Forest Cover Research Articles

Advancing climate resilience through a geo-design framework: strengthening urban and community forestry for sustainable environmental design

Urban and community forestry is a specialized discipline focused on the meticulous management of trees and forests within urban, suburban, and town environments. This field often entails extensive civic involvement and collaborative partnerships with institutions. Its overarching objectives span a spectrum from preserving water quality, habitat, and biodiversity to mitigating the Urban Heat Island (UHI) effect. The UHI phenomenon, characterized by notably higher temperatures in urban areas compared to rural counterparts due to heat absorption by urban infrastructure and limited urban forest coverage, serves as a focal point in this study. The study focuses on developing a methodological framework that integrates Geographically Weighted Regression (GWR), Random Forest (RF), and Suitability Analysis to assess the Urban Heat Island (UHI) effect across different urban zones, aiming to identify areas with varying levels of UHI impact. The framework is designed to assist urban planners and designers in understanding the spatial distribution of UHI and identifying areas where urban forestry initiatives can be strategically implemented to mitigate its effect. Conducted in various London areas, the research provides a comprehensive analysis of the intricate relationship between urban and community forestry and UHI. By mapping the spatial variability of UHI, the framework offers a novel approach to enhancing urban environmental design and advancing urban forestry studies. The study’s findings are expected to provide valuable insights for urban planners and policymakers, aiding in creating healthier and more livable urban environments through informed decision-making in urban forestry management.

Impact of land use/land cover change on surface water hydrology in Akaki river catchment, Awash basin, Ethiopia

Watershed reactions to environmental changes is critical for water resource use and management planning. The change in land use/land cover (LUCC) alters surface water hydrology and water balance, subsequently it affects the availability of water resources. This study examined Akaki River catchment surface hydrological responses to future land use scenarios. The future LULC simulated using Cellular Automata-Markov Chain (CA-Markov) model in IDRISI software for 2031, 2041, and 2051 under Business as Usual (BAU) and Forest Patch Protection (FPP) scenarios. Water yield (WY), sediment export (SE), and soil loss (SL) were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The findings indicate that under BAU, forest and settlement areas increased 42.64% and 31.47%, whereas water body, grass land, and agriculture dropped 31.99%, 25.72%, and 10.4%, respectively, from 2021 to 2051. The FPP scenario shows a 66.42% increase in forest coverage and a 31.97% decrease in cultivated land between 2021 and 2051. Overall settlement expansion will expand by 31.44%, while water body and grassland will decline by 11.12% and 24.9%. As a result of LULC changes in BAU scenario, the proportions of WY (4.36%), SE (26%), and SL (22.45%) increased. The hydrological components exhibited more gradual variations of 0.55%, 18.8%, and 14.24% for the WY, SE, and SL, respectively, under the FPP scenario. Therefore, the alteration has resulted in a concerning state within the area, necessitating the implementation of comprehensive management techniques to restore the hydrology of the catchment.

Mapping the wildland-urban interface at municipal level for wildfire exposure analysis in mainland Portugal

The Wildland-Urban Interface (WUI), where vegetation and built-up structures intermingle, encompasses a variety of territorial elements that interact spatially, being variable both in space and time. Mapping the WUI at finer scales is paramount to assess wildfire exposure and define tailored mitigation strategies. Our aim was to develop a semi-automated method to map the WUI at municipal level, leveraging recent advances in data and technology. We tested the procedure in four municipalities of mainland Portugal with different fire history, biophysical conditions, and sociodemographic contexts. We considered WUI as either intermix or interface. Our approach integrates both building location data and high-resolution vegetation maps, to calculate the density of buildings and forest cover proportion within different circular moving window sizes. Within each radius, we evaluated the total area and spatial distribution of the WUI types, as well as the number of buildings within WUI and within the fire perimeters recorded between the years 2000 and 2022 and analysed the differences between municipalities. We then compared the mapped WUI with previous WUI mappings for mainland Portugal, to identify common spots and potential spatial divergences. We found that the area mapped as WUI within all four municipalities ranged from about 400 km2 to 1135 km2 depending on the radius size. A distinct distribution for each type of WUI was observed as the radius size increased: the intermix WUI showed a tendency to increase, and the interface WUI increased only between the radius of 100 and 200 m, decreasing gradually in subsequent radii. Between 39.4% and 45.5% of the nearly 200,000 buildings in the study areas were within WUI, depending on radius size and a total of 5436 buildings were within the historic fire perimeter. Although the comparison with other maps showed fair agreement, due to differences in data and methodology, common areas mapped as WUI were found, which suggests that these areas should receive greater attention from decision-makers regarding fire management strategies, since their classification as WUI remains consistent across different methodologies.

Agricultural intensification in Lake Naivasha Catchment in Kenya and associated nutrients and pesticides pollution

Investments in agricultural intensification in sub-Saharan Africa aim to fulfill food and economic demands. However, the increased use of fertilizers and pesticides poses ecological risks to water bodies in agricultural catchments. This study focused on assessing the impact of agricultural intensification on nutrient and pesticide pollution in the L. Naivasha catchment in Kenya. The research revealed significant changes in the catchment’s agricultural landscape between 1989 and 2019, driven by intensified agricultural expansion. As a result, nutrient and pesticide emissions have worsened the lake’s trophic status, shifting it towards hypereutrophic conditions. The study found a weak relationship between total nitrogen (TN) and sum dichlorodiphenyltrichloroethane (∑DDT), indicating that an increase in TN slightly predicted a reduction in ∑DDT. Analysis also showed potential phosphorus (P) limitation in the lake. Additionally, the observed ratio between dichlorodiphenyldichloroethane and dichlorodiphenyldichloroethylene (DDD:DDE) and (DDE + DDD):DDT ratios suggest recent use of banned DDT in the catchment. The study concludes that the transformation of L. Naivasha landscape shows unsustainable agricultural expansion with reduced forest cover, increased croplands, and increased pesticide contamination. This reflects a common issue in sub-Saharan Africa, that sustainable catchment management must address, specifically for combined pollutants, to support water quality and achieve the SDGs in agriculture.

Landscape genetics of spruce grouse at the trailing edge of the boreal forest

Populations on the periphery of a species range generally occupy marginal or less continuous habitat and can have greater extinction risk than populations in the range‐center. For climate‐sensitive populations on the trailing edge of a species' distribution (i.e. low latitude or low elevation), the effects of climate change are expected to compound these threats, increasing the vulnerability of these populations. The spruce grouse Canachites canadensis is a boreal forest specialist that is expected to experience range contraction at the trailing edge of its range due to climate change. In this study, we investigated the genetic structure, genetic diversity, and connectivity of spruce grouse in Minnesota, along the southeastern range limit in the United States. Clustering algorithms and genetic diversity indices suggested a single continuous population occurred throughout northern Minnesota. We detected no signatures of recent inbreeding or population bottlenecks. We used maximum likelihood population effects modeling and identified coniferous forest land cover and lower average spring temperatures as predictors of gene flow. We used two approaches based on circuit theory to map the potential for gene flow and identified regions of consistently high gene flow in the northwest and northeast of the study area. Omniscape, which incorporated additional parameters representing the likely origins of dispersers and the maximum dispersal distance, suggested a more continuous gene flow landscape than did Circuitscape. Our work highlights the current genetic integrity of one of the largest populations of the eastern subspecies of spruce grouse C. c. canadensis in the United States, identifies key landscape attributes for functional connectivity, and demonstrates complementary approaches of Circuitscape and Omniscape for gene flow mapping.

Assessing GEDI data fusions to map woodpecker distributions and biodiversity hotspots

Abstract In forested systems, woodpecker species richness has been linked with songbird diversity, and identifying woodpecker biodiversity hotspots may contribute important information for conservation planning. The availability of global forest structure data via the Global Ecosystem Dynamics Investigation (GEDI) instrument provides a new tool for examining broad extent relationships amongst environmental variables, forest structure, and woodpecker diversity hotspots. Within the Marine West Coast Forest ecoregion, USA, we used eBird data for 7 woodpecker species to model encounter rates based on bioclimatic variables, process data (e.g. duration and timing of survey), MODIS forest land cover data, and GEDI-fusion metrics. The GEDI-fusion metrics included foliage height diversity (fhd), rh98 (a representation of canopy height), and canopy cover, which were created by combining GEDI data with Landsat, Sentinel-1, topographic, and climatic information within a random forest modeling framework. AUCs for the species-specific models ranged from 0.77–0.98, where bioclimatic and process predictors were amongst the most important variables for all species. GEDI-fusion forest structure metrics were highly ranked for all species, with fhd included as a highly ranked predictor for all species. The structural metrics included as top predictors for each species were reflective of known species-specific habitat associations. Hotspots in this ecoregion tended to be inland and occurred most often on privately-owned lands. Identification of hotspots is the first step towards management plans focused on biodiversity, and understanding ownership patterns is important for future conservation efforts. The near-global extent of GEDI data, along with recent studies that recommend woodpeckers as indicators of biodiversity across multiple forest types at local and global scales, suggest that synthesis of GEDI-derived data applied to woodpecker detection information might be a powerful approach to identifying biodiversity hotspots.

Environmental Dynamics in The Sumatran Coffee Landscapes: Opportunities and Challenges Through Spatial Perspectives

The coffee industry in Indonesia, particularly in the Sumatran landscape, emerges as a vital contributor to the nation's economy, impacting regional growth. Nevertheless, this landscape faces ecological threats from rapid deforestation, resulting in a substantial loss of primary forest cover. This historical deforestation along with climate crisis presents challenges for coffee plantations. The study employs geospatial analysis to comprehensively outline challenges and opportunities for smallholder coffee farmers in Sumatra, particularly in the Arabica (Central Aceh) and Robusta (Tanggamus) landscapes. The study shows non-shade coffee plantations covered approximately 23,453 ha in Central Aceh and 43,991 ha in Tanggamus. Additionally, mixed agroforestry areas were prevalent, comprising about 132,569 ha in Tanggamus and 19,450 ha in Central Aceh. Tanggamus and Central Aceh have become favorable areas for Robusta coffee and Arabica coffee, respectively. One significant opportunity identified for coffee development in Central Aceh is that 86% of existing coffee farms already adhere to EUDR. Furthermore, 94% of existing coffee farms in Tanggamus meet EUDR standards, opening doors for more farmers to access the European market.

Climate and Land Use Changes Impact the Future of European Amphibian Functional Diversity

Climate and land use changes drive shifts in species distributions, causing variations in species richness. Yet the influence of shifts in species distributions on functional diversity at broad spatial scales remains uncertain. Here, we explored the potential effect of climate and land use changes on the functional diversity of European amphibian assemblages from the present to 2050, along with their effect on species richness. We performed species distribution modelling using a scenario of climate and land use change to estimate current and future potential distributions of 73 species. We estimated functional diversity using morphological and ecological functional traits. Our results highlight the intricate effects of climate and land use changes on taxonomic and functional diversity of amphibians. A climate-induced northward expansion of amphibians is anticipated, with temperature, precipitation, and forest cover prominently shaping future assemblages. Species expected to have shrinking ranges (n = 35) tend to mature sexually at a later age, produce fewer offspring per reproductive event, and live at higher maximum altitudes compared to species expected to expand (n = 38). Furthermore, trait composition changes are expected to exceed predictions based solely on species richness. These changes will vary geographically, with northern regions likely experiencing substantial increases in functional richness and functional redundancy, i.e., the coexistence of species with similar functional roles. Our findings underscore that functional diversity changes might serve as an early warning signal to assess human impacts on biodiversity.

Long-Term Landscape Changes in the Ojców National Park (Poland) and Its Surroundings: Implications for the Effectiveness of Buffer Zones

Protected areas (PAs) serve as crucial elements in biodiversity conservation but are in danger of becoming isolated islands in human-dominated landscapes. It is related to landscape changes, especially changes in land use and land cover (LULC). Over the past decades, most research on the effectiveness of nature conservation has focused mainly on PAs, while the areas surrounding PAs are of key importance for maintaining ecological connectivity and biodiversity. Therefore, the main objective of this study was to determine the long-term changes in LULC within the selected national park in Poland and its surroundings and to assess the effectiveness of the BZ based on these changes. We hypothesized that, despite restrictions within the buffer zone, land development has intensified and increased, in the nearest surroundings of the analyzed national park. For the analysis, we selected Ojców National Park (southern Poland), one of the oldest national parks in Poland. We analyzed landscape changes before (since the 1930s) and after establishing the park and its BZ. We conducted a comprehensive quantitative analysis of the landscape structure and LULC. We used historical maps and the contemporary national LULC database. Our results showed that almost 40% of the study area consisted of lands with non-persistent LULC. The main changes include a three-fold increase in built-up areas and an increase in forest cover, mainly on abandoned agricultural land. We also found that land development around the national park is at a level similar to the general rate for the area outside the BZ. It suggests the ineffectiveness of the buffer zone in preventing land development. The identified long-term landscape changes the basis for sustainable development land management from the nature conservation perspective.

Fire is associated with forest degradation and economic land concessions, but not land conversion in the rapidly transforming Cambodian landscape

Abstract Cambodia is beset by high deforestation rates and fire frequencies. From 2001–2020, forest cover declined by 34%, and cropland and rubber expanded by 31,401 km2 and 4,530 km2, respectively; meanwhile nearly 8.7 million fires burned 41.6% of the land. Fires may be associated with deliberate land change, stable land management systems, and unplanned forest degradation. We integrated annual land cover and monthly burned area data from 2001–2020 to test three hypotheses. First, if fire is used during land conversion, there would be a detectable pulse in fire activity in the year immediately prior to, and the year of land cover change. Our temporal analysis found statistically elevated burn rates in five of 16 transition tests, however, they were typically <1% outside the predicted range, indicating no practical significance in the association of fire with land cover change. Second, fire prevalence would be lower in land managed for conservation or agricultural production than unclassified or unmanaged land. persistent forest and shrubland burned at significantly higher rates than expected, cropland burned significantly less, burning was almost absent from rubber plantations, and forests in protected areas (PAs) exhibited lower total burn percentages than unclassified land or industrial economic land concessions (ELCs), thus supporting the fire-land management hypothesis. However, total burned area in ELCs was greater than unclassified land for several persistent land cover classes, suggesting that local landowners may prevent fire in commercially valuable private agricultural land, but there may be no such prevention measures in industrial ELCs. Anti-fire policy enforcement in ELCs should be enhanced. Third, forests that converted into (degraded) shrublands would experience increasing fire frequency in the years leading up to transition, a hypothesis we found strong support for through our temporal analysis. Cambodia’s 2013 Law on Fire Prevention and Fire Fighting deputizes the public to enforce its provision, however given that the vast majority of fires occur in persistent forest in state-owned land, collective action problems are likely to hinder its effective implementation.

Coupling Coordination of Multi-Dimensional Urbanization and Ecological Security in Karst Landscapes: A Case Study of the Yunnan–Guizhou Region, China

Globally, karst regions face the dual challenges of urbanization and ecological protection, with the coupling coordination of multi-dimensional urbanization (MDU) and ecological security (ECS) being a necessary condition for achieving sustainable development. This study, based on statistical data on MDU and ECS in the Yunnan–Guizhou Region (the YGR) in China, employs the entropy weight TOPSIS model, degree of coupling coordination (CCD) model, and panel Tobit regression model to explore the coupling relationship between MDU and ECS. The main conclusions are as follows. (1) MDU in the YGR increased from 0.299 to 0.305, indicating low-level and sluggish development. Spatially, it is characterized by a “dual-core” structure centered on Kunming and Guiyang. (2) ECS decreased from 0.456 to 0.423, with a spatial pattern of “high in the east, low in the west”. The impact of human activities on ECS increased from 0.579 to 0.631 due to the increase in social and economic activities. (3) CCD increased to 0.579, achieving moderate coordination. The spatial feature evolved into a tri-cluster pattern of “high–low–high” across the “eastern–central–northwestern” regions. (4) Regression results indicate that annual average precipitation has a “both promoting and limiting” dual effect on CCD. The coefficient for the proportion of afforested land area is 0.205, with a significance level of 5%, suggesting that increasing forest cover is a key measure for improving CCD. The study reveals the factors influencing the evolution of MDU and ECS from a negative to a positive correlation, providing a basis for decisions related to sustainable development for urban and ecological management in karst landscapes globally.

Can Ecological Protection Affect High-Quality Forestry Development?—A Case Study of China

As the global ecological environment faces serious challenges, ecological protection has attracted global attention. As a basic industry of the national economy, China’s total forestry output value is 8.04 trillion RMB in 2022. This study aims to assess the impact of ecological protection on high-quality forestry development and find its mechanism by using provincial panel data from 2010 to 2021 in China. The variables of environmental regulation and urbanization level were introduced. The benchmark regression model, mediation effect model and threshold effect model were employed for empirical analysis. The results show that: (1) The estimated ecological protection coefficient is 0.146. The ecological protection level significantly promotes high-quality forestry development; (2) The effect is more significant in the western region and the area with higher forest coverage. The estimated coefficients are 1.392 and 0.745. It is less affected by the marginal effect of the ecological protection level in the east; (3) The estimated environmental regulation coefficient is −0.021. Ecological protection promotes high-quality forestry development by reducing environmental regulations; (4) The impact increases with the level of urbanization. The p-value of the double threshold is 0.073. Therefore, policy recommendations are proposed to strengthen ecological protection and promote high-quality forestry development.

Forest cover lessens hurricane impacts on peak streamflow

AbstractCyclonic storms (i.e., hurricanes) are powerful disturbance events that often cause widespread forest damage. Storm‐related canopy damage reduces rainfall interception and evapotranspiration, but impacts on streamflow regimes are poorly understood. We quantify streamflow changes in Puerto Rico following Hurricane Maria in September 2017, and evaluate whether forest cover and storm‐related canopy damage account for the differences. Streams are particularly vulnerable to flooding in early post‐disturbance stages during hurricane season, so we focus on 3 months (Oct–Dec) following the hurricane. To discern changes in rainfall responses, we partitioned streamflow into baseflow and quickflow using a digital filter. We collected 2010–2017 streamflow and rainfall data from 18 watersheds and compared the relative magnitude of post‐ to pre‐hurricane double mass curve slopes of baseflow and quickflow volumes against rainfall. Several watersheds displayed higher post‐hurricane quickflow and baseflow, however, the response was variable. The magnitude of quickflow increase was greater in watersheds with high forest damage. Under the same level of relative damage, watersheds with low initial forest cover had greater quickflow increases than highly forested ones. Conversely, baseflow generally increased, but increases were greater in highly forested watersheds and smaller in highly damaged watersheds. These results suggest that post‐storm baseflow increases were due to recharge of hurricane‐related rainfall, as well as forest transpiration interruption and soil disturbance enhancing recharge of post‐hurricane rainfall, while increases to quickflow are related to loss of canopy rainfall interception and higher soil saturation decreasing infiltration. Our research demonstrates that forest damage from disturbance lowers quickflow and elevates baseflow in highly forested watersheds, and elevates quickflow and lowers baseflow in less‐forested watersheds. Less‐forested watersheds may be closer to the forest cover loss threshold needed to elicit a streamflow response following disturbance, suggesting higher flooding potential downstream, and a lower storm‐related forest disturbance threshold than in heavily forested watersheds.

A global annual fractional tree cover dataset during 2000–2021 generated from realigned MODIS seasonal data

Fractional tree cover facilitates the depiction of forest density and its changes. However, it remains challenging to estimate tree cover from satellite data, leading to substantial uncertainties in forest cover changes analysis. This paper generated a global annual fractional tree cover dataset from 2000 to 2021 with 250 m resolution (GLOBMAP FTC). MODIS annual observations were realigned at the pixel level to a common phenology and used to extract twelve features that can differentiate between trees and herbaceous vegetation, which greatly reduced feature dimensionality. A massive training data, consisting of 465.88 million sample points from four high-resolution global forest cover products, was collected to train a feedforward neural network model to predict tree cover. Compared with the validation datasets derived from the USGS circa 2010 global land cover reference dataset, the R2 value, MAE, and RMSE were 0.73, 10.55%, and 17.98%, respectively. This dataset can be applied for assessment of forest cover changes, including both abrupt forest loss and gradual forest gain.

Impact of land use and land cover change on land surface temperature: Comparative studies in four cities in southwestern Ethiopia

The urban climate has undergone significant changes due to rapid population growth, leading to a decline in vegetation cover and an increase in land surface temperature (LST). This study aims to assess the influence of land use land cover (LULC) changes on LST in four major urban areas in southwestern Ethiopia, namely Jimma, Bonga, Mattu and Nekemte, during the period from 2002 to 2024. To investigate the impact of LULC dynamics on LST, 30 m spatial resolution images from Landsat were utilized, including Thematic Mapper (TM) for the year 2002 and Landsat Operational Land Imager (OLI) and Thermal Infrared (TIRS) for the years 2014 and 2024. Over the past 22 years, the mean LST has increased by 2.81 °C, 2.94 °C, 3.37 °C, and 3.96 °C for Bonga, Nekemte, Mattu, and Jimma, respectively. The increase in LST can be attributed to various factors, but one of the primary reasons is linked to the rapid urbanization and decrease in forest cover. Changes in LULC triggered by rapid urbanization significantly influences LST in major cities. The results highlight the increment of impervious surface and the decline in vegetation cover as key factors contributing to the upward trend in LST. The results indicate that urban centers with less vegetation cover experienced higher LST compared to their surroundings. The results of this study indicate the necessity of effective urban planning to increase vegetation cover through urban greenery and parks to mitigate the increasing trends of LST, which can improve urban thermal comfort levels.

Impact of urban-rural development and its industrial elements on regional economic growth: An analysis based on provincial panel data in China

Urban-rural development is an important driving force for regional economic growth. The existing researches have studied this issue from various perspectives, but they ignore the impact of big data on the economy. In the post pandemic era, big data, as an emerging production factor, has a significant indicative effect in promoting urban-rural economic recovery and fostering new business forms. Therefore, fully considering the factor of big data can help reveal its impact mechanism on urban-rural economic growth in the post-epidemic period. Based on the data of 30 provinces and cities in China, this paper introduced big data on the basis of traditional models and constructed a multi-dimensional factor indicator system. At the same time, the panel regression model was established by using unit root test, Hausman test and precision test. Through benchmark regression and heterogeneity analysis, the impact of urban-rural development factors on economic growth was discussed. The results showed that the panel model passed all tests, and its regression error was stable below 5 %. Transportation, technology, and the three major industries can all promote positive economic growth, with a significance of 1 %. The three industries' contribution to economic growth ranks the third, second and first industries in order. In addition, the good ecological environment contributes to the benign economic growth during the study period. A 1 % increase in forest cover would drive economic growth by 0.215 %. But the impact of public's attention on the overall economy was an indirect effect manifested through its physical industries.The regional heterogeneity indicated that each element had different effects on economic development in eastern, central and western regions. Based on its results, this paper proposed suggestions for each region. In addition, this study found that the Internet attention reflected by big data did not directly drive economic growth, but affected economic growth through indirect channels such as information flow and resource allocation of real industries. This study provided data support for the existing theoretical review, and provided policy reference for the rational planning and industrial layout of China's regional economy.

Classification of forest cover of Ta Dung National Park, Vietnam using optical satellite images

Abstract The objective of this study was to classify the forest status of Ta Dung National Park, Vietnam using integrated satellite imagery and a machine learning algorithm to support biodiversity conservation and forest management. The complexity of land use poses a challenge to producing accurate land cover/land use maps using satellite imagery, particularly in tropical countries where farming often occurs in small, fragmented regions. This challenge is compounded when attempting to assess the natural forest status in tropical forests, which are inherently complex and have often experienced varying degrees of disturbance. Consequently, there is a need for approaches that enhance image classification accuracy while still allowing for the categorization of forest characteristics into reasonably homogeneous groups. In this study, we combined optical satellite images to classify the area of Ta Dung National Park, Vietnam into nine categories representing different forest statuses. Our results showed that integrating Sentinel-2 and Landsat 9 imagery using the random forest algorithm achieved a high classification accuracy of 84.75% with an overall accuracy and a kappa coefficient of 0.83. This approach can be applied to other areas facing similar challenges in classifying forest status.

Geospatial AI solution to monitor and mitigate increasing adverse ecological and hydrological impacts of climate change in Uttarakhand Himalaya (India).

Though climate change and its adverse ecological and geohydrological impacts are being experienced across the world in all types of ecosystems but as far as the Himalaya mountain ecosystem is concerned, the rate of climate change and subsequent impacts have reached an alarming stage due to anthropogenic and technogenic intervention on natural process and now need most effective and less time taking management strategy. Addressing this burning environmental problem, a geospatial artificial intelligence (GeoAI) technique-based case study is presented here from one of the most densely populated and urbanized regions of Himalaya mountain, viz Uttarakhand Himalaya, which is also called central Himalaya. The results of the study suggest that due to quite a high rate of climate change, the climatic zones shifting towards higher altitudes at the average rate of 5.6 2m/year, causing several adverse ecological impacts in terms of decreasing quality dense temperate forest cover (0.05%/year), snow cover (0.02%/year), water bodies (0.01%/year), agricultural land (0.31%/year), and horticultural land (0.01%/year). Conversion of these eco-friendly land use land cover into barren land, fallow land, and built-up land causes geohydrological consequences of climate change in terms of decreasing rainy days (1%/year), drying perennial springs (0.20%/year), perennial streams (0.11%/year), decreasing spring and stream discharge during non-monsoon season, increased extreme rainfall events (6-8%/year), and subsequent surface runoff during monsoon season. Further, the study advocates that the degraded geohydrological process has resulted in an increased frequency of disaster events (floods, cloudbursts, landslides. etc.) with a 3% (12 events) annual rate, causing great loss of environment, infrastructure, lives, and economy each year. Therefore, it has been very urgent to mitigate climate change and increase geohydrological disaster events through an integrated approach. Keep in view this, the present study proposed an integrated watershed management plan which is equally useful to be implemented across the Himalaya region and other similar ecosystems across the world.

Loss of species and functions in a deforested megadiverse tropical forest.

Tropical species richness is threatened by habitat degradation associated with land-use conversion, yet the consequences for functional diversity remain little understood. Progress has been hindered by difficulties in obtaining comprehensive species-level trait information to characterize entire assemblages and insufficient appreciation that increasing land-cover heterogeneity potentially compensates for species loss. We examined the impacts of tropical deforestation associated with land-use heterogeneity on bird species richness, functional redundancy, functional diversity, and associated components (i.e., alpha diversity, species dissimilarity, and interaction strength of the relationship between abundance and functional dissimilarity). We analyzed over 200 georeferenced bird assemblages in the Atlantic Forest of Brazil. We characterized the functional role of the species of each assemblage and modeled biodiversity metrics as a function of forest cover and land-cover heterogeneity. Replacement of native Atlantic Forest with a mosaic of land uses (e.g., agriculture, pastures, and urbanization) reduced bird species richness in a nonrandom way. Core forest species, or species considered sensitive to edges, tended to be absent in communities in heterogenous environments. Overall, functional diversity and functional redundancy of bird species were not affected by forest loss. However, birds in highly heterogenous habitats were functionally distinct from birds in forest, suggesting a shift in community composition toward mosaic-exclusive species led by land-cover heterogeneity. Threatened species of the Atlantic Forest did not seem to tolerate degraded and heterogeneous environments; they remained primarily in areas with large forest tracts. Our results shed light on the complex effects of native forest transformation to mosaics of anthropogenic landscapes and emphasize the importance of considering the effects of deforestation and land-use heterogeneity when assessing deforestation effects on Neotropical biodiversity.

Not population density, but city size and per capita income influence the urban forest carbon sequestration: A case of growing cities in Arkansas, USA

While urban trees provides significant ecosystem services, the impact of increasing urbanization and population on their carbon sequestration potential remains relatively underexplored in interior sprawling cities, highlighting a critical research gap amid growing urban environmental challenges. Although existing studies suggest a strongly correlation between urban forest cover and carbon sequestration, this study aims to investigate how the urban demography factors influence land cover and carbon sequestration across cities with low, medium, and high population densities. Using the i-Tree Canopy tool, we sampled 18,814 random points to estimate city land cover and carbon sequestration in Arkansas, interior state of the US. Results from the principal component analysis revealed that 74% of the variation in a city's land cover among population density classes is attributed to tree and soil cover percentages. The mean annual (1.40 ± 0.08 T ha-1) and total carbon sequestration rates (35.30 ± 5.57 T ha-1) were significantly higher in the areas with low population density due to a higher average tree cover percentage (46%). Carbon sequestration rate was negatively associated with land cover types such as impervious surfaces like buildings (r = -0.44), roads (r = -0.28), grass cover (r = -0.46), and impervious other (r = -0.53). The log-linear model with scaled variables suggested that factors such as city's size and tree cover has positive influence urban trees' annual and total carbon sequestration, while spatial distribution and per capita income negatively affect these ecosystem befits in growing cities, regardless of population density. Travel time within city may have negative impact, while decadal population change may positively impact on carbon sequestration alongside management effort. Valuing this potential urban forest carbon sequestration for emerging carbon market could provide monetary benefits to the urban communities, city managers, and policymakers, enabling the development of effective urban forest management strategies in the context of urban climate change.