMs exhibited good model performance and were not overfitted, with a mean Boyce index of 0.960 ± 0.015 and a mean omission rate of 0.002 ± 0.003, and suggested that precipitation seasonality, annual mean temperature, the proportion of forest cover, and total annual precipitation are the most important factors in shaping the current distribution pattern of the giant pandas. Our projections of future species distribution also suggested a range expansion under an optimistic greenhouse gas emission, while suggesting a range contraction under a pessimistic greenhouse gas emission. Moreover, we found that there is considerable variation in the projected range change patterns among the five mountains in the study area. Especially, the suitable habitat of the giant panda is predicted to increase under all scenarios in the Minshan mountains, while is predicted to decrease under all scenarios in Daxiangling and Liangshan mountains, indicating the vulnerability of the giant pandas at low latitudes. Our findings highlight the importance of an integrated approach that combines climate and land use change to predict the future species distribution and the need for a spatial explicit consideration of the projected range change patterns of target species for guiding conservation and management strategies.

Influences of Land Policy on Urban Ecological Corridors Governance: A Case Study from Shanghai

The analysis of land use change (LUC) characteristics and the impact of policies related to urban ecological space is required to improve spatial planning and to support decision making regarding green infrastructure (GI) investment. This study employed Geo-informatic Tupu analysis and Fluctuation Potential Tupu analysis methods to analyze the characteristics of LUC in an urban ecological corridor (EC). To help understand the influence of land use policy on GI governance and support the optimization of spatial planning, we proposed a situation-structure-implementation-outcome (SSIO) policy cascade analysis framework. SSIO takes "place" as its starting point, then couples the local policy with the governance structure to promote the sustainability of urban commons governance. The results show that the land use type within an EC in the city is mainly cultivated land. However, between 2009 and 2019, cultivated land, construction land, and facility agricultural land all showed a decreasing trend, while forest land and garden land types underwent increasing trends. The LUC Tupu unit highlights the transition from cultivated land to forest land. Forest land has the greatest increase in area and accounts for 52.34% of the area of increasing land use. Cultivated land shows the greatest decrease in area and accounts for 70.30% of the area of decreasing trends. Based on the local policy situation of the metropolis, a land policy governance mechanism can be constructed by the establishment of a governance structure with local government as the core, using land consolidation as the platform, taking ecological spatial planning and inefficient construction land reduction as typical policy tools, and experimentally integrating the concept of Nature-based Solutions (NbS). In general, these findings may be applicable to other rapidly urbanizing cities around the world that are developing complex land use policies for ecological space governance.

Change of Rice Paddy and Its Impact on Human Well-Being from the Perspective of Land Surface Temperature in the Northeastern Sanjiang Plain of China

Large-scale and high-speed paddy land expansion has appeared in Northeast China since the 21st century, causing the change in land surface temperature. The lack of continuous investigation limits the exploration of discoveries in this region. To address this limitation, a collaborative approach that combined human-computer interaction technology, gravity center model and spatial analysis was established. It provided some new findings in spatiotemporal evolution, migration trajectory and surface cooling effect of the paddy field in Northeastern Sanjiang Plain, a center of paddy field planting in China. The results show that: (1) A sustained paddy expansion was monitored, with a total area ranging from 2564.58 km² to 11430.94 km², along with a rate of growth of 345.72% from 2000 to 2020. Correspondingly, its reclamation rate changed to 47.53% from 10.66%, showing the improved planting level of the paddy field. (2) Gravity center of paddy field continued to be revealed northward with a 5-year interval from 2000 to 2020. Migration distance of the straight line reached 23.94 km², with the direction offset of 27.20° from east to north. (3) Throughout the growing season of crops, the land surface temperature of paddy field was 27.73°, 29.38°, 27.01°, 25.62° and 22.97° from May to October; and the cooling temperature effect of paddy field was investigated, with the reduced values of 0.61°, 0.79° and 1.10° in the low-, medium- and high-paddy field density regions from 2000 to 2020, respectively. Overall, these new findings in the cold temperate zone, high latitude region of the Northern Hemisphere, provided the reference for the investigation of paddy field monitoring and its environmental effects in China and other regions.

[Spatial and temporal variations of ecosystem service synergy and trade-off in Qinling Mountains, China]

The Qinling Mountains are an important ecological function area in China. Exploring the trade-offs and synergies of ecosystem services is important for ecological protection and sustainable development in the Qinling Mountains. In this study, we analyzed the spatio-temporal variations of land uses in the Qinling Mountains in 2000, 2010 and 2020 based on remote sensing, meteorological, and soil texture data. The amounts of carbon sequestration, water yield, habitat quality, and soil conservation were calculated with CASA, InVEST and RUSLE models. The relationships between its spatially heterogeneous characteristics and various ecosystem services were analyzed. The results showed that, from 2000 to 2020, the area of arable land and grassland in the study area continued to decrease, the area of forest and building land increased, and the change of water body and unused land was not noticeable. Carbon sequestration was high in the east and low in the west, with an increasing trend. Water production continued to decrease, showing a tendency of higher on the south slope and lower on the north slope. Habitat quality increased steadily, while soil conservation increased and then decreased. Ecosystem services varied across land classes and across ecosystems in the same land class. In general, there was a synergistic relationship between carbon sequestration and soil conservation, habitat quality and soil conservation, carbon sequestration, and habitat quality. There was trade-off between carbon sequestration and water production, soil conservation and water production, habitat quality, and water production. There were significant differences in the relationship between service volumes under different conditions. The results could reduce the risk of trade-offs and maximize overall benefits, and provide a reference for promoting ecologically high-quality development and achieving a win-win situation for natural resource management and human well-being.

Global patterns of soil gross immobilization of ammonium and nitrate in terrestrial ecosystems

Microbial nitrogen (N) immobilization, which typically results in soil N retention but based on the balance of gross N immobilization over gross N production, affects the fate of the anthropogenic reactive N. However, global patterns and drivers of soil gross immobilization of ammonium (I_NH4 ) and nitrate (I_NO3 ) are still only tentatively known. Here, we provide a comprehensive analysis considering gross N production rates, soil properties, and climate and their interactions for a deeper understanding of the patterns and drivers of I_NH4 and I_NO3 . By compiling and analyzing 1966 observations from 274 ¹⁵ N-labelled studies, we found a global average of I_NH4 and I_NO3 of 7.41 ± 0.72 and 2.03 ± 0.30 mg N kg^-1  day^-1 with a ratio of I_NO3 to I_NH4 (I_NO3 :I_NH4 ) of 0.79 ± 0.11. Soil I_NH4 and I_NO3 increased with increasing soil gross N mineralization (GNM) and nitrification (GN), microbial biomass, organic carbon, and total N and decreasing soil bulk density. Our analysis revealed that GNM and GN were the main stimulators for I_NH4 and I_NO3 , respectively. The structural equation modeling showed that higher soil microbial biomass, total N, pH, and precipitation stimulate I_NH4 and I_NO3 through enhancing GNM and GN. However, higher temperature and soil bulk density suppress I_NH4 and I_NO3 by reducing microbial biomass and total N. Soil I_NH4 varied with terrestrial ecosystems, being greater in grasslands and forests, which have higher rates of GNM, than in croplands. The highest I_NO3 :I_NH4 was observed in croplands, which had higher rates of GN. The global average of GN to I_NH4 was 2.86 ± 0.31, manifesting a high potential risk of N loss. We highlight that anthropogenic activities that influence soil properties and gross N production rates likely interact with future climate changes and land uses to affect soil N immobilization and, eventually, the fate of the anthropogenic reactive N.

Assessing land use influences on isotopic variability and stream water ages in urbanising rural catchments

Stable water isotopes are invaluable in helping understand catchment functioning and are widely used in experimental catchments, with higher frequency data becoming increasingly common. Such datasets incur substantial logistical costs, reducing their feasibility for use by decision makers needing to understand multi-catchment, landscape-scale functioning over a relatively short period to assess the impact of proposed land use change. Instead, reconnaissance style surveys (high spatial resolution across the landscape at a lower temporal frequency, over a relatively short period) offer an alternative, complementary approach. To test if such sampling could identify heterogeneities in hydrological functioning, and associated landscape controls, we sampled 27 stream sites fortnightly for one year within a peri-urban landscape undergoing land use change. Visual examination of raw data and application of mean transit time and young water fraction models indicated urbanisation, agriculture and responsive soils caused more rapid cycling of precipitation to stream water, whereas mature forestry provided attenuation. We were also able to identify contiguous catchments which functioned fundamentally differently, meaning their response to land use alteration would also be different. This study demonstrated how stable water isotopes can be a valuable, low-cost addition to tools available for environmental decision makers by providing local, process-based information.

Spatial and Temporal Variations of Habitat Quality and Its Response of Landscape Dynamic in the Three Gorges Reservoir Area, China

Habitat quality is an important indicator for assessing biodiversity and is critical to ecosystem processes. With urban development and construction in developing countries, habitat quality is increasingly influenced by landscape pattern changes. This has made habitat conservation to be an increasingly urgent issue. Despite the growing interest in this issue, studies that reveal the role of land use change in habitat degradation at multiple scales are still lacking. Therefore, we analyzed the spatial and temporal variations of habitat quality of the Three Gorges Reservoir area by the InVEST habitat quality model and demonstrated the responses of habitat quality to various landscape dynamics by correspondence analysis. The result showed that the habitat quality score of this area increased from 0.685 in 2000 to 0.739 in 2015 and presented a significant spatial heterogeneity. Habitat quality was significantly higher in the northeastern and southwestern parts of the reservoir area than in other regions. Meanwhile, habitat quality improved with altitude and slope, and increased for all altitude and slope zones. The habitat quality of >1000 m and >25° zone exceeds 0.8, while the habitat quality of <500 m and <15° zone is less than 0.6. Habitat quality significantly varied among landscape dynamics and was extremely sensitive to vegetation recovery and urban expansion. The vegetation restoration model of returning farmland to forest is difficult to sustain, so we suggest changing the vegetation recovery model to constructing complex vegetation community. This study helps us to better understand the effects of landscape pattern changes on habitat quality and can provide a scientific basis for formulating regional ecological conservation policies and sustainable use of land resources.

Response of Ecosystem Health to Land Use Changes and Landscape Patterns in the Karst Mountainous Regions of Southwest China

The quantitative assessment of ecosystem health is important for interpreting the ecological effects of land use changes and formulating effective measures of sustainable ecological development by policymakers. This study investigated the response of ecosystem health to land use changes and landscape patterns in the karst mountainous regions of southwest China by taking Guiyang City as a case study area and assessing the spatial and temporal changes in ecosystem health from 2008 to 2017 using the vigor–organization–resilience model; it analyzed the influence of land use changes and landscape patterns on ecosystem health using spatial overlay analysis, the Dunnett’s T3 test, and the Spearman correlation analysis. The results show that the land use structure dramatically changed, with a trend of a sharp decrement of farmland and rapid increment of forestland and construction land due to rapid urbanization and ecologization. The overall ecosystem health was at a relatively strong level, with the average value greater than 0.6. The deterioration of ecosystem health was attributed to the expansion of construction land and farmland and the degradation of forestland, while the increment of forestland was the major contributor to the improvement of ecosystem health. The ecosystem health of the forestland + farmland landscape was significantly superior to that of forestland + construction land and construction land + farmland landscapes. Moreover, each landscape configurations had a significant positive or negative correlation with the ecosystem health. This study provides a valuable reference for formulating sustainable environmental management strategies in karst mountainous regions in China.

Climate change aggravates non-target effects of pesticides on dragonflies at macroecological scales

Critical gaps in understanding how species respond to environmental change limit our capacity to address conservation risks in a timely way. Here, we examine the direct and interactive effects of key global change drivers, including climate change, land use change, and pesticide use, on persistence of 104 odonate species between two time periods (1980-2002 and 2008-2018) within 100 × 100 km quadrats across the USA using phylogenetic mixed models. Non-target effects of pesticides interacted with higher maximum temperatures to contribute to odonate declines. Closely related species responded similarly to global change drivers, indicating a potential role of inherited traits in species' persistence or decline. Species shifting their range to higher latitudes were more robust to negative impacts of global change drivers generally. Inherited traits related to dispersal abilities and establishment in new places may govern both species' acclimation to global change and their abilities to expand their range limits, respectively. This work is among the first to assess effects of climate change, land use change, and land use intensification together on Odonata, a significant step that improves understanding of multispecies effects of global change on invertebrates, and further identifies conditions contributing to global insect loss.

Environmental outcomes of the US Renewable Fuel Standard

The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and thereby guides nearly half of all global biofuel production, yet outcomes of this keystone climate and environmental regulation remain unclear. Here we combine econometric analyses, land use observations, and biophysical models to estimate the realized effects of the RFS in aggregate and down to the scale of individual agricultural fields across the United States. We find that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 2.8 Mha (8.7%) and total cropland by 2.1 Mha (2.4%) in the years following policy enactment (2008 to 2016). These changes increased annual nationwide fertilizer use by 3 to 8%, increased water quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision-makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.

Projecting the Impact of Socioeconomic and Policy Factors on Greenhouse Gas Emissions and Carbon Sequestration in U.S. Forestry and Agriculture

Understanding greenhouse gas mitigation potential of the U.S. agriculture and forest sectors is critical for evaluating potential pathways to limit global average temperatures from rising more than 2° C. Using the FASOMGHG model, parameterized to reflect varying conditions across shared socioeconomic pathways, we project the greenhouse gas mitigation potential from U.S. agriculture and forestry across a range of carbon price scenarios. Under a moderate price scenario ($20 per ton CO2 with a 3% annual growth rate), cumulative mitigation potential over 2015-2055 varies substantially across SSPs, from 8.3 to 17.7 GtCO2e. Carbon sequestration in forests contributes the majority, 64-71%, of total mitigation across both sectors. We show that under a high income and population growth scenario over 60% of the total projected increase in forest carbon is driven by growth in demand for forest products, while mitigation incentives result in the remainder. This research sheds light on the interactions between alternative socioeconomic narratives and mitigation policy incentives which can help prioritize outreach, investment, and targeted policies for reducing emissions from and storing more carbon in these land use systems.

Ephemeral forest regeneration limits carbon sequestration potential in the Brazilian Atlantic Forest

Although deforestation remains widespread in the tropics, many places are now experiencing significant forest recovery (i.e., forest transition), offering an optimistic outlook for natural ecosystem recovery and carbon sequestration. Naturally regenerated forests, however, may not persist, so a more nuanced understanding of the drivers of forest change in the tropics is critical to ensure the success of reforestation efforts and carbon sequestration targets. Here we use 35 years of detailed land cover data to investigate forest trajectories in 3014 municipalities in the Brazilian Atlantic Forest (AF), a biodiversity and conservation hotspot. Although deforestation was evident in some regions, deforestation reversals, the typical forest transition trajectory, were the prevalent trend in the AF, accounting for 38% of municipalities. However, simultaneous reforestation reversals in the region (13% of municipalities) suggest that these short-term increases in native forest cover do not necessarily translate into persistent trends. In the absence of reversals in reforestation, forests in the region could have sequestered 1.75 Pg C, over three times the actual estimated carbon sequestration (0.52 Pg C). We also showed that failure to distinguish native and planted forests would have masked native forest cover loss in the region and overestimated reforestation by 3.2 Mha and carbon sequestration from natural forest regeneration by 0.37 Pg C. Deforestation reversals were prevalent in urbanized municipalities with limited forest cover and high agricultural productivity, highlighting the importance of favorable socioeconomic conditions in promoting reforestation. Successful forest restoration efforts will require development and enforcement of environmental policies that promote forest regeneration and ensure the permanence of regrowing forests. This is crucial not only for the fate and conservation of the AF, but also for other tropical nations to achieve their restoration and carbon sequestration commitments.

Belowground Root Competition Alters the Grass Seedling Establishment Response to Light by a Nitrogen Addition and Mowing Experiment in a Temperate Steppe

Predicting species responses to climate change and land use practices requires understanding both the direct effects of environmental factors as well as the indirect effects mediated by changes in belowground and aboveground competition. Belowground root competition from surrounding vegetation and aboveground light competition are two important factors affecting seedling establishment. However, few studies have jointly examined the effect of belowground root and light competition on seedling establishment, especially under long-term nitrogen addition and mowing. Here, we examined how belowground root competition from surrounding vegetation and aboveground light competition affect seedling establishment within a long-term nitrogen addition and mowing experiment. Seedlings of two grasses (Stipa krylovii and Cleistogenes squarrosa) were grown with and without belowground root competition under control, nitrogen addition, and mowing treatments, and their growth characteristics were monitored. The seedlings of the two grasses achieved higher total biomass, height, mean shoot and root mass, but a lower root/shoot ratio in the absence than in the presence of belowground root competition. Nitrogen addition significantly decreased shoot biomass, root biomass, and the survival of the two grasses. Regression analyses revealed that the biomass of the two grass was strongly negatively correlated with net primary productivity under belowground root competition, but with the intercept photosynthetic active radiation in the absence of belowground root competition. This experiment demonstrates that belowground root competition can alter the grass seedling establishment response to light in a long-term nitrogen addition and mowing experiment.

Landscape Evolution and Simulation of Rural Settlements around Wetland Park Based on MCCA Model and Landscape Theory: A Case Study of Chaohu Peninsula, China

As a transitional zone between urban and rural areas, the peri-urban areas are the areas with the most intense urban expansion and the most frequent spatial reconfiguration, and in this context, it is particularly important to reveal the evolution pattern of rural settlements in the peri-urban areas to provide reference for the rearrangement of rural settlements. The study takes five townships in the urban suburbs, and explores the scale, shape, spatial layout, and spatial characteristics of the urban suburbs of Hefei from 1980 to 2030 under the influence of urban-lake symbiosis based on spatial mathematical analysis and geographical simulation software. The study shows that: (1) the overall layout of rural settlements in the study area is randomly distributed due to the hilly terrain, but in small areas there is a high and low clustering phenomenon, and the spatial density shows the distribution characteristics of “high in the east and low in the west”; (2) since the reform and opening up, there are large spatial differences in the scale of rural settlements in the study area. (3) Different development scenarios have a strong impact on the future spatial pattern of rural settlement land use within the study area, which is a strong reflection of policy.

Knowledge Mapping of Research on Land Use Change and Food Security: A Visual Analysis Using CiteSpace and VOSviewer

Many scholars have conducted in-depth research on the theme of land use change and food security, and formed fruitful research results, but there is a lack of quantitative analysis and comprehensive evaluation of research achievements. Therefore, based on the relevant literature on the theme of land use change and food security in the core collection of the Web of Science (WOS) database, this paper takes the advantage of CiteSpace and VOSviewer bibliometric software to draw the cooperative network and keyword cooccurrence map to analyze the research progress and frontier. The results reveal that: (1) The research started in 1999 and can be divided into three stages: initial research, rapid development, and a stable in-depth stage. This topic has increasingly become a research hotspot in the academic community. (2) The distribution of research institutions is concentrated and forms a small cluster, and the research networks between developed and developing countries have been established, and developed countries are in the core position, but the cooperation network is not prominent. (3) The research content is becoming increasingly organized and systematic, and the research hot topics are divided into seven aspects. (4) The research area of the subject covers multiple levels, such as global, national, and specific natural geographical regions, and has formed a research system of geographic information technology and satellite remote sensing technology. It also presents the trend of cross integration with economics, land management and soil science. In the future, theoretical innovation still needs to be strengthened, and we should strengthen the research on the impact of agricultural chemical fertilizers on food security and study the impact of urban expansion on land use change.

Identifying Key Drivers of Peatland Fires Across Kalimantan's Ex-Mega Rice Project Using Machine Learning

Throughout Indonesia ecological degradation, agricultural expansion, and the digging of drainage canals has compromised the integrity and functioning of peatland forests. Fragmented landscapes of scrubland, cultivation, degraded forest, and newly established plantations are then susceptible to extensive fires that recur each year. However, a comprehensive understanding of all the drivers of fire distribution and the conditions of initiation is still absent. Here we show the first analysis in the region that encompasses a wide range of driving factors within a single model that captures the inter-annual variation, as well as the spatial distribution of peatland fires. We developed a fire susceptibility model using machine learning (XGBoost random forest) that characterizes the relationships between key predictor variables and the distribution of historic fire locations. We then determined the relative importance of each predictor variable in controlling the initiation and spread of fires. The model included land-cover classifications, a forest clearance index, vegetation indices, drought indices, distances to infrastructure, topography, and peat depth, as well as the Oceanic Niño Index (ONI). The model performance consistently scores highly in both accuracy and precision across all years (>75% and >67.5% respectively), though recall metrics are much lower (>25%). Our results confirm the anthropogenic dependence of extreme fires in the region, with distance to settlements and distance to canals consistently weighted the most important driving factors within the model structure. Our results may help target the root causes of fire initiation and propagation to better construct regulation and rehabilitation efforts to mitigate future fires.

Predicted declines in suitable habitat for greater one-horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios

Rapidly changing climate is likely to modify the spatial distribution of both flora and fauna. Land use change continues to alter the availability and quality of habitat and further intensifies the effects of climate change on wildlife species. We used an ensemble modeling approach to predict changes in habitat suitability for an iconic wildlife species, greater one-horned rhinoceros due to the combined effects of climate and land use changes. We compiled an extensive database on current rhinoceros distribution and selected nine ecologically meaningful environmental variables for developing ensemble models of habitat suitability using ten different species distribution modeling algorithms in the BIOMOD2 R package; and we did this under current climatic conditions and then projected them onto two possible climate change scenarios (SSP1-2.6 and SSP5-8.5) and two different time frames (2050 and 2070). Out of ten algorithms, random forest performed the best, and five environmental variables-distance from grasslands, mean temperature of driest quarter, distance from wetlands, annual precipitation, and slope, contributed the most in the model. The ensemble model estimated the current suitable habitat of rhinoceros to be 2610 km2, about 1.77% of the total area of Nepal. The future habitat suitability under the lowest and highest emission scenarios was estimated to be: (1) 2325 and 1904 km2 in 2050; and (2) 2287 and 1686 km2 in 2070, respectively. Our results suggest that over one-third of the current rhinoceros habitat would become unsuitable within a period of 50 years, with the predicted declines being influenced to a greater degree by climatic changes than land use changes. We have recommended several measures to moderate these impacts, including relocation of the proposed Nijgad International Airport given that a considerable portion of potential rhinoceros habitat will be lost if the airport is constructed on the currently proposed site.

Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections

Land use and climate change are anticipated to affect phytoplankton of lakes worldwide. The effects will depend on the magnitude of projected land use and climate changes and lake sensitivity to these factors. We used random forests fit with long-term (1971-2016) phytoplankton and cyanobacteria abundance time series, climate observations (1971-2016), and upstream catchment land use (global Clumondo models for the year 2000) data from 14 European and 15 North American lakes basins. We projected future phytoplankton and cyanobacteria abundance in the 29 focal lake basins and 1567 lakes across focal regions based on three land use (sustainability, middle of the road, and regional rivalry) and two climate (RCP 2.6 and 8.5) scenarios to mid-21st century. On average, lakes are expected to have higher phytoplankton and cyanobacteria due to increases in both urban land use and temperature, and decreases in forest habitat. However, the relative importance of land use and climate effects varied substantially among regions and lakes. Accounting for land use and climate changes in a combined way based on extensive data allowed us to identify urbanization as the major driver of phytoplankton development in lakes located in urban areas, and climate as major driver in lakes located in remote areas where past and future land use changes were minimal. For approximately one-third of the studied lakes, both drivers were relatively important. The results of this large scale study suggest the best approaches for mitigating the effects of human activity on lake phytoplankton and cyanobacteria will depend strongly on lake sensitivity to long-term change and the magnitude of projected land use and climate changes at a given location. Our quantitative analyses suggest local management measures should focus on retaining nutrients in urban landscapes to prevent nutrient pollution from exacerbating ongoing changes to lake ecosystems from climate change.

Gray Forecast of Ecosystem Services Value and Its Driving Forces in Karst Areas of China: A Case Study in Guizhou Province, China

A sound ecosystem is the prerequisite for the sustainable development of human society, and the karst ecosystem is a key component of the global ecosystem, which is essential to human welfare and livelihood. However, there remains a gap in the literature on the changing trend and driving factors of ecosystem services value (ESV) in karst areas. In this study, Guizhou Province, a representative region of karst mountainous areas, was taken as a case to bridge the gap. ESV in the karst areas was predicted, based on the land use change data in 2009-2018, and the driving mechanisms were explored through the gray correlation analysis method. Results show that a total loss of CNY 21.47 billion ESV from 2009 to 2018 is due to the conversion of a total of 22.566% of the land in Guizhou, with forest land as the main cause of ESV change. By 2025 and 2030, the areas of garden land, water area, and construction land in Guizhou Province will continue to increase, whereas the areas of cultivated land, forest land, and garden land will decline. The total ESV shows a downward trend and will decrease to CNY 218.71 billion by 2030. Gray correlation analysis results illuminate that the total population and tertiary industry proportion are the uppermost, among all the driving factors that affect ESV change. The findings in this study have important implications for optimizing and adjusting the land use structure ecological protection and will enrich the literature on ESV in ecologically fragile areas.