Vegetation Cover Research Articles

Assessment of Soil Moisture in Vegetation Regions of Mu Us Sandy Land Using Several Aridity Indicators

Drought, a significant calamity in the natural domain, has extensive worldwide repercussions. Drought, primarily characterized by reduced soil moisture (SM), presents a significant risk to both the world environment and human existence. Various drought indicators have been suggested to accurately represent the changing pattern of SM. The study examines various indices related to the Drought Severity Index (DSI), Evaporation Stress Index(ESI), Vegetation Supply Water Index(VSWI), Temperature-Vegetation Dryness Index(TVDI), Temperature Vegetation Precipitation Dryness Index(TVPDI), Vegetation Health Index(VHI), and Temperature Condition Index (TCI). An evaluation was conducted to assess the effectiveness of seven drought indicators, such as DSI, ESI, TVPDI, VSWI, etc., in capturing the changes in SM in Mu Us Sandy Land. The research results indicated that DSI and ESI had the highest accuracy, while TVDI and VSWI showed relatively lower accuracy. However, their smaller fluctuations in the time series demonstrated stronger adaptability to different regions. Additionally, the delayed impact of aridity indices on soil moisture, variable attributes, temperature, and vegetation coverage in sandy land and grassland areas with low, medium, and high coverage all contributed to the effectiveness of the four aridity indices (DSI, ESI, VSWI, and TVPDI) in capturing the dynamics of soil moisture. The primary element that affects the effectiveness of TVDI is the divergence of the relationship curve between Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which is a kind of deterioration. This paper presents a very efficient approach for monitoring soil moisture dynamics in dry and semi-arid regions. It also analyzes the patterns of soil moisture changes, offering valuable scientific insights for environmental monitoring and ecological enhancement.

The Scale-Dependent Differences in Cooling Efficiency of UGS in Different Functional Areas: A Case Study of Xi’an, China

Urban green spaces (UGS) play a critical role in mitigating the urban heat island (UHI) effect and addressing climate change challenges through their cooling effects. Expanding green space and optimizing its layout are key strategies in urban planning. However, with limited land resources, maximizing cooling efficiency becomes crucial. While previous studies have yet to reach a consensus on the optimal UGS size threshold for achieving maximum cooling efficiency, this study employs high-resolution remote sensing imagery to extract 25,594 UGS patches in Xi’an and explores the scale dependency of UGS cooling effects. Results show that 54.20% of the patches exhibit a “cooling island effect”, reducing surface temperatures by 0.10 ± 0.13 °C to 1.66 ± 1.15 °C. A nonlinear relationship was observed between cooling intensity and UGS size, influenced by vegetation coverage and edge complexity. Further analysis reveals that medium-sized UGS have the highest cooling efficiency. These UGS were categorized into five functional zones to explore the dominant factors affecting cooling efficiency in each zone, and corresponding strategies for improvement were proposed. These findings provide insights into optimizing UGS layout and refining the cooling efficiency thresholds.

Investigation of impact of community environment factors on the residents’ visiting rate to outdoor venues in South China

Understanding the activity patterns of urban residents is crucial for urban community design and urban energy forecasting. Predicting the visitation rates of different types of locations is a important issue because urban residents can only be in one place at a time. Achieving accurate predictions of outdoor public space visitation rates is equivalent to predicting the upper limit of the number of visitors to other buildings. Previous similar studies usually rely on survey methods such as questionnaires and GPS positioning. These methods have some drawbacks, such as small sample sizes and inaccurate data. In this paper, we used mobile signaling to investigate the park visit rates of residents in different communities in Guangzhou. In accordance with Chinese tradition, we define a community as a residential community, which consists of multiple residential units and a set of basic service facilities and management structures that are sufficient to meet the daily needs of residents. We found that the park visit rate of a community is closely related to the characteristics of the community itself. The park visit rate is positively correlated with the average LST (land surface temperature) of the communities, the average distance between the community and the large park, and the building coverage rate, while it is negatively correlated with the vegetation coverage rate, the average surface reflection rate, the convenience of transportation, and the per capita green space area. Given the different travel habits of urban residents on weekdays and weekends, we also used multiple linear regression to establish prediction models for community park visitation rates on weekdays and weekends.

Detection of spatial and temporal variation characteristics of vegetation cover in the Lower Mekong region and the influencing factors

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

Biophysical and socioeconomic characterization of Agewmariam experimental watershed in Northern Ethiopia: insights and management options.

Watershed characterization is essential for sustainable watershed management and effective resource utilization, particularly in assessing changes resulting from interventions. This study investigates the biophysical and socio-economic conditions of the Agewmariam watershed, aiming to develop land capability and suitability maps while identifying viable management options. Biophysical data, including land slope, soil properties, erosion severity, stoniness/rockiness cover, and vegetation cover, were collected through field surveys and analyzed using overlay analysis in ArcGIS. Socio-economic data, encompassing population demographics, income, and expenditure, were gathered via individual interviews, complete census, and focus group discussions and summarized using descriptive statistics. The study identified 259 households with an average family size of 4 and a demographic dependency ratio of 96.6%. The major sources of income are crop production and livestock rearing supplemented by casual labor and food aid. The average farmland holding size is 0.5ha, with sorghum, barley, teff, and wheat as the dominant crops. The watershed is characterized by six land capability classes (classes II, III, IV, VI, VII, and VIII). The suitability analysis indicated that the watershed is not currently suitable for wheat and teff crops unless physical, chemical, and biological management improvements are implemented. The study revealed that the major limiting factors for land capability and suitability were slope, erosion severity, stoniness, soil organic matter, and soil texture. The socio-economic characterization enhanced awareness about the local socio-economic condition, informing appropriate planning and management strategies. The study recommends intensive soil and water conservation intervention, afforestation on hillsides, changing the land use system, and the addition of organic matter and fertilizers to enhance land capability and suitability for sustainable agricultural practices.

Mapping and Analyzing Ecosystem Services Hotspots and Coldspots for Sustainable Spatial Planning in the Greater Asmara Area, Eritrea.

Rapid urbanization in African metropolises like the Greater Asmara Area, Eritrea, poses numerous environmental challenges, including soil sealing, loss of vegetation cover, threats to protected natural areas, and climate change, among others. Mapping and assessing ecosystem services, particularly analyzing their spatial and temporal distribution is crucial for sustainable spatial planning. This study aims at mapping and analyzing ecosystem services hotspots and coldspots dynamics in the Greater Asmara Area to identify recent trends and opportunities for enhancing ecosystem services supply. Utilizing remote sensing images, we produced land cover maps for 2009 and 2020 and mapped six ecosystem services through a lookup table approach. The study includes provisioning, regulating and maintenance, and cultural ecosystem services. We analyzed their spatio-temporal variations, identifying ecosystem services hotspots and coldspots and their changes over time. Results show that overall ecosystem services potential in the Greater Asmara Area remains low but stable, with some improvements. By 2020, areas with no ecosystem services potential decreased in southern regions like Gala Nefhi and Berik, and new hotspots and coldspots emerged in central Gala Nefhi. This pilot study demonstrates the feasibility and key challenges of the ecosystem services hotspots and coldspots approach for sustainable spatial planning in rapidly urbanizing African metropolitan regions. Despite limitations, the study offers valuable insights into ecosystem services potentials, and related hotspots and coldspots dynamics, raising awareness and paving the way for further research and application.

Colonial management drives ecological change following the exclusion of Indigenous stewardship in a Stoney Iyethka montane grassland, Canadian Rocky Mountains

Abstract For millennia, Indigenous Peoples and their ecological stewardship have kept culturally important landscapes open, diverse and productive. Under colonization which suppresses stewardship activities, landscape vegetation patterns shift and areas previously stewarded by Indigenous Peoples are now undergoing successional change. As a case study, we document ecological change on the homelands of the Stoney Iyethka Nations in the Canadian Rocky Mountains, where landscapes have changed dramatically over the past century of colonial management. On the Stoney Iyethka traditional montane Egnuck Wida grasslands, we analysed vegetation change on both the landscape and plot level. Using oblique photographs taken in 1924 paired with 2021 satellite imagery, we compared past and present landscape vegetation cover and assessed drivers of succession. We also examined differences in vegetation class cover and plant community structure between surveys conducted in 1981, 1995 and 2020. Nearly half (47%) of the landscape surveyed showed seral progression in vegetation class, which was not explained by topography, geology or climate warming. Grassland area decreased four‐fold between 1924 and 2021. Grassland retention was strongly related to management zoning, with greater losses in the crown‐managed ecological reserve than on lands that remain under Stoney Iyethka stewardship. Vegetation plots surveyed reveal changes to plant community composition and shifts in dominant vegetation class. In plots previously composed primarily of forbs and graminoids, shrubs have become the dominant groundcover. Declines in historic vegetation include a loss of culturally important food, medicine and ceremonial plants to the Stoney Iyethka Nations. The most likely explanation for these results is the displacement of Indigenous Peoples and their stewardship from the landscape. We demonstrate that the past century of colonial environmental management has altered ecological processes maintained on this landscape for millennia by Indigenous Peoples. Read the free Plain Language Summary for this article on the Journal blog.

Research on the spatiotemporal distribution and control degree of soil erosion in Dali River Basin

The Dali River basin as the representative areas of the middle reaches of the Yellow River. Accurately evaluating the degree of soil erosion control is very important for soil erosion control. In response to the problems existing in the current research on soil erosion control degree (SECD) methods, the maximum possible soil erosion modulus is introduced into the evaluation model. Thereby eliminating the uncertainty of the assumed state of the original model. This paper calculates the SECD for 2020 based on this method. The results show: (1) From the soil erosion modulus spatial distribution, it can be seen that the soil erosion intensity is stronger in the eastern and southwestern parts. (2) Based on the SECD spatial distribution, it was found that eastern and southwestern regions were well controlled. This is consistent with the actual situation. (3) As the slope increases, the area proportion of SECD within the 0.2-0.3 range in each slope zone shows an increasing trend, while that of SECD within the 0.5-1 range gradually decreases; (4) In the case of vegetation coverage greater than 80%, SECD is still concentrated between 0.3-0.5, which indicates that vegetation coverage is not the only factor affecting soil erosion control. This research provided a new perspective for the evaluation of SECD.

Monitoring the Dynamics of Aquatic Vegetation in a Typical Shallow Lake Using the Water Bloom Index Algorithm—A Case Study in Bao’ an Lake in the Middle Reaches of the Yangtze River

Understanding changes in the distribution and coverage of aquatic vegetation (AV) is of great significance for the restoration of lake ecosystems. In this study, the vegetation and bloom indices (VBI) algorithm were used to interpret submerged aquatic vegetation (SAV), floating/emergent aquatic vegetation (FEAV), and algal bloom (AB). The dynamics of AV and their influencing factors in Bao’ an Lake, in the middle reaches of the Yangtze River in China, were studied from 2000 to 2023. The results showed that (1) the VBI algorithm can accurately distinguish AV and AB of different life forms with an overall accuracy of 93% and a kappa coefficient of 0.86. (2) Macrophyte coverage decreases. AV grew vigorously in spring, and SAV was the dominant type within it, whereas AV coverage was low in summer, and SAV had no summer species for a long time. In 2000, the coverage of AV was the highest, reaching 64.5%, but a gradual decrease that followed in the coming years finally led to a coverage percentage of less than 5% by 2023. (3) The correlation between SAV coverage and total phosphorus (p < 0.01), total nitrogen (p < 0.05), and water depth/transparency (p < 0.05) in Bao’ an Lake were 0.23, 0.28, and 0.32, respectively. (4) The SAV species experienced three stages: richness (before 2003), monotonicity (2004–2020), and final disappearance (2021–present). This study shows that the coverage of AV in Bao’ an Lake is too low and the number of SAV species is one (2010–now). Therefore, it is necessary to implement measures to improve vegetation coverage and diversity.

Estimating the Greenhouse Gas Emission Potential Due to Construction Work on the 225 kV Segou - Bamako High Voltage BI-Ternal Electric Line in Mali in The Context of Climate Change

The aim of this study is to assess the carbon emissions resulting from the construction of the power line linking Bamako to Ségou. It focuses on direct emissions, more specifically those linked to the degradation and desctruction of the vegetation cover in the project right-of-way. To collect the data, surveys were set up on the project right-of-way, through which 3302 trees were inventoried in situ at the three sites. Circumference was measured at 1.30 m from the ground surface. Allometric equations for direct biomass estimation were used as a predictor o f tree diameter. Emission factors were then used to estimate the potential greenhouse gas emissions resulting from tree felling during power line construction. The standard error associated with the carbon fraction in dry biomass was calculated. In the Ségou, Koulikoro and Dioïla project areas, there are a number of plant species that provide local populations with various ecosystem services, including micro-climate regulation through carbon sequestration or absorption of atmospheric CO2. The implementation of the project will undoubtedly result in the felling of these trees. This felling will generate emissions of 22.11 t.eqCO2/ha in Ségou, 16.56 t.eqCO2/ha in Koulikoro and 15.43 t.eqCO2/ha in Dioïla. Across Ségou, Koulikoro and Dioïla, the trees in the project right-of-way represent a reservoir of 34.04 t/ha of above-ground woody biomass. This biomass represents a carbon stock of around 16.58 t.C/ha. This carbon stock will be transformed into a carbon source with emissions of 60.78 t.eqCO2/ha if the trees in the power line right-of-way are systematically felled. Mitigation measures are therefore urgently needed, with compensatory reforestation areas planted with species with high carbon sequestration potential.

Impact of land use/land cover (LU/LC) changes on ecosystem service values in Muger Sub-basin, Upper Blue Nile Basin, Ethiopia

This study was conducted to estimate the impact of land use/land cover (LULC) changes on the ecosystem service value (ESV) in the Upper Blue Nile basin over three-decade (1986–2020). The findings revealed that there is a decline in total ESV from US$ 492.77 × 106 in 1986 to US$ 400.65 × 106 for the year 2020. The ESV lost between 1986 and 2020 was about US$ 92.11 × 106. In terms of the individual ecosystem services, the contribution of all service values declined except food production and biological control. Among the major contributors of ESVs, food production, water regulation, erosion control, climate regulation, nutrient cycling, waste treatment, and water supply represent 89%, 88%, 86% in 1986, 2003, and 2020, respectively. Soil erosion and sediment transport under environmental pressure significantly contributed for the loss of ecosystem services (ES) in the sub-basin. In addition, FGD and KII ranked provisioning ecosystem services first in order of importance for communities in the study area. Therefore, it is important to pay attention to the sustainable conservation and restoration of natural resources through natural vegetation protection, enhanced vegetation cover, conservation practices and wetland management to enhance the natural capital and ecosystem services in the Muger Sub-basin.

Trends in socioeconomic disparities in urban heat exposure and adaptation options in mid-size U.S. cities

There is ample evidence that Environmental Justice communities experience high levels of extreme heat. However, it is unknown how disparities in urban heat exposure and adaptation options change over time. This study investigates socioeconomic disparities over time in urban heat exposure and adaptation options in eight mid-sized Northeastern cities. We ask: How were socioeconomic factors associated with heat exposure and adaptation options over time? We analyzed disparities at the census block group level and census block level, respectively. At the census block group level, we ran spatial regression models between socioeconomic variables, including race, income, gender, and age, and heat exposure and adaptation variables, including land surface temperature, normalized different vegetation index (NDVI), tree cover, and air conditioning ownership rate. We found that: Low median household income is always associated with high LST and low NDVI from 1990 to 2020; Low percentage of females is always associated with high LST and low NDVI from 1990 to 2020. High percentage of POC is associated with high LST in 2010 and 2020, but not in 1990 and 2000; Low median household income and low percentage of elderly are associated with lower tree cover; High percentage of POC, low percentage of elderly, and low median household income are associated with lower AC rates. In analysis at the census block level by city, we found that disparities in urban heat exposure between predominantly POC and predominantly white communities increased in most cities during 1990-2020. Predominantly POC communities consistently have lower vegetation cover over time in most cities. Disparities in vegetation cover per unit area increased in most cities, whereas disparities in vegetation cover per capita decreased in most cities. Our findings of the trends in disparities in heat exposure and adaptation are useful for forecasting disparities in the future. These findings also suggest that interventions should prioritize cities with increasing disparities in heat exposure and adaptation.

A spatially explicit multi-hazard framework for assessing flood, landslide, wildfire, and drought susceptibilities

Sustainable development goals require evaluating vulnerabilities and examining natural and climatic hazards for effective planning that reduces their impact on economic, social, and developmental efforts. Key hazards like floods, landslides, wildfires, and droughts have significantly affected terrestrial ecosystems and human societies, emphasizing the importance of comprehending these hazards. This study aimed to predict and spatially map multi-hazard, identifying historical and potential risks to inform sustainable development and construction programs that mitigate risks and promote resilience. A 34-year drought magnitude map was generated using long-term data, and ensemble and individual machine learning techniques were used to produce maps of flood, landslide, and wildfire hazards in a northwest region of Iran. Results demonstrated that ensemble learning models outperformed individual models, with the top-performing models being the weighted average (WA) of the two best models, random forest, extreme gradient boosting, WA models with over 80% accuracy, and WA incorporating all models, respectively. The CART model performed best among individual models. Variable importance analysis revealed that slope and precipitation were crucial factors for identifying high-hazard landslide areas, distance from waterways, vegetation cover, and topographic humidity index emerged as the most crucial factor for identifying flood hazard areas, while vegetation, rainfall, and proximity to roads significantly impacted wildfire hazard. The multi-hazard map produced by our study indicated that about 30% of the study area was highly and very highly susceptible to floods, landslides, wildfires, and droughts and the hazards mitigation efforts should be primarily directed to these specific portions of the study area. Our study underscored the importance of integrating long-term data and machine learning techniques in multi-hazard prediction and mapping, ultimately guiding mitigation efforts and promoting resilience in the face of natural and climatic hazards.

Quantitative contributions of different atmospheric circulation systems to Holocene aeolian activity in northwestern China: Evidence from a closed interdune lake in the Tengger Desert hinterland

The aeolian deserts of northwestern China are major landscape types in the arid regions of the Northern Hemisphere, and collectively they are one of the largest dust source regions on Earth. However, owing to occurrence of sedimentary hiatuses within aeolian deposits in the deserts, we lack clear knowledge of the history of Holocene aeolian activity and the interaction between aeolian processes and their potential drivers. In this study, we extracted an environmentally sensitive grain-size component from the sediments of a closed interdune lake in the hinterland of the Tengger Desert. Our methodology included the application of End Member Analysis (EMA) of different modern sediment types from catchment to regional scales. We reconstructed aeolian activity over the past 13 cal ka BP and quantified the contributions of environmental factors. The results indicated that the EM 2 fraction of the interdune lake sediments is mainly transported by local winds and reflects changes in the intensity of aeolian activity. Based on EM 2 the strongest aeolian activity occurred during 13.0–7.0 cal ka BP, especially during 8.0–7.0 cal ka BP, and the weakest activity occurred during 7.0–3.5 cal ka BP. Aeolian activity increased after 3.5 cal ka BP, but with a gradually weakening trend. The occurrence of the weakest aeolian activity in the Tengger Desert during the Middle Holocene differs from that on the Asian Summer Monsoonal Boundary and in the area influenced by the Westerlies-dominated climate regime. Thus, there was a clearly defined spatio-temporal differentiation of Holocene aeolian activity across the deserts and dune fields of northern China. Quantitative analysis of the contributions of the potential drivers indicated that wind activity forced by different atmospheric circulation systems, rather than changes in vegetation cover, were the most important driver of regional aeolian activity, although their relative effects varied during the Holocene.

Spatiotemporal changes and management measure to enhance ecosystem services in the Mongolian Plateau

The eco-environment in many underdeveloped areas is vulnerable. Elucidating the changes and relationships in ecosystem services (ESs) is a fundamental basis for achieving sustainable development in these regions. Utilizing multiple data sources and models, we quantified water provision (WP), habitat quality (HQ), carbon fixation (CF), soil conservation (SC), and wind erosion prevention (WEP) on the Mongolian plateau during 1992-2018. We then analyzed the spatial-temporal changes, trade-offs/synergies, and bundles relationship of these ESs. The results indicated there was high spatial variability in five ESs across the plateau, with overall higher ESs in forested areas, and grassland and cropland areas had higher WEP values. The annual mean values of WP, HQ, CF, SC, and WEP in the plateau during 1992-2018 were 27.15 mm, 0.57, 176.17 gC·m2, 48.83 t·hm2, and 58.31 t·hm2, respectively. Due to fluctuations in precipitation, vegetation cover and land use, the five ESs decreased from 1992 to 2000s, but increased from 2000s to 2018, Notably, the HQ changed most significantly (p<0.01), while the WP changed insignificantly (p>0.05). The different ESs on the plateau overall exhibited synergistic effects, trade-offs between several pairs of ESs related to HQ, were observed in cropland areas. We further identified five distinct categories of ES bundles and proposed targeted recommendations for spatial planning and management of these ESs, tailored to their characteristics. The findings offer a valuable reference for high-quality environmental management, as well as the restoration and enhancement of ESs in arid inland areas in a warming climate.

Investigation, Determination, and Analysis of Dominant Vegetation in Mining Areas

During the mining process, a large amount of untreated and unusable land, namely mining wastelands, is generated. Ecological remediation in mining areas aims to rehabilitate polluted mining wasteland, thus enabling the reuse of land resources. Phytoremediation technology can effectively restore pollution in mining areas, with the prerequisite of identifying suitable tolerant or dominant plant species, which are typically found in the vicinity of mining sites with a long history of exploitation. This study conducted field surveys and collected samples, followed by laboratory analyses to explore the dominant plant species in the vanadium-titanium mining area of Zhujiabaobao, Panzhihua. Field surveys revealed a low coverage of wild vegetation due to the fragile ecological environment, primarily consisting of low, medium, and high-coverage vegetation types. Based on a comprehensive analysis of 13 dominant plant species in terms of their quantity, quality, morphological characteristics, and potential value, Eriophorum vaginatum, Rumex hastatus, and Dodonaea viscosa were identified as the three most suitable species for ecological remediation in this mining area.

Growth and Survival Outcomes for Immature Gopher Tortoises in Contrasting Habitats: A Test of Drone-Based Habitat Assessment.

Juvenile growth rate is a critical demographic parameter, as it shortens the time to maturity and often dictates how long individuals remain vulnerable to predation. However, developing a mechanistic understanding of the factors determining growth rates can be difficult for wild populations. The gopher tortoise (Gopherus polyphemus) is an ecosystem engineer threatened by habitat loss and deficient management of pinelands in the southeastern United States. We investigated the factors governing immature gopher tortoise growth and explored the use of drone-based imagery for habitat assessment by comparing predictive models based on ground-based plant surveys versus drone-derived data. From 2021 to 2022, we tracked and measured immature tortoises in native sandhill and human-modified, ruderal habitat in south-central Florida. Using quarterly, high-resolution drone imagery, we quantified plant cover types and vegetation indices at each occupied burrow and measured the frequency of occurrence of forage species by hand. Annual growth rates of immature tortoises in ruderal habitat were higher than those in sandhill and were the highest published for this species. Models based on drone-derived data were able to explain similar proportions of variation in growth as ground-collected measures of forage, especially during the late dry season when both types of models were most predictive. Habitat differences in forage nitrogen content were also more pronounced during this season, when dominant ground cover in ruderal habitat (bahiagrass) had much higher nitrogen content than dominant ground cover in sandhill (wiregrass). Despite concerns about potential growth-survival trade-offs, tortoises in ruderal habitat did not exhibit lower apparent survival. Our findings indicate that habitat dominated by nutritious non-native grass can provide a valuable supplement to native sandhill through the mechanism of increased growth rates due to higher forage quality. Finally, our study demonstrates that drone technology may facilitate management by providing less labor-intensive ways to assess habitat quality for this and other imperiled herbivores.

Shrub cover declined as Indigenous populations expanded across southeast Australia.

Wildfires in forests globally have become more frequent and intense because of changes in climate and human management. Shrub layer fuels allow fire to spread vertically to forest canopy, creating high-intensity fires. Our research provides a deep-time perspective on shrub fuel loads in fire-prone southeastern Australia. Comparing 2833 records for vegetation cover, past climate, biomass burning, and human population size across different phases of human occupation, we demonstrated that Indigenous population expansion and cultural fire use resulted in a 50% reduction in shrub cover, from approximately 30% from the early to mid-Holocene (12 to 6 thousand years ago) to 15% during the late to mid-Holocene (6 to 1 thousand years ago). Since the start of British colonization to the present, shrub cover has increased to the highest ever recorded (mean of 35% land cover), increasing the risk of high-intensity fires.

Spatio-temporal land use/land cover change analysis and assessment of urban heat island in Ghana: A focus on the Greater Accra Region

The expansion of cities coupled with economic development over the years has transformed many locations into hotspots for massive urban populace. The Greater Accra Region which is the capital city of Ghana is no exception. The urban population growth rate in the region has expanded extensively at the expense of increasingly vegetation cover. As a result, there is an increasing need to investigate urban resilience, land use/land cover (LULC) change, and urban heat islands (UHI) dynamics in the region. The aim of this study is to analyze multi-spectral Landsat images of 2000 and 2020 to examine the LULC change and the UHI trend across the Greater Accra Region of Ghana. The results from the analysis show a significant change in the spatial trend of land surface temperature (LST) and UHI between the years 2000 and 2020. Spatial distribution of LST from 0°C to 28°C and 17°C to 33°C in the years 2000 and 2020 respectively were observed. Urban areas dominated more than half of the study area in 2020, covering 85% (equivalent to 3160 sq. km), and reflecting a 20% increase from the year 2000 to 2020. During the same period, sparse and dense forested areas decreased by 10% (373 sq. km) and 4% (146 sq. km) with a 5% reduction in bare land (equivalent to 177 sq. km). The spatio-temporal analysis revealed a significant surge in the population of urban areas within the study area. The UHI areas also increased from 13.20% in 2000 to 18.20% in 2020. On the other hand, non-UHI areas decreased from 86.80% to 81.80% during the same period. The successful contribution of this research demonstrates the usefulness of spatial models as tools in generating LULC maps for assessing UHI to facilitate future sustainable city planning.

Spatiotemporal variations of surface albedo in Central Asia and its influencing factors and confirmatory path analysis during the 21st century

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 °C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.