The impact of land cover change on the carbon stock of moist afromontane forests in the Majang Forest Biosphere Reserve

BACKGORUND

Forest plays an important role in the global carbon cycle by sequestering carbon dioxide and thereby mitigating climate change. In this study, an attempt was made to investigate the effects of land use/land cover (LULC) change (1989-2017) on carbon stock and its economic values in tropical moist Afromontane forests of the Majang Forest Biosphere Reserve (MFBR), south-west Ethiopia. Systematic sampling was conducted to collect biomass and soil data from 140 plots in MFBR. The soil data were collected from grassland and farmland. InVEST modelling was employed to investigate the spatial and temporal distribution of carbon stocks. Global Voluntary Market Price (GVMP) and Tropical Economics of Ecosystems and Biodiversity (TEEB) analysis was performed to estimate economic values (EV) of carbon stock dynamics. Correlation and regression analyses were also employed to identify the relationship between environmental and anthropogenic impacts on carbon stocks.

RESULTS

The results indicated that the above-ground carbon and soil organic carbon stocks were higher than the other remaining carbon pools in MFBR. The mean carbon stock (32.59 M tonne) in 2017 was lower than in 1989 (34.76 Mt) of MFBR. Similarly, the EV of carbon stock in 2017 was lower than in 1989. Elevation, slope, and harvesting index are important environmental and disturbance factors resulting in major differences in carbon stock among study sites in MFBR.

CONCLUSIONS

Therefore, the gradual reduction of carbon stocks in connection with LULC change calls for urgent attention to implement successful conservation and sustainable use of forest resources in biosphere reserves.

Spatial-temporal evolution of production-living-ecological space and layout optimization strategy in eco-sensitive areas: a case study of typical area on the Qinghai-Tibetan Plateau, China

To achieve sustainable development goals and to solve environmental problems, land resources in eco-sensitive areas should be used and optimized. Qinghai, which is an important eco-sensitive area in China, represents a typical ecological vulnerable region on the Qinghai-Tibetan Plateau. Using land use/cover data for 2000, 2010 and 2020, this study applied a series of quantitative methods to analyze the spatial pattern and structure of the production-living-ecological space (PLES) in Qinghai. The results indicated that the spatial pattern of the PLES in Qinghai was stable over time, but the spatial distribution was very different. The structure of the PLES in Qinghai was stable, and the proportion of each space from high to low was ecological (81.01%), production (18.13%) and living (0.86%). We found that the proportion of ecological space in both the Qilian Mountains and the Three River Headwaters Region was lower than the rest of the study area, except for the Yellow River-Huangshui River Valley. Our study objectively and credibly presented the characteristics of the PLES in an important eco-sensitive area in China. This study further formulated targeted policy suggestions to provide a basis for regional sustainable development, ecological environment protection, and land and space optimization in Qinghai.

Multi-temporal assessment of land surface temperatures as an indicator of land use/cover changes and climate variability in the Develi Basin, Turkey

Land surface temperature (LST) is an important parameter that reflects land surface processes of water and energy balance and has been used in assessment of land use/cover changes. However, the use of LST in monitoring changes in non-urban areas such as agricultural areas and wetlands is still limited. In this study, we aim to determine the spatial and temporal changes in LST in a semi-arid agricultural basin in Turkey (Develi Basin), where land use/cover and climatic conditions showed considerable variability since 1980s. Irrigated agriculture have expanded in the basin since 1987, after the construction of a large irrigation project. The basin hosts an internationally important wetland, called the Sultan Marshes, affected negatively by irrigation expansion. The study covers a 39-year period from 1984 to 2022. Four Landsat Thematic Mapper (TM) images acquired in 1984, 1987, 2003, and 2007 and two Landsat 8 OLI/TIRS images acquired in 2014 and 2022 were used in the analyses. The land use/cover changes were evaluated based on Normalized Difference Vegetation Index (NDVI). LST was estimated through top-of-atmosphere brightness temperature from thermal bands of Landsat images. Climate variability from 2014 to 2022 was analyzed with statistical methods. The results indicated that Develi Basin faced both spatial and temporal land use/cover changes. The area covered with natural steppe vegetation and water bodies decreased in the basin. In contrast, the sparsely and densely vegetated soil covers, which mostly denote agricultural areas, increased. Changes in LST values were observed from 1984 to 2022 as a result of climatic factors and land use/cover changes. LST changes were variable across different land use/cover types; LST decreased in irrigated areas and increased in lakes that went dry over years. LST changes proved useful for evaluating land use/cover changes and climatic variations in agricultural basins.

Assessment of seasonal and spatial water quality variation in a cascading lake system in Chennai, India

Water quality and scarcity are among the most severe problems humans have been facing in the last decades. India, as a fast-developing country, is not an exception. The surface water quality has deteriorated due to anthropogenic activities. Another factor which impacts the water quality is the heavy rainfall during monsoon season. To maintain the quality and the sustainability of water resources, there is the need to study how human activities impact water quality. We hypothesized that the water quality can be impacted by the spatial land use types and by the seasonality. In the present study, seasonal and spatial water quality regarding physical, chemical, and biological parameters from a lake cascading system was assessed monthly from July to December 2019. Land use/cover data was produced by Impact Observatory, Microsoft, and Esri based on the 10-m Sentinel-2 images. Redundancy analysis was applied to investigate the relationship between land use/cover data and water quality in the riparian of 500 and 1000 m to the lakes. Our results showed clear temporal and spatial variation of water quality in 2019, with better water quality in rainy season (Oct.-Dec.) and downstream lakes while relatively worse water quality was recorded in dry season (Jul.-Sep.) and upstream lakes. The water quality variation was explained 27.8 % and 42.7 % by the land use types within 500 m and 1000 m buffer widths, respectively. The outlet of the catchment showed exceptional results due to the impact of a dumpsite. Our findings indicate that the water quality is highly impacted by human-induced land use/cover. The land use/cover types, such as crops, woodland and urban area, show negative impacts and relate to the high level of nutrient concentrations. In opposite, grass land shows positive effects and leads to better water quality. Our study confirms that the lake water quality is distinguished in both spatial and seasonal aspects. Monsoon season improves the water quality.

Exploring the spatiotemporal changes in carbon storage under different development scenarios in Jiangsu Province, China

Carbon storage (CS) is closely linked to the global challenge of climate change. Land use/cover (LULC) change is the main factor driving changes in CS, and evaluating the impact of LULC changes on CS is important for carbon balance. Taking Jiangsu Province as an example, we used the Integrated Valuation of Ecosystem Services and Trade-offs model to analyze the spatiotemporal changes in CS during 2000-2015. Then we coupled it with the patch-generating land use simulation model to simulate and predict LULC and CS in 2050 under four different development plans. The results showed that LULC change in Jiangsu Province was manifested mainly as transformation of cropland to construction land (3,485 km²) and cropland to water body (470 km²). The high value area for CS was concentrated mainly in forest land, water body and grassland, whereas the low value area was concentrated mainly in construction land. During 2000-2015, CS decreased by 0.23 Tg, and during 2015-2050, CS was predicted to decrease by 0.16, 1.69, 0.02, and 0.10 Tg under the baseline, fast, slow and harmonious development scenarios. The conversion of a large amount of cropland to construction land was the main cause of CS loss. In all scenarios, the carbon loss was the largest in southern Jiangsu and lowest in central Jiangsu. It is necessary to balance the conflict between economic development and ecological protection during the process of urbanization. This study can provide an important reference for decision makers during the formulation of regional development models and ecological management strategies.

Trade-off among grain production, animal husbandry production, and habitat quality based on future scenario simulations in Xilinhot

The balance and optimization of ecosystem services (ESs) are the basis of spatial planning and ecological landscape design. Selecting suitable ESs and developing integrated, quantitative, and spatially explicit assessment models is the key to balance research. In Xilinhot in eastern Inner Mongolia, China, grain production, animal husbandry production, and habitat quality are key ESs that affect the livelihoods of local farmers and herders and the regional ecological balance. Based on GlobeLand30 data for 2000-2020, we designed six future land scenarios for the region and used the future land use simulation (FLUS) model to simulate the land use/cover scenarios in 2030. Then, we analyzed staple grain production (SGP), sustainable stocking capacity (SSC), and habitat quality (HQ) under each scenario, and constructed a multi-ES comprehensive trade-off method, using the comprehensive trade-off score (CTS) to measure their overall development quality. The results show the following. (1) Under various scenarios, the SGP is negatively correlated with SSC and HQ, and the SSC is positively correlated with HQ. (2) In the inertial development scenario, the economic development priority scenario, and the quality habitat protection scenario, the SGP will increase, the SSC and HQ will decrease; among these scenarios, the economic development priority scenario is the most significant; their CTSs are 0.97, 0.95, and 0.98, respectively. In the ecological comprehensive governance scenario, the SSC will increase, SGP and HQ will decrease, and CTS is 0.98. (3) Based on the comprehensive trade-off analysis, the economic and ecological coordination scenario is the most beneficial for regional sustainable development. It achieves the stability of the SGP; although the SSC decreases slightly, the negative impact can be offset by a larger improvement in HQ. This paper provides clear policy suggestions for regional development, and the methodological framework we have constructed provides a reference for the study of complex land scenario simulations and multi-ecosystem service comprehensive trade-offs.

Expressing carbon storage in economic terms: The case of the upper Omo Gibe Basin in Ethiopia

Terrestrial carbon storage is important for planning decisions regarding climate change. Therefore, modelling the spatial distribution of carbon storage and valuation can help restore the sustainability of the ecosystems. This study aimed at showing the spatial and temporal variations in carbon storage and valuation in the upper Omo Gibe Basin. Land use/cover and carbon pool data based on field data collection and laboratory analyses supported by GIS and remote sensing were used. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software was used for modelling carbon storage. The Global voluntary carbon market price and Tropical Economics of Ecosystems and Biodiversity (TEEB) data were used for describing carbon storage in economic terms. ANOVA was carried out to detect significant differences in carbon stock correlation with parameters. The results show that the annual carbon stock declined by 0.37 t/ha and the carbon market declined from USD 25.04 billion in 1988 to USD 24.01 billion in 2018. The highest loss of carbon storage and valuation was found in forest land followed by grazing land. Moreover, carbon stock was positively correlated with NDVI and habitat quality (p < 0.05). Slopes did not affect carbon stock (p > 0.05). This study helps promote and enhance carbon trading.

An analytical approach for assessment of geographical variation in ecosystem service intensity in Punjab, Pakistan

Ecosystem services (ESs) are a diverse range of environmental properties that have significant effects on both landscape characteristics and human well-being, an understanding of the spatial variation of which is required for effective ecosystem management and conservation. In this study, we aimed to identify the geographical variation in ESs and examine the factors impacting ESs in Punjab Province, Pakistan. We evaluated ecosystem service intensity (ESI) by using the benefit transfer method and investigated the spatial heterogeneity of ESIs at the tehsil level by using an exploratory spatial data analysis (ESDA) model and semivariance analysis. This analysis indicated that spatial distribution of ESI shows significant and optimal spatial heterogeneity of ESs, revealing several hot and cold spots for ESI transformation in the study area. The ESI decreased from east to west and north to south, with a trough in the metropolitan zones, including Lahore, Sheikhupura, Faisalabad, and Multan, which was in accordance with the land use/cover pattern. Furthermore, using geographically weighted regression (GWR) analysis, we also identified geographical clusters within which land use/cover pressure and population growth were significantly positively associated with ESI across the province, based on a lag distance scale. The findings of this study have functional economic implications with respect to highlighting areas worthy of conservation and designing ecological corridors to enhance the delivery of ESs for regional benefits.

Haiti has more forest than previously reported: land change 2000-2015

Estimates of forest cover have important political, conservation, and funding implications, but methods vary greatly. Haiti has often been cited as one of the most deforested countries in the world, yet estimates of forest cover range from <1% to 33%. Here, we analyze land change for seven land cover classes (forest, shrub land, agriculture/pasture, plantation, urban/infrastructure, barren land, and water) between 2000 and 2015 using Landsat imagery (30 m resolution) in the Google Earth Engine platform. Forest cover was estimated at 26% in 2000 and 21% in 2015. Although forest cover is declining in Haiti, our quantitative analysis resulted in considerably higher forest cover than what is usually reported by local and international institutions. Our results determined that areas of forest decline were mainly converted to shrubs and mixed agriculture/pasture. An important driver of forest loss and degradation could be the high demand for charcoal, which is the principal source of cooking fuel. Our results differ from other forest cover estimates and forest reports from national and international institutions, most likely due to differences in forest definition, data sources, spatial resolution, and methods. In the case of Haiti, this work demonstrates the need for clear and functional definitions and classification methods to accurately represent land use/cover change. Regardless of how forests are defined, forest cover in Haiti will continue to decline unless corrective actions are taken to protect remaining forest patches. This can serve as a warning of the destructive land use patterns and can help us target efforts for better planning, management, and conservation.

Characteristics of aerosol optical depth over land types in central Asia

Aerosols are an important contributor to global atmospheric changes and have critical effects on the climate system. Regionally, aerosols in central Asia comprise a significant portion of global aerosols. Based on aerosol optical depth (AOD)Level 2 daily product data and land cover type product data, the long-term AOD characteristics of six major land use/cover types and their relationships with landscape metrics are discussed. Contribution analysis is applied to quantitatively estimate the effects of land use/cover on regional AOD over central Asia. The results show that series of daily AODs over six land uses/covers display remarkable annual cyclic variations and obvious seasonal changes. The annual average AODs for barren land and cropland are highest, followed by regional AODs. There are different frequencies and times of occurrence for high AOD values of various land types. Urban areas are one of the major contributors to the regional atmosphere in winter; grasslands have a great influence on regional AOD decreases. Barren land always has a high contribution to the regional AOD. The land use types affected by anthropogenic activities were smaller contributors to regional aerosols than barren lands affected by climate factors. This paper advances the understanding of relationship between aerosols and land use/cover and facilitates land use decision making.

Attributing the hydrological impact of different land use types and their long-term dynamics through combining parsimonious hydrological modelling, alteration analysis and PLSR analysis

Understanding the relationship between hydrological processes and environmental changes is important for improved water management. The Geba catchment in Ethiopia, forming the headwaters of Tekeze-Atbara basin, was known for its severe land degradation before the recent success in integrated watershed management. This study analyses the hydrological response attributed to land management change using an integrated approach composed of (i) simulating the hydrological response of Land Use/Cover (LULC) changes; (ii) assessing the alteration of streamflow using Alteration of Hydrological Indicators (IHA); and (iii) quantifying the contribution of individual LULC types to the hydrology using Partial Least Square Regression model (PLSR). The results show that the expansion of agricultural and grazing land at the expense of natural vegetation has increased the surface runoff 77% and decreased dry season flow by 30% in the 1990s compared to 1970s. However, natural vegetation started to recover from the late 1990s and dry season flows increased by 16%, while surface runoff declined by 19%. More pronounced changes of the streamflow were noticed at sub-catchment level, mainly associated with the uneven spatial distribution of land degradation and rehabilitation. However, the rate of increase of low-flow halted in the 2010s, most probably due to an increase of water withdrawals for irrigation. Fluctuations in hydrological alteration parameters are in agreement with the observed LULC change. The PLSR analysis demonstrates that most LULC types showed a strong association with all hydrological components. These findings demonstrate that changing water conditions are attributed to the observed LULC change dynamics. The combined analysis of rainfall-runoff modelling, alteration indicators and PLSR is able to assess the impact of environmental change on the hydrology of complex catchments. The IHA tool is robust to assess the magnitude of streamflow alterations obtained from the hydrological model while the PLSR method is useful to zoom into which LULC is responsible for this alteration.

Land-use/cover change in Coimbatore urban area (Tamil Nadu, India)-a remote sensing and GIS-based study

The purpose of the present study was to explain land-use/cover changes in Coimbatore City Corporation using Landsat ETM+ and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data for the period of 2003-2014. Two Landsat images from years 2003 and 2014 were downloaded from USGS Earth Explorer. Maximum likelihood method was used to classify the images into five classes: urban fabric, vegetation, water bodies, agriculture lands, and barren lands. Overall kappa accuracy measure is about to 87.60 and 86.15% for the years 2003 and 2014, respectively. The change detection analysis has been performed for years 2003 and 2014 postclassified images. The results of the study have indicated that Coimbatore City has experienced rapid modifications in LULC, particularly in terms of urban/built-up area. Over the past 11 years, urban/built-up areas have increased by 94.5 km², resulting in a significant drop in the area of agricultural land and vegetation cover. It is found that (1) urban areas are increased 200% due to population growth cum rapid economic progress. (2) Vegetation cover decreased 38.76% due to conversion into urban features. (3) Water bodies in area increased to 15.78% due to eradication of encroachment. (4) There is loss of 1.89% of agricultural lands due to demand for construction activities. (5) About 85.24% of barren lands were converted into other uses, particularly 57.33% to urban areas. (6) Urban growth has accelerated towards north-eastern, northern, and eastern parts, where national highways exist. The built-up areas were dropped from 85.32 to 22.28%, within 5-km distance from the city center.

Geospatial assessment of tourism impact on land environment of Dehradun, Uttarakhand, India

India's tourism industry has emerged as a leading industry with a potential to grow further in the next few decades. Dehradun, one of the famous tourist places in India located in the state of Uttarakhand, attracts tourist from all over the country and abroad. The surge in tourist number paved the way for new infrastructure projects like roads, buildings, and hotels, which in turn affects the topography of the mountainous region. In this study, remote sensing and GIS techniques have been used to assess the impact of tourism on the land environment of Dehradun. Satellite images of the years 1972, 2000, and 2016 were analyzed using object-based image analysis (OBIA) to derive land use and land cover (LULC) and ASTER-DEM (Digital Elevation Model) was used to determine the topography of the study area. LULC classification includes built-up, vegetation, forest, scrub, agriculture, plantation, and water body. The slope of the region was categorized as gentle, moderate, strong, extreme, steep, and very steep. To assess the sprawl of built-up on high terrain land, built-up class of LULC was overlaid on slope classes. The overlay analysis reveals that due to increase in tourism, the land use in terms of the built-up area has been extended from gentle slope to very steep slope. The haphazard construction on the extreme, steep, and very steep slope is prone to landslide and other natural disasters. For this, landslide susceptibility maps have also been generated using multicriteria evaluation (MCE) techniques to prevent haphazard construction and to assist in further planning of Dehradun City. This study suggests that a proper developmental plan of the city is essential which follows the principles of optimum use of land and sustainable tourism.

Land use and land cover data changes in Indian Ocean Islands: Case study of Unguja in Zanzibar Island

Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETM+Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change.

Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project

The satellite imagery has been effectively utilized for classifying land cover types and detecting land cover conditions. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor imagery has been widely used in classification process of land cover. However, atmospheric corrections have to be made by preprocessing satellite sensor imagery since the electromagnetic radiation signals received by the satellite sensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study, an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance (TOA), was used to classify the land use/cover types, according to COoRdination of INformation on the Environment (CORINE) land cover nomenclature, for an area representing the heterogonous characteristics of eastern Mediterranean regions in Kahramanmaras, Turkey. The results indicated that using the surface reflectance data of ASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of 83.2% and 0.79, respectively) and low-cost cover mapping as a part of inventory for CORINE Land Cover Project.