Land Use Change Research Articles

Understanding future water-carbon-land coupled systems in the era of COP 27: The case of the Hanjiang river Basin, China

The 27th Conference of the Parties (COP 27) emphasized addressing this century's interconnected challenges of food, water, and energy. This study proposes a coupled ecosystem service and multi-scenario land-use change simulation model designed to investigate the future dynamics of water-carbon-land coupled systems in the Hanjiang River Basin (HJRB), the primary objective is to provide valuable insights that can inform strategic spatial management decisions, aligning with the ambitious objectives outlined in COP 27. Specifically, this study utilized the PLUS model, InVEST model, and redundancy analysis to comprehensively analyze the interplay between ecosystem services and land-use changes, with a specific focus on water, carbon, and land dynamics. The results showed that regardless of the simulated scenarios, there was a consistent pattern observed in the changes of land use types within the HJRB, with a decrease in farmland and an increase in forest. However, the water area showed an increasing trend in all scenarios, especially in the ecological land protection (ELP) and sustainable development scenarios. Furthermore, the ELP scenario effectively suppressed the expansion of building land and the erosion of ecological land. Ecosystem services under different scenarios showed similar spatial distribution patterns but presented varying degrees of change related to the impact of future land use and urban development on ecosystem services. The water yield (WY), carbon storage, and soil conservation in the upstream areas increased to varying degrees, while those in the downstream areas decreased. In conclusion, precipitation, land use/land cover change, DEM (Digital Elevation Model), and NDVI (Normalized Difference Vegetation Index) were the main driving factors affecting ecosystem services, with precipitation having the most significant and enduring impact on WY. This study supports the adoption of targeted spatial management measures to promote sustainable development and enhance human well-being.

Controls on channel planform changes in rivers of the Atlantic Coastal Plain: Findings from the Congaree river valley (South Carolina, USA)

Rivers shaped the landscape of the Atlantic Coastal Plain during the last tens of thousands years. However, their spatial and temporal evolution is understudied. We conducted geophysical, geological and remote sensing surveys in the Congaree River valley, characterized by numerous traces of palaeochannels preserved in the floodplain. The age of the former channels was determined by AMS radiocarbon dating. The main goal of our study was to identify factors controlling the river planform changes and compare the findings with other rivers of the Atlantic Coastal Plain. We found that the Congaree floodplain was shaped by single-thread channels characterized by formation of levees and floodbasins at least 34,000 cal. BP. Large-scale meanders were active between 16,000 and 12,000 cal. BP. They were replaced by meandering channel belts shifting by avulsions between 12,000 and 3,000 cal. BP. Compound meanders have been formed during the last 3000 years. Traces of these channel planforms are also present in other rivers of the Atlantic Coastal Plain. The abandonment of the large-scale meanders was caused by increase in climate humidity, changes in vegetation cover, and inundation of the coastal plain by the ocean level rise, resulting in base-level rise. The avulsions of meander belts in the Early and Middle Holocene were formed in conditions of a humid climate, a series of flooding periods, and continued base-level rise. A relatively drier climate in the Late Holocene caused a change in the meanders’ evolution from the channel belts shifting by avulsions to compound meanders evolving by cutoffs. The last 200 years were dominated by a huge delivery and deposition of fines, caused by deforestation and land-use changes in the river valleys.

Spatiotemporal Evolution and Driving Factors of Land Use Carbon Emissions in Jiangxi Province, China

Analyzing the spatiotemporal changes and influencing factors of carbon emissions generated by land use is of great importance for improving land use structure and promoting regional low-carbon economic development. This study, based on remote sensing and statistical yearbook data from 1995 to 2020, calculated the carbon emissions from land use in Jiangxi Province, China. Multiple spatial analysis methods and the logarithmic mean Divisia index were used to elucidate the spatiotemporal evolution and driving factors of carbon emissions, and the findings revealed the following: (1) The spatiotemporal changes in land use in Jiangxi Province during 1995–2020 were substantial as forest land accounted for 65% of the entire land area, while construction land increased by 98.1%. Cultivated land decreased the most, followed by forest land. (2) There was a fourfold rise in carbon emissions in Jiangxi Province, driven primarily by construction land, and northern areas produced higher carbon emissions compared with central and southern regions. Forest land was the main carbon sink. (3) Economic development (257.36%) and the impact of the proportion of construction land (211.31%) were the primary factors contributing to the increase in carbon emissions from land use, while other factors had inhibitory effects. This study transformed the macroscale low-carbon development strategy of cities into targeted local policies, and the research theories and methods adopted could provide scientific reference for other regions in urgent need of carbon reduction worldwide.

Effects of land use change on runoff depth in the Songnen Plain, China.

Climate change and human activities both have a considerable impact on runoff depth, which are important parts of a changing ecosystem. Nevertheless, the main focus of hydrological response research has been on investigating the impact of climate change on the depth of runoff. In contrast, there has been limited emphasis on comprehending the precise mechanisms through which changes in land use, in relation to human activities, influence runoff depth. This paper employs the MIKE SHE/MIKE 11 model to simulate surface runoff in the study area from 1980 to 2020, assesses the effects of climate change and land use change on runoff depth using the runoff reduction method, and quantifies the influence of land use change on runoff depth through a spatio-temporal geographically weighted regression model. This study indicates that during the past 40 years, the average runoff depth in the Songnen Plain was 36.26mm, exhibiting a tendency of 'increasing-decreasing-increasing'. The impact of climate change on surface runoff depth is more substantial than that of land use change. During the impact period 1, the runoff depth diminished by 19.07mm, with climate change contributing to a decrease of 15.89mm (83.31% contribution). In the impact period 2, the runoff depth increased by 7.49mm relative to the baseline period, with climate change leading to an increase of 12.73mm (70.84% contribution). Changes in various land types within the watershed can be used to observe the influence of human activities on runoff depth. More precisely, a 10% rise in the rate of change of construction land, dry land, and unoccupied land results in an increase in runoff depth of 6.21mm, 2.45mm, and 1.14mm, respectively. Conversely, a 10% rise in the rate of alteration of marsh, paddy, and forest land leads to a reduction in the depth of runoff by 9.49mm, 6.46mm, and 3.07mm, respectively. This research can contribute to improving the efficiency of water and land resource utilization and optimizing land resource governance.

Multi-Scenario Simulation of Land Use and Assessment of Carbon Stocks in Terrestrial Ecosystems Based on SD-PLUS-InVEST Coupled Modeling in Nanjing City

In the context of achieving the goal of carbon neutrality, exploring the changes in land demand and ecological carbon stocks under future scenarios at the urban level is important for optimizing regional ecosystem services and developing a land-use structure consistent with sustainable development strategies. We propose a framework of a coupled system dynamics (SD) model, patch generation land-use simulation (PLUS) model, and integrated valuation of ecosystem services and trade-offs (InVEST) model to dynamically simulate the spatial and temporal changes of land use and land-cover change (LUCC) and ecosystem carbon stocks under the NDS (natural development scenario), EPS (ecological protection scenario), RES (rapid expansion scenario), and HDS (high-quality development scenario) in Nanjing from 2020 to 2040. From 2005 to 2020, the expansion rate of construction land in Nanjing reached 50.76%, a large amount of ecological land shifted to construction land, and the ecological carbon stock declined dramatically. Compared with 2020, the ecosystem carbon stocks of the EPS and HDS increased by 2.4 × 106 t and 1.5 × 106 t, respectively, with a sizable ecological effect. It has been calculated that forest and cultivated land are the two largest carbon pools in Nanjing, and the conservation of both is decisive for the future carbon stock. It is necessary to focus on enhancing the carbon stock of forest ecosystems while designating differentiated carbon sink enhancement plans based on the characteristics of other land types. Fully realizing the carbon sink potential of each ecological functional area will help Nanjing achieve its carbon neutrality goal. The results of the study not only reveal the challenges of ecological conservation in Nanjing but also provide useful guidance for enhancing the carbon stock of urban terrestrial ecosystems and formulating land-use planning in line with sustainable development strategies.

Exploring the LULC dynamics and its relation with land surface temperature variation using split window algorithm: A study of Barasat subdivision, West Bengal, India.

Rapid urban growth in an unplanned way, decreased forest cover and consequential changes in land use in urban and rural areas have become pivotal obstacles for policymakers and urban planners to a great extent. Specifically, in a developing country like India, the repercussions of these changes have generated a substantial alteration in climate in the form of increased land surface temperature (LST), heat islands and associated human health risks. This research was initiated to assess the interrelationship between LST and LULC dynamics using spatial techniques over the Barasat Sub-Division in West Bengal (India). This study encompasses the extraction of LST using satellite images, seasonal variations of LST, the relationship of different land indices (i.e. NDVI, NDBI, NDMI and NDWI) with LST, and hotspot analysis of the landscape to get a comprehensive understanding of LST changes from 1988 to 2023, seasonal patterns, and relationships with LULC dynamics in the study area. The results of this research signify a substantial percentage increase in built-up spaces (51%), a decline in fallow areas (- 73%), relatively higher LST changes (3.41°C) in high-density built-up areas (e.g. Madhyamgram), a positive relationship (e.g. r2 = 0.59) between NDBI and LST, a transition from a cold spot to a hot spot share of 20% and a persisting hot spot of 42% throughout the summer season (1988 to 2023) in the selected landscape. The findings of this study will improve our present knowledge of seasonal fluctuations in land surface temperature (LST) and the variables that influence them. These findings will also draw attention to the growing worries about the fast variations in LST and the climatic and health hazards they pose. It is advised to establish planned urban expansion, efficient land use and land cover (LULC) management laws and encourage green areas that support sustainable development in India's urban surroundings in order to reduce these dangers.

Spatial Analysis of the Impacts Caused by Changes in Land Use on the Estimation of Surface Temperature in the The City of Paracatu (MG)

The increase in built-up areas, coupled with the suppression of vegetation without the necessary mitigating measures to curb the effects of urbanization, causes changes in the microclimate and directly impacts the health of the local population. In this sense, the present study aims to analyze the influence of land cover type on the variation of Land Surface Temperature (LST) estimation in the city of Paracatu, Minas Gerais (MG), in the years 1990 and 2020.For this, the maps provided by the Annual Mapping of Land Cover and Land Use of Brazil (MapBiomas) and images from the LANDSAT-5 (1990) and LANDSAT-8 (2020) satellites were used. Four images, distributed across seasons, were utilized to estimate LST for these periods, aiming to obtain a representative LST estimate for that year. For the calculation of the LST with bands 6 and 10, respectively of the LANDSAT-5 and 8 satellites, the SCP plugin of the QGIS software was used, and the process of recovery of the LST in the scenes used occurred through conversion of the values of the Digital Number (DN) into radiance at the Top of the Atmosphere (ToA), conversion of radiance into brightness temperature in ToA, correction of atmospheric effects and obtaining LST in Kelvin and, subsequently, in degrees Celsius. After that, the average between them was performed by means of normalization of each of the scenes, obtaining a representative mosaic for the LST of each year,thus enabling the estimation of the spatial behavior of the minimum, mean, and maximum values.. Finally, in order to verify the influence of Changes in Use and Occupation (LULC) on the spatial variation of the LST, the classes found in Vegetation, Exposed Soil, Urban Area and Water Resources were segmented, and it was found that, while the urban area of Paracatu had its territorial extension practically doubled, the vegetation class decreased by almost 25%, a fact that implied in the average increase of the LST by more than 5º C. the minimum and maximum values of these classes varied around 4.5 and 3º C, and it is possible to conclude that, in this interval of 30 years, Paracatu had no urban growth occurring exponentially and without the proper mitigations for the transformation of the microclimate, implying the need for measures that can curb these changes in strategic points of the municipality, as in the Bom Pastor neighborhood, which had its use and occupation totally changed in this temporal hiatus. In addition, in view of the estimates of economic growth in the city, it is believed that these measures should be taken as a matter of urgency, so that the results presented here can support the decisions of the managing public agencies.

Choosing reference land use for carbon and biodiversity footprints

Abstract Purpose Carbon and biodiversity footprints are increasingly calculated. However, little attention has been paid to the coherency of methodological choices and interpretation of the footprint results. This paper aims to clarify the coherency between the choice of reference land use and carbon and biodiversity footprints and discuss the challenges encountered. Methods First, we analyse features of reference land use options proposed in ISO 14067 (2018) i.e. business as usual, projected future, target, potential natural regeneration and historic baseline. Second, we discuss the connection between temporal scope and life cycle of land use. Third, we provide guidance on how to choose reference land use coherently. Fourth, we discuss specific issues related to carbon and biodiversity footprints and their relationship to reference land use. Finally, we provide conclusions and recommendations for further conceptual development. Results and discussion Choice of reference land use and determination of temporal scope of a study may significantly influence the assessment of carbon or biodiversity footprints. If the aim of a footprint study is to assess the effects of land use, reference land use should describe dynamically non-use of land. Thus, potential natural regeneration or continuation of natural state (if it is the starting point) of land is the coherent reference land use in this case. If the aim of a footprint study is to assess the effects of a decision to change land use or its management, reference land use should describe dynamically alternative use of land expected without the studied decision. Business as usual or projected future is a coherent reference land use in this case. Historic baseline or target reference land use may be useful in comparing the ecosystem value of the studied land use with a pre-set historic baseline or (policy) target. Conclusions We conclude that coherent choice of reference land use for carbon or biodiversity footprints depends on the goal and scope of a study. Beyond methodological coherency, issues related to the reliability and availability of appropriate data are relevant and vary between reference land use choices. However, difficulties in the assessment should not justify incoherent choices. We recommend that uncertainties are not overlooked but incorporated in the assessment and considered in the interpretation of the results. In addition, we recommend that key methodological choices, including the definition of the purpose of a study, chosen temporal scope and applied reference land use, should be clearly and transparently presented.

Habitat quality assessment on the Qinghai-Tibet plateau across vegetation ecoregions using InVEST and Geodetector models

IntroductionThe Qinghai-Tibet Plateau holds a significant position in the global ecosystem, with its unique high altitude and complex geographical features fostering rich biodiversity. The plateau’s high-altitude environment and distinctive climate system significantly influence the Asian monsoon and regional hydrological cycles. Its vast glaciers and snow reserves are crucial in regulating the Asian climate. While previous studies have analyzed the habitat quality of the Qinghai-Tibet Plateau, significant variations exist across different vegetation ecoregions, warranting further investigation into these variations and their influencing factors.MethodsThis study conducted a comprehensive assessment of habitat quality on the Qinghai-Tibet Plateau by analyzing the impacts of human activities, climate change, and grazing intensity. Using the InVEST Model and Geodetector Model, we evaluated habitat quality across the plateau’s six vegetation ecoregions from 2000 to 2020. The efficacy of ecological red-line policies in actual conservation efforts was also examined.ResultsThe results indicate that habitat quality among vegetation ecoregions is shaped by a complex interaction of geographical and human-induced factors, leading to notable spatiotemporal variations. From 2000 to 2020, the quality of habitats was significantly impacted by human activities, climate change, grazing intensity, and land-use changes. These effects were especially prominent during the period from 2005 to 2010.DiscussionThe changes in habitat quality on the Qinghai-Tibet Plateau are influenced by multiple driving factors, with significant differences in the drivers across various vegetation ecoregions. The ecological redline policy has played an important role in protecting the ecological environment in key areas, particularly in regions with high human intervention, where its effectiveness is more pronounced. In future ecological management, it is essential to strengthen conservation measures based on regional specificity. By comprehensively considering the impact of human activities and natural factors, developing more targeted management strategies is crucial for improving habitat quality.

Attribution of Vegetation Dynamics in the Yellow River Water Conservation Area Based on the Deep ConvLSTM Model

Climate change and human activities have significantly impacted the long-term growth of vegetation, thereby altering the ecosystem’s response mechanisms. The Yellow River Water Conservation Area (YRWCA) is a critical ecological functional zone in China. Since 1982, the vegetation in the YRWCA has changed significantly, and the primary drivers of vegetation which changed before and after 2000 were identified as climate change and human activities, respectively. However, the extent to which different drivers contribute to the vegetation dynamics of the YRWCA remains uncertain. In this study, we introduced a modified deep Convolutional Long Short-Term Memory (ConvLSTM) model to quantify the contributions of climate change and human activities to vegetation change while considering the spatiotemporal heterogeneity. We identified areas with minimal human activity before 2000 using the residual trend method, and used the regional data from these areas to train the model. Subsequently, we applied the trained deep ConvLSTM model to perform an attribution analysis after 2000. The results show that the deep ConvLSTM effectively captures the impacts of climate change on vegetation growth and outperforms the widely used Random Forest model (RF). Despite the fact that the input data of RF were optimized, ConvLSTM still distinctly outperformed RF, achieving R2, MAE, and RMSE values of 0.99, 0.013, and 0.018, respectively, compared to RF’s corresponding values of 0.94, 0.038, and 0.045. Since 2000, the regional normalized difference vegetation index (NDVI) has shown a broad increasing trend, particularly in dryland, primarily induced by human activities from 2006 to 2015. Furthermore, an analysis of changes in regional land use, particularly in drylands, revealed that the highest magnitude of conversion of farmland back to forest or grass was recorded from 2000 to 2005. However, the most significant contributions from human activities occurred from 2006 to 2015, indicating a time lag in vegetation recovery from these ecological programs. The attribution results provide valuable insights for the implementation of ecological programs, and the introduced deep ConvLSTM proves the suitability of deep learning models that capture spatiotemporal features in vegetation growth simulations, allowing for broader applications.

Impacts of land use and land cover change on the landscape pattern and ecosystem services in the Poyang Lake Basin, China

ContextDecades of intensifying human activities have led to drastic changes in land use and land cover (LULC) in the Poyang Lake Basin (PLB), resulting in significant changes in landscape pattern and ecosystem service value (ESV), thereby affecting regional sustainability.ObjectivesWe focused on understanding the impact of LULC changes on the landscape pattern and ESV of the PLB and used the Patch-generating Land Use Simulation model (PLUS) to predict LULC changes in 2050.MethodsWe evaluated landscape patterns using landscape metrics and calculated ESV using the ecosystem service equivalent factor method. The Pearson correlation coefficient was used to analyze the correlation between landscape patterns and ESV from 1990 to 2020. Then, we combined the PLUS model and the ecosystem service equivalent factor method to calculate the ESV under multiple scenarios from 2020 to 2050.ResultsFrom 1990 to 2020, the LULC of the PLB changed to varying degrees. The PLB has undergone a rapid process of landscape fragmentation, and the total ESV of the PLB has decreased. The total ESV was positively correlated with the CONTAG index and negatively correlated with the SHDI index. Between 2020 and 2050, the ESV of the PLB is projected to decrease under the NDS (nature development scenario) and EDS (economic development scenario) and increase under the EPS (ecological protection scenario).ConclusionsESV responded to changes in landscape pattern. We recommend that the PLB should increase patch connectivity. Additionally, future development in the PLB should prioritize ecological protection to prevent further declines in ESV.

Comparison of various models for multi-scenario simulation of land use/land cover to predict ecosystem service value: A case study of Harbin-Changchun Urban Agglomeration, China

Understanding the intricate changes in land use and land cover (LULC) transformations, as well as accurately quantifying the ecosystem services value (ESV), holds paramount importance in achieving sustainable development goals. However, previous studies have notably neglected conducting empirical evaluations across various LULC prediction models under identical conditions within the same geographical region. Additionally, the majority of relevant studies primarily concentrate on local scales. In this study, we used CA-Markov, Future Land Use Simulation (FLUS) and Patch-generating Land Use Simulation (PLUS) models to simulate the dynamics of LULC, respectively. Subsequently, we successfully projected the future LULC patterns and corresponding ESV within the Harbin-Changchun Urban Agglomeration (HCUA), China. During the period spanning from 2000 to 2020, a persistent reduction of 2067 km2 in farmland was witnessed within the HCUA, while an accompanying expansion of 4081 km2 in built-up land occurred concurrently. The ESV in HCUA experienced a fluctuating trend. There was an initial decline of 7.443 × 109 yuan during the first decade, which was subsequently followed by an increase of 4.615 × 109 yuan during the latter decade. PLUS, FLUS, and CA-Markov models can all simulate the LULC of HCUA, but in decreasing order of accuracy and ease of use, with OA values of 0.8987, 0.8944 and 0.8651, and Kappa values of 0.8217, 0.8150 and 0.7860, respectively. The PLUS model was chosen to predict the future LULC. Then four development scenarios were set. Our optimization results indicate that it is advisable to restrict the area of built-up land within 17000 km2 in 2030. Moreover, under the economic and ecological balance (EEB) scenario, both ESV and economic benefits are projected to increase compared to the business as usual (BAU) scenario. This study offers valuable insights and serves as a significant reference for future research endeavors focused on optimizing land use.

Impacts of land use and abiotic factors on fruit, seed, and leaf morphology of the desert date Balanites aegyptiaca in Benin: Implications for management

Preserving intraspecific phenotypic variation within socio-economically important but declining species is fundamental in the current context of rapid change in land use and environmental conditions. Balanites aegyptiaca (L.) Delile is a valuable seed oil tree species native to the arid and semi-arid regions of Africa. Notable morphological variations within the species are recognized by local communities, who often select trees with preferred traits for preservation in croplands. This study compared phenotypic variation in B. aegyptiaca based on sixteen phenotypic traits of fruits, seeds, and leaflets between trees in a strictly protected area and those in croplands. Furthermore, the relative role of land use, soil characteristics, bioclimatic variables, elevation, and slope in the observed variation was analysed. Student t-test, principal component analysis, redundancy analysis, and variance partitioning were used for data analysis in R software. Results showed that, after accounting for tree variation, significant differences were observed in only two traits: seed ratio, and leaflet dry weight, with mean values in cropland being 1.470 (higher), and 0.943 (lower) times that of wild trees, respectively. Furthermore, principal component analysis showed great overlap between ellipses of cropland and wild trees. The variance partitioning analysis showed that bioclimatic variables explained 18 % of the total variation followed by soil characteristics (11 %), and land use (9 %). These findings collectively suggest weak impacts of croplands and a lack of domestication syndrome in B. aegyptiaca in Benin, potentially due to persisting gene flow between wild and cropland trees, inadvertent species management, or low intensity of selection pressures. Future studies should explore organoleptic properties, physico-chemical characteristics of the pulp and seed oil and discern the extent to which observed differences are attributable to genetic factors and biotic factors (pest attacks, plant-plant interactions, etc.).

Geographical distribution of caudatoside and ptaquiloside in bracken ferns in Northern Europe

Bracken ferns (genus Pteridium) are among the most prevalent plants worldwide, with their distribution expanding due to their invasive nature. The environmental implications of their proliferation in areas affected by human activity, natural disasters, or land-use changes are concerning, primarily because of the carcinogenic illudane glycosides they produce. These compounds cause domestic and wildlife animal poisoning, as well as contamination of dairy products and drinking water. Several illudane glycosides are known, but usually only ptaquiloside (PTA) is monitored. This study investigates the spatial and temporal variations in illudane glycosides PTA, caudatoside (CAU) and ptesculentoside (PTE) across two phenotypes of Pteridium aquilinum (vars. aquilinum and latiusculum) over a broad geographic range spanning Denmark, Sweden, and Finland, encompassing 66 locations. We analysed different parts of the fern fronds (the tips and the lowest pinnae) using LC–MS and statistically explored the influence of phenotype, frond part, geographic location, sunlight exposure, and the surrounding ecosystem on glycoside content. Our findings reveal that PTA accounts for approximately two-thirds of the total illudane glycoside content, followed by CAU at nearly one-third, and a minor contribution from PTE. Glycoside levels were not influenced by phenotypic varieties or the studied environmental factors, but were significantly affected by geographic location. Specifically, CAU levels increased progressively towards the northeast, while PTA concentrations were highest in Denmark and markedly decreased in northeastern countries by over threefold, presumably due to climatic gradient. It has been further supported by temporal analysis in selected PTA-dominant regions indicating a reduction in PTA towards the end of the growing season, aligning its levels with those of CAU. Our study highlights that CAU concentrations in bracken ferns may equal or surpass PTA, contesting the prevailing view that PTA is the only notable illudane glycoside in Bracken. To provide unbiased assessment of the potential risks posed by P. aquilinum in the region, environmental and toxicological research should include measurements of not only PTA, but also CAU and, if possible, PTE.

Effects of expansion of protected areas and habitat transformation on spatiotemporal variation in human-wildlife conflict.

Land-use changes and the expansion of protected areas (PAs) have fostered increased interactions between humans and wildlife, resulting in an escalation of human-wildlife conflict (HWC) globally. However, HWC spatiotemporal pattern variation and its associations with PAs and land-use change remain poorly understood. To address this knowledge gap, we mapped and analyzed HWCs from 1990 to 2022 across China. We comprehensively mapped the spatiotemporal dynamics of HWCs in ArcGIS with data sets stratified by county, year, and species; assessed the impact of PAs through propensity score matching; and analyzed the effects of habitat transformation with linear mixed models. As PA increased from 0 to 20,000km2, the likelihood of HWCs initially increased (50%) before declining (20%). Conversely, as the distance from a PA grew, the likelihood of HWC gradually decreased (0 beyond 65km). There was a temporal lag between the establishment of a PA and the occurrence of HWC. Habitat loss catalyzed HWCs, whereas decreased levels of habitat fragmentation sometimes initially caused a temporary increase in HWCs. In general, the distribution of PAs greatly affected HWC occurrence, and habitat loss and fragmentation were critical drivers of HWCs, both of which exhibited time-lagged effects. HWC has become more challenging to address as conservation initiatives have led to significant recovery of the habitats and populations of wild animals. Further measures to address the HWCs are needed to ensure the preservation of animal welfare while fostering the mutually beneficial coexistence of humans and animal species. Finally, our study provides an important starting point for informing future HWC research and conservation planning on a global scale.

Urban green spaces with high connectivity and complex vegetation promote occupancy and richness of birds in a tropical megacity

Urban growth often leads to land-use changes that result in biodiversity loss and reduced human benefits. In urban zones, green areas facilitate physicochemical processes (such as carbon capture, reducing environmental temperature and noise pollution), offer multiple benefits to human beings (e.g., water filtration and purification), and support numerous vertebrate populations, including birds. In the tropics, the capacity of green spaces to maintain bird populations is regulated by characteristics of these areas (e.g., vegetation structure) and environmental seasonality. In order to generate ecological knowledge to help conserve bird diversity in large urban settlements, this study aimed to (1) identify the most influential variables on the distribution of bird species in green areas of a tropical megacity, and (2) assess how bird richness varies between the dry and rainy seasons. Across two dry and rainy seasons between 2021 and 2022, detection records of 108 bird species were obtained from 101 green areas. Air temperature and sampling time were the primary factors influencing bird detection. Bird occupancy and richness were higher in parks near other green areas in first dry and increased with tree richness during the rainy seasons. Floral abundance explained the occupancy and richness in the second dry season. In 2021, the highest richness was observed during the dry season, while in 2022, the highest richness was estimated during the rainy season. These findings highlight the importance of resource availability and spatial arrangement in urban green areas for bird diversity, offering insights for conservation and maintaining ecosystem benefits in urban environments.

Grassland albedo as a nature-based climate prospect: the role of growth form and grazing

Abstract Nature-based solutions for mitigating climate change focus largely on land management to reduce carbon emissions and enhance carbon sequestration. Tree planting, commonly advocated for carbon offset, threatens grassland biodiversity and may induce positive radiative forcing (warming) by lowering albedo. Before making decisions about land-use changes in grasslands, an understanding of the fine-scale albedo of grassy versus woody vegetation is needed. Existing satellite-based albedo products offer global coverage with temporally fine, but spatially coarse, resolution, whereas fine-scale in situ grassland albedo data are sparse. We examined the hypotheses that albedo varies seasonally between grass type patches, between shrub and grass patches, and with grazing at the patch scale. Using a tripod-mounted albedometer, we quantified albedo of seven distinct grassland patches in South Africa’s eastern Karoo during early and late dormancy and growing seasons. Patches included intensely-grazed grazing lawn (Cynodon dactylon), grazed and less-grazed red tussock grass (Themeda triandra), grazed and less-grazed white tussock grass (Eragrostis lehmanniana), shrub (Pentzia incana) encroached grass, and bare ground. Season influenced albedo in all patches and, additionally, we found strong differences for the same period between years due to varying rainfall and temperature patterns. For grass-dominated patches, albedo differences were most pronounced during early dormancy, likely due to an effect of grass inflorescences. Albedo of intensely-grazed grazing lawns was consistently higher than other patches, except during early dormancy when white tussock grass albedo was equally high. We found no albedo difference between grazed and less-grazed tussock patches of either red or white grass. Shrub-encroached patches exhibited consistently lower albedo than other patches. Our findings underscore the nuanced relationship between grassland patches and albedo, with shrub encroachment, proposed afforestation, and certain grasses possibly increasing warming potential through reduced albedo. As climate initiatives extend into grasslands, understanding these patterns is essential for climate change mitigation and grassland conservation.

A Descriptive Analysis of Human-Environment Interactions in the Suburban Area of Pune City

The Baner-Balewadi was a rural area that transformed into a residential suburb and is now metamorphosing into a commercial and educational hub of Pune city. This area is now a part of Pune Municipal Corporation and is occupied by various schools, universities, and IT companies. The decadal population growth rate of the Baner-Balewadi area is 275%; it is much higher than the Pune district’s and city’s growth rate, which makes it a fascinating area for this study. A cross-sectional survey was conducted in this area covering three major regions: Balewadi Highstreet, Baner-Balewadi road, and NICMAR University. The data for 15 parameters were gathered, a total of 38 survey samples were collected using stratified random sampling, and land use was mapped to understand the grassroots reality. Thereafter, the parameters were analysed using a descriptive statistical technique, and spider mapping was used for data presentation. The strengths and challenges regarding infrastructural services, transportation, socio-economic factors, environment, and land use were identified. The results show that the waste collection is strong, but there are drinking water issues in the area. The recent development is causing stress on the infrastructural services and unregulated land-use change leading to environmental degradation. The metro construction is causing a lot of noise and air pollution, and people will still prefer buses as a transportation medium in the future because of good connectivity. The study is concluded with area-wise parametric recommendations made after examining the advancement, challenges, and gaps identified at the grassroots from both stakeholders’ and experts’ perspectives.

Can regionalization enhance the performance of land-use change models in rapidly urbanizing areas?

The performance of Land Use Change (LUC) models is influenced by the regional spatial characteristics that trigger the changes. However, the literature on LUC models generally reports validation results for entire regions without considering subregions that differ significantly in their LUC drivers. This research explores how the LUC driving forces differ among subregions and whether regionalization can improve the performance of LUC models in areas undergoing rapid urbanization. We analyzed the Geomod, Cellular Automata-Markov, and Land Change Modeler models across rural and urbanized subregions on the western edge of Mexico City. Regionalization significantly enhanced the overall accuracy of the models and the concordance of spatial patterns with the reference data in rural regions but was of limited benefit in urbanized regions. This shows the need to consider regionalized modeling to improve the performance of LUC models when there are noticeable differences in LUC drivers between subregions. These findings will enhance the usefulness of LUC models for urban planning and land management policies, promoting more precise and effective decision-making.

Perturbation of soil organic carbon induced by land-use change from primary forest

Abstract The impact of land-use change (LUC) on soil organic carbon (SOC) has been a wide concern of land management policymakers because CO2 emissions induced by LUC have been the second largest carbon source worldwide. However, due to insufficient data quality and limited biome coverage, a global big picture of the impact of LUC on SOC is still not clear. This study conducted a meta-analysis on 288 independent observations sourced from 62 peer-reviewed papers to provide a global summary of the change in SOC after the conversion of primary forests into other land-use types. The conversion of primary forest to cropland resulted in the most severe SOC loss (-33.2%), followed by conversion into plantation forests (-22.3%) and secondary forests (-19.1%). Nonetheless, SOC increased by 9.1% after a conversion from primary forests into pasture. More SOC loss was found at sites with lower precipitation for primary forests converted to cropland and plantation forests. The SOC loss decreased consistently with increasing mean annual temperature (MAT) for all four types of LUC. Moreover, the loss of SOC tended to worsen over time when primary forests are converted to cropland or plantation forests. In contrast, SOC loss recovered over time following conversion to secondary forests. The gain of SOC gradually increased over time after conversion to pastures. To conclude, the changes in SOC are related not only to the land-use type but also to precipitation, temperature and turn years after LUC. Due to limited data, this study focuses on soil profiles within 30 cm depth, and future research should explore SOC dynamics induced by LUC at greater depths. Overall, cases of SOC loss of approximately 30% following deforestation were very common (except for conversion to pasture). Thus we suggest that the loss of SOC following LUC should be carefully considered and monitored in land management.