Vegetation Distribution Research Articles

Assessing climatic response and drought resilience in growth of Pinus tabulaeformis Carr. and Tsuga chinensis Pritz. on the southern slope of the Qinling Mountains

Climate anomalies have significant impacts on forest productivity and tree mortality worldwide, leading to ecological disturbances. Understanding the climate-growth relationship and species-specific responses to climate and drought events are crucial for developing effective conservation strategies for tree growth. However, studies on such issues are scarce in the Qinling Mountains (QLM), a significant geo-ecological boundary for climate, vegetation distribution, and river systems in China. This study focuses on the southern slope of the QLM, where we developed tree-ring-width chronologies for Pinus tabulaeformis Carr. and Tsuga chinensis Pritz. in the same habitat, and analyzed their response to climate and two extreme drought events. Both species were found to have a positive correlation with temperature, but their responses to precipitation and scPDSI differed. Specifically, P. tabulaeformis showed a negative correlation with precipitation and scPDSI, while T. chinensis exhibited a positive correlation with precipitation. These differences in response may be attributed to species-specific preferences and interspecific competition between the two coniferous species. Results of the 31-year sliding correlation analysis and K-S test analysis, which aimed to explore the dynamic relationship between chronologies and their most limiting climate factors, demonstrated that both P. tabulaeformis and T. chinensis have experienced a qualitative change in their response patterns to certain climatic factors. Under the backdrop of warming climate, the response of P. tabulaeformis to the maximum temperatures from June to September of the previous year has diminished to a non-response; the response to precipitation from July to September of the previous year, although still significantly negatively correlated, has seen a decrease in significance. In contrast, T. chinensis has exhibited an increasing sensitivity to precipitation from September of the previous year to June of the current year. Study on resistance (Rt), recovery (Rc), and resilience (Rs) of tree growth to drought events revealed that P. tabuliformis and T. chinensis did not exhibit a negative response to the transient drought event in 1933 AD. However, when faced with the prolonged and severe drought event in 1941–1944 AD, both species experienced a decline in growth. It was observed that T. chinensis displayed weaker drought tolerance compared to P. tabuliformis and was more susceptible to the negative impacts of drought conditions. These findings suggest that forest management in the context of climate change should be species-specific, and more effort is needed for species with weaker drought resistance in the QLM, such as T. chinensis.

Mechanism of Vegetation Greenness Change and Its Correlation with Terrestrial Water Storage in the Tarim River Basin

The response of dryland vegetation to climate change is particularly sensitive in the context of global climate change. This paper analyzes the characteristics of spatial and temporal dynamics of vegetation cover in the Tarim River Basin, China, and its driving factors in order to investigate the response of vegetation growth to water storage changes in the basin. The Enhanced Vegetation Index (EVI), the GRACE gravity satellite, and meteorological data from 2002 to 2022 are used to decipher the characteristics of the response of water storage changes to vegetation changes, which is of great significance to the realization of regional ecological development and sustainable development. The results of the study show the following: (1) The vegetation in the Tarim River Basin has an overall increasing trend, which is mainly distributed in the Aksu Basin and the Weigangkuche River Basin and is spatially distributed in the form of a ring. (2) Vegetation distribution greatly improved during the 20-year study period, dominated by high-cover vegetation, with a change rate of 200.36%. Additionally, vegetation changes are centered on the watersheds and expand to the surrounding area, with a clear increase in vegetation in the Kumukuri Basin. Areas with a vegetation Hurst index of <0.5 account for 63.27% of the study area, and the areas with a continuous decrease were mainly located in the outer contour area of the Tarim River and Kumu Kuri Basins. (3) There are obvious spatial differences in the correlation between EVI and temperature and precipitation elements. The proportion of areas with positive correlation with temperature within the study area is 64.67%. EVI tends to be consistent with the direction of migration of the center of gravity of the population and GDP, and the areas with positive correlation between vegetation and terrestrial water reserves are mainly distributed in the northern slopes of the Kunlun Mountains, with an area proportion of about 50.513%. The Kumukuli Basin also shows significantly positive correlation.

Mapping global lake aquatic vegetation dynamics using 10-m resolution satellite observations

Aquatic vegetation is crucial for improving water quality, supporting fisheries and preserving biodiversity in lakes. Monitoring the spatiotemporal dynamics of aquatic vegetation is indispensable for the assessment and protection of lake ecosystems. Nevertheless, a comprehensive global assessment of lacustrine aquatic vegetation is lacking. This study introduces an automatic identification algorithm (with a total accuracy of 94.4%) for Sentinel-2 MSI, enabling the first-ever global mapping of aquatic vegetation distribution in 1.4 million lakes using 14.8 million images from 2019 to 2022. Results show that aquatic vegetation occurred in 81,116 lakes across six continents over the past four years, covering a cumulative maximum aquatic vegetation area (MVA) of 16,111.8 km2. The global median aquatic vegetation occurrence (VO, in %) is 3.0%, with notable higher values observed in South America (7.4%) and Africa (4.1%) compared with Asia (2.7%) and North America (2.4%). High VO is also observed in lakes near major rivers such as the Yangtze, Ob, and Paraná Rivers. Integrating historical data with our calculated MVA, the aquatic vegetation changes in 170 lakes worldwide were analyzed. It shows that 72.4% (123/170) of lakes experienced a decline in aquatic vegetation from the early 1980s to 2022, encompassing both submerged and overall aquatic vegetation. The most substantial decrease is observed in Asia and Africa. Our findings suggest that, beyond lake algal blooms and temperature, the physical characteristics of the lakes and their surrounding environments could also influence aquatic vegetation distribution. Our research provides valuable information for the conservation and restoration of lacustrine aquatic vegetation.

Living in Sangiran: A spatial reconstruction of hominin environment in Java at 1 Ma

This study focuses on analysing and testing the relationship between Homo erectus behaviour and environmental dynamics in Sangiran, Java, at the time around 1 Ma. Here, palaeoenvironmental conditions encountered by Homo erectus in Java at 1 Ma were reconstructed using multiple methods. High resolution palaeotopography and coastlines, palaeoclimatic, as well as palaeovegetation maps are produced in this study for the eastern part of Java, where the majority of hominin fossils was found. After correcting for tectonic elevation changes and eustatic sea-level changes, which sum up to a marine regression of −41.8 m, the palaeotopography map shows a significant extension of land surface in the northern and eastern parts of the palaeoisland. As a palaeoclimatic indicator drought categories are used here, derived from the proportion between the number of dry and wet months according to monthly mean precipitation. Drought, i.e. the length of dry season, is the main driver of lowland vegetation distribution. Palaeotopography and paleoclimatic estimates were combined to develop a palaeovegetation map based on the topographic and climatic restrictions of modern vegetation units. In eastern Java, lowland monsoonal forests dominated the landscape at 1 Ma. These results provide for the first time a spatial sense of how topography and hydrology, rainfall patterns and vegetation units could have been distributed in the palaeolandscape of Sangiran Homo erectus.

Analysis of vertical differentiation of vegetation in Taishan World Heritage site based on cloud model

While the forests on Mount Taishan are predominantly man-made, there is a notable vertical variation in vegetation. This study employs the method of cloud model, quantifying uncertainty (fuzziness and randomness) of things. Utilizing digital elevation model (DEM) and vegetation distribution data, we constructed elevation cloud models for Mount Taishan’s deciduous broad-leaved, temperate coniferous, and mixed coniferous-broadleaved forests. Using three numerical features of the cloud model—Expectation (EX), Entropy (EN), and Hyper-entropy (HE)—we quantitatively analyzed the macro regularity and local heterogeneity of Mount Taishan’s forests vertical distribution from the perspective of uncertainty theory. The results indicate: (1) The EX of the core zone elevation of deciduous broad-leaved forest is 716.65 m, temperate coniferous forest is 1053.51 m, and mixed coniferous-broadleaved forest is 1384.09 m. The variation range of the core zone distribution height is smaller in the mixed coniferous-broadleaved forest (EN: 53.74 m) compared to deciduous broad-leaved forest (EN: 99.63 m) and temperate coniferous forest (EN: 121.70 m). (2) The fuzziness and randomness of the distribution height of the lower extension zones of deciduous broad-leaved forest and temperate coniferous forest (EN: 75.15 m, 184.56 m; HE: 24.09 m, 63.54 m) are greater than those of the upper extension zones (EN: 44.75 m, 42.49 m; HE: 14.48 m, 13.23 m). (3) The distribution fuzziness and randomness within temperate coniferous forests exceed those of deciduous broad-leaved forests. Within the core zones, the uncertainty regarding the vertical distribution of vegetation across different aspects remains consistent, which retains the characteristic of man-made forests. However, in transition areas, there is significant disparity, reflecting the adaptive relationship between vegetation and its environment to some extent. In the upper and lower extension zones of deciduous broad-leaved forests, the EX values for the vertical distribution height of mixed coniferous and broad-leaved forests differ significantly from those of deciduous broad-leaved forests (the difference is 22.82–39.15 m), yet closely resemble those of temperate coniferous forests (the difference is 4.79–7.94 m). This suggests a trend wherein deciduous broad-leaved tree species exhibit a proclivity to encroach upon coniferous forest habitats. The elevation cloud model of vertical vegetation zones provides a novel perspective and method for the detailed analysis of Mount Taishan’s vegetation vertical differentiation.

UAV-based modelling of vegetation recovery under extreme habitat stresses in the water level fluctuation zone of the Three Gorges Reservoir, China

Impoundment of the Three Gorges Reservoir on the upper Yangtze River has remarkably altered hydrological regime within the dammed reaches, triggering structural and functional changes of the riparian ecosystem. Up to date, how vegetation recovers in response to compound habitat stresses in the water level fluctuation zone remains inexplicitly understood. In this study, plant above-ground biomass (AGB) in a selected water level fluctuation zone was quantified to depict its spatial and temporal pattern using unmanned aerial vehicle (UAV)-derived multispectral images and screened empirical models. The contributions of multiple habitat stressors in governing vegetation recovery dynamics along the environmental gradient were further explored. Screened random forest models indicated relatively higher accuracy in AGB estimation, with R2 being 0.68, 0.79 and 0.62 during the sprouting, growth, and mature periods, respectively. AGB displayed a significant linear increasing trend along the elevational gradient during the sprouting and early growth period, while it showed an inverted U-shaped pattern during late growth and mature period. Flooding duration, magnitude and timing were found to exert greater negative effects on plant sprouting and biomass accumulation and acted as decisive factors in governing the elevation-dependent pattern of AGB. Localized spatial variations in AGB were modulated by other stressors such as sediment burial, soil erosion, soil moisture and nutrient content. Occurrence of episodic summer floods and vegetation distribution were responsible for an inverted U-shaped pattern of AGB during the late growth and mature period. Generally, AGB reached its peak in August, thereafter an obvious decline by an unprecedent dry-hot climatic event. The water level fluctuations with cumulative flooding effects exerted substantial control on AGB temporal dynamics, while climatic condition played a secondary role. Herein, further restorative efforts need to be directed to screening suitable species, maintaining favorable soil condition, and improving vegetation pattern to balance the many trade-offs.

Bioclimatic and remote sensing factors are better key indicators than local topography and soil: Vegetation composition variability in forests of Pakistan's Spin Ghar Mountain range

The composition, structure and distribution of vegetation are influenced by diverse environmental factors. Such research inquiries provide the initial data for future conservation and management efforts. The study area of North Waziristan district, Khyber Pakhtunkhwa, Pakistan comprises diverse forests of the Spin Ghar Mountain Range (at the border areas of Pakistan and Afghanistan), and a highly remote, mountainous, and unexplored region. There was little information on the complex relationships that existed between the study area's ambient environment and vegetation. This study hypothesized that the varying environmental complexity in the study area and vegetation variety may be significantly correlated, and the ranking of leading influencing factors might enhance our ecological understanding. A total of 61 study sites comprising 183 transects (50 m each) were randomly selected to record the vegetation-environment data from January-2018 to December-2020 (3 years). Monte Carlo permutation testing, hierarchical clustering of study samples, indicator species analysis, and ordination were applied to assess the sampling data. The results indicated that there were a total of 391 vascular plant species which were further classified into seven significantly different (p < 0.05) plant assemblages, each comprising of a distinct species makeup. A variety of different environmental variables (topographic (06), bioclimatic (19), edaphic (09), remote sensing, and anthropogenic predictors (16)) were considered. Simple term effects testing results depicted the significant (p(adj) < 0.05) role of 39 variables initially, whereas, conditional term effects testing (with variance inflation factor (VIF) threshold value of < 10, and forward selecting variables that provided the most unique information) results highlighted the prominent role of eight (08) contributors. The results of the latter analysis ranked the mean temperature of the warmest quarter (Bio10) as the most influencing factor, followed by Normalized Difference Vegetation Index (NDVI), longitude, continuous heat insulation load index (CHILI), precipitation of the warmest quarter (Bio18), global human modification of the terrestrial systems (gHM), organic carbon density (OCD), and annual precipitation (Bio12). This study concluded that the vegetation variability in the study area was significantly correlated with the prevailing environment, and considered bioclimatic and remote sensing factors were better key indicators for any vegetation distribution when the study was conducted on a large spatial scale. Based on these results, the anticipated future variations in climate, particularly global warming, lengthy drought spells, and population explosion might remarkably lead to decline in local plant species richness and distribution. For the study area to guard its priceless biodiversity for future generations, careful and prompt conservation and management planning are required.

Variation in Debris-Flow-Prone Areas with Ecosystem Stability: A Case Study of the Qipan Catchment in the Wenchuan Earthquake Region

The spatial distribution of vegetation in a basin has a far-reaching influence on the potential for sediment separation and transport capacity. However, many landslides induced by strong earthquakes have greatly changed the existing pattern, which further increases the probability of debris flow in a basin during heavy rainfall and has a significant impact on the stability of the basin. Thus, this study selected the debris flow basin in the Qipan catchment of the Wenchuan earthquake area as the research object. Multisource and high-precision remote sensing images were used to analyze the land use changes in the basin, and the index of connectivity (IC) was introduced to analyze the evolution of sediment transport capacity. An ecosystem stability assessment method suitable for post-earthquake debris flow basins was proposed. Through quantitative assessment of the ecosystem stability of the basin after the Wenchuan earthquake in 2008 and the two debris flow events after the earthquake, the dynamic relationship between the debris-flow-prone area and the ecosystem stability of the basin was revealed. The results showed that the stability of the ecosystem in the Qipan catchment increased annually, indicating a stable and substable state. The spatial distribution characteristics were lower in the north and south and greater in the middle. By comparing the evaluation results with the actual terrain change trend, the accuracy and feasibility of the evaluation method are verified. The results of this study provide a scientific basis for the formulation of regional disaster prevention strategies and help to accelerate the improvement of regional stability in debris-flow-prone areas.

Ecological disturbance effects of surface vegetation during coal mining in arid regions of Western China.

Coal mining in arid western regions is damaging the fragile ecology, causing problems such as surface damage, vegetation destruction, and soil erosion. These issues are obstacles to the development of green coal, as mining activities can disrupt the distribution of surface vegetation, leading to its spread outside the mining area and affecting surrounding areas. Based on Landsat data, the binary pixel model was used to calculate the vegetation coverage (FVC) in mining area from 2005 to 2021. Through vegetation coverage classification and regression trend analysis, the temporal and spatial changes and evolution trends of vegetation disturbance caused by coal mining and climate were analyzed. Correlation analysis revealed the range of ecological disturbance caused by coal mining at the coal mine scale and mining area scale. The results show that the vegetation coverage of the mining area showed a decreasing trend from 2005 to 2021. Winter and spring precipitation was the primary factor affecting vegetation growth in the area, while coal mining had indirect and secondary effects on vegetation. Human activities played a significant role in improving vegetation, and between 2015 and 2018, the area of vegetation improvement increased by 133.41% compared to that of 2009-2014. Compared to the reference area, the impact range of vegetation disturbance in the mining area is 2.5-5 km, while the impact range of vegetation disturbance in the coal mine is less than 500 m. Therefore, this study provides a theoretical basis for studying the impact of mining activities on vegetation and boundary identification.

Unveiling the landscape predictors of resilient vegetation in coastal wetlands to inform conservation in the face of climate extremes.

Unveiling spatial variation in vegetation resilience to climate extremes can inform effective conservation planning under climate change. Although many conservation efforts are implemented on landscape scales, they often remain blind to landscape variation in vegetation resilience. We explored the distribution of drought-resilient vegetation (i.e., vegetation that could withstand and quickly recover from drought) and its predictors across a heterogeneous coastal landscape under long-term wetland conversion, through a series of high-resolution satellite image interpretations, spatial analyses, and nonlinear modelling. We found that vegetation varied greatly in drought resilience across the coastal wetland landscape and that drought-resilient vegetation could be predicted with distances to coastline and tidal channel. Specifically, drought-resilient vegetation exhibited a nearly bimodal distribution and had a seaward optimum at ~2 km from coastline (corresponding to an inundation frequency of ~30%), a pattern particularly pronounced in areas further away from tidal channels. Furthermore, we found that areas with drought-resilient vegetation were more likely to be eliminated by wetland conversion. Even in protected areas where wetland conversion was slowed, drought-resilient vegetation was increasingly lost to wetland conversion at its landward optimum in combination with rapid plant invasions at its seaward optimum. Our study highlights that the distribution of drought-resilient vegetation can be predicted using landscape features but without incorporating this predictive understanding, conservation efforts may risk failing in the face of climate extremes.

Distribution of density and zoning patterns of mangrove forest in eastern coastal Sumatera, Indonesia

Indonesia has the largest mangrove forest in the world, touching 3.2 million hectares or the equivalent of 22.6% of the total mangrove forests, and the results of the updated national mangrove map in 2021 cover an area of 3,364,080 hectares. One of the mangrove ecosystems located in Wonosari Village, Panai Hilir District, Labuhanbatu Regency, focuses on analyzing each zone’s density distribution and formation. This study aims to analyze the density distribution of mangrove vegetation in 2002 and 2022 and the formation of mangrove vegetation. The method used in this research is NDVI analysis and IVI analysis by conducting vegetation analysis. The results obtained are the density of vegetation in 2002 and 2022, the highest density class value, namely density with an NDVI value range of 0.3 – 0.4 with an area of 415.61 ha in 2002 and 2022 with an area of 495.53 ha. The vegetation density class in 2002 and 2022, which experienced the greatest increase, was the vegetation density class covering an area of 79,92 ha, and the very dense vegetation density decreased by 111.80 ha. The mangrove vegetation formation is divided into three zones: the open zone found Rhizophora mucronata, Bruguiera parviflora, and Avicennia alba. In the middle zone found the species of Rhizophora mucronata and Bruguiera parviflora, and in the back zone, which is on the mainland, found the species of Xylocarpus granatum, Acrostichum aureum, Excoecaria agallocha.

Distribution and changes in mangrove area using satellite imagery of Landsat 8 OLI TIRS

Abstract This research aims to observe the distribution and changes in the area of mangrove vegetation in Jawai District, Sambas Regency, West Kalimantan Province. This sub-district is part of the administrative area of Sambas Regency and is one of 6 sub-districts that have coastal regions. The data used in this research is Landsat 8 satellite imagery, recording data from 2016 and 2022. The results of the data analysis show that of the total of 13 villages, only one village did not find mangrove vegetation in its area, namely Dungun Laut Village. Based on the analysis of the distribution of mangrove vegetation in 12 villages, there are two villages, namely Mutus Darussalam and Sarang Burung Danau, which show a decrease in the area of mangrove vegetation cover. Both experienced a reduction in the area of 0.184 ha and 42,081 ha, respectively. During 2016 and 2022, the lowest mangrove vegetation area was in Sentebang Village, 2,768 ha and 19,112 ha. The highest area of mangrove vegetation is increasing in Sarang Burung Kolam Village, with an area of 188,889 ha (2016) and 212,335 ha (2022). These findings show the importance of conservation in protecting the mangrove ecosystem in this area.

Analysing the influence of surface greening on soil conservation in China using satellite remote sensing

Global surface greening is very important to slow down regional warming, promote ecological balance and sustainable development, and China has made a significant contribution to this in the past 30 years, and effectively alleviated environmental problems such as land degradation, water shortage and air pollution by rapidly increasing vegetation coverage. Previous studies have shown that vegetation plays a positive role in alleviating soil erosion, but there is no quantitative description of runoff erosion and sediment transport under vegetation evolution with long time series and high resolution in China area. In this study, we use the RUSLE model and multi-source satellite remote sensing data to simulate overland soil erosion in China from 1990 to 2020 and analyze both the temporal and spatial variation of vegetation avoided erosion (VAE) and its correlation with multiple driving factors, such as Gross Primary Production (GPP). The results show that: 1)The distribution has increased by 12.89 % from 1990 to 2020, which is significant, and indicates that greening of the surface has significantly prevented soil and water loss;2)The spatial correlation strength of VAE-GPP in China is roughly in line with the division of the Hu Huanyong line (Hu-line), which is the result of the combined effect of vegetation distribution and human activities;3)The efficiency of VAE was significantly improved, especially the forest, accounting for about 76.50 % of the total, which was twice the sum of the other types. The research conclusion is of great significance to soil erosion prevention and control, soil ecological improvement, vegetation dynamic planning and regional sustainable development.

Life on gypsum: the vegetation of gypsum ecosystems in Cyprus

Gypsum ecosystems occur in arid and semi-arid areas, where evaporation is intense and annual precipitation is low and insufficient to leach the gypsum. They host sparse and scattered vegetation, composed of species specialized in this soil type. In Cyprus, gypsophilous vegetation is part of the priority habitat *1520 Iberian gypsum steppes (Gypsophiletalia) characterized by Campanula fastigiata, Gypsophila linearifolia, and Teucrium salaminium. Despite the ecological importance of gypsophilous vegetation, its distribution and ecology in Cyprus is still understudied. This study aimed to provide the first comprehensive account of the gypsum communities, focusing on the distribution of gypsophytes in relation to the substrate and the floristic composition of gypsum soils. Floristic inventory was carried out in 27 sites with gypsum soil. Biophysical information and data about human impact were also recorded. A total of 97 taxa were identified, including three gyspophile species, two gypsoclines, 20 gypsovags, and 72 waifs. A new endemic Rostraria hadjikyriakou was recorded in five locations. The known geographical distribution of gypsophilous vegetation has been updated. For 35% of the sites, gypsophilous vegetation was recorded for the first time while none of the characteristic gypsophilous species was found in the western part of the island.

Phenotypic plasticity variations in Phragmites australis under different plant–plant interactions influenced by salinity

Abstract Coastal wetland ecosystems are increasingly threatened by escalating salinity levels, subjecting plants to salinity stress coupled with interactions in the community. Abiotic factors can disrupt the balance between competition and facilitation among plant species. Investigating the effects of different neighboring species and trait plasticity could extend the stress gradient hypothesis and enhance understanding of vegetation distribution and diversity in salt marshes. We conducted a greenhouse experiment and investigated the plastic response of wetland grass Phragmites australis to seven neighboring plants of three functional types (conspecifics, graminoids and forbs) under soil salinity (0 and 10 g/L). Plant height, base diameter, density, leaf thickness, specific leaf area and total and part biomasses were measured. Additionally, the relative interaction index (based on biomass) and the relative distance plasticity index (RDPI) were calculated. Salinity significantly reduced the biomass, height, density and diameter of P. australis. The functional types of neighboring plants also significantly affected these growth parameters. The influence of graminoids on P. australis was negative under 0 g/L, but this negative effect shifted to positive facilitation under 10 g/L. The facilitation effect of forbs was amplified under salinity, both supporting the stress gradient hypothesis. The growth traits of P. australis had a plastic response to salinity and competition, such as increasing belowground biomass to obtain more water and resources. The RDPI was higher under salt conditions than in competitive conditions. The plant–plant interaction response to stress varies with plant functional types and trait plasticity.

Geographic analysis of the distribution of surface temperature, vegetation cover and its relationship with socioeconomic indicators – Cuiabá/MT

In Brazil and around the world, the problems resulting from urban planning, changes in land cover and the increase in urban infrastructure influence temperature change. The aim of this research is to understand the difference in temperature over the last 36 years (1985-2021) in the city of Cuiabá/MT, and its relationship with vegetation and socioeconomic and racial-ethnic factors. Annual images (36 images) from the Landsat 5 and 8 satellites between 1985 and 2021 were used, and Google Earth Engine was used to obtain this data for the urban area of the city of Cuiabá. Mapping of the spatial distribution of surface temperature, vegetation and changes in land use and cover was carried out using data from the MapBiomas project and socio-economic data from the Instituto Brasileiro de Geografia e Estatística (IBGE, Brazilian Institute of Geography and Statistics in English) 2010 census. The results indicated that over the last 36 years Cuiabá's surface temperature has increased by an average of 13°C, as part of the result of the growth of urban infrastructure and loss of vegetation cover, specifically in the peripheral areas. There is an inequality between the high-income population living in neighborhoods with milder temperatures and the low-income population living in neighborhoods with higher temperatures. In the temperature and skin color data, the white population generally lives in neighborhoods with milder temperatures, unlike the black population, which mostly suffers from high temperatures.

Projected distributions of Mongolian rangeland vegetation under future climate conditions

Abstract Mongolian herder households maintain the health and condition of their livestock by adapting to the characteristics of the local vegetation distribution. Thus, predicting future vegetation changes is important for stable livestock grazing and sustainable rangeland use. We predicted the distributional extent of rangeland vegetation, specifically desert steppe, steppe and meadow steppe communities, for the period 2081–2100, based on vegetation data obtained from a previous study. Rangeland vegetation data collected in Mongolia (43–50° N, 87–119° E) between 2012 and 2016 (278 plots) were classified into community types. Species distribution modeling was conducted using a maximum entropy (MaxEnt) model. Distribution data for desert steppe, steppe and meadow steppe communities were used as objective variables, and bioclimatic data obtained from WorldClim were used as explanatory variables. CMIP6-downscaled future climate projections provided by WorldClim were used for future prediction. The area under the curve values for the desert steppe, steppe and meadow steppe models were 0.850, 0.847 and 0.873, respectively. Suitable habitat was projected to shrink under all scenarios and for all communities with climate change. The extent of reduction in potential suitable areas was greatest for meadow steppe communities. Our results indicate that meadow steppe communities will transition to steppe communities with future climate change.

Assessing Seasonal and Inter-Annual Changes in the Total Cover of Submerged Aquatic Vegetation Using Sentinel-2 Imagery

Remote sensing is a valuable tool for surveying submerged aquatic vegetation (SAV) distribution patterns at extensive spatial and temporal scales. Only regular mapping over successive time periods (e.g., months, years) allows for a quantitative assessment of SAV loss or recolonization extent. Still, there are only a limited number of studies assessing temporal changes in SAV patterns. ESA Sentinel-2 (S2) has a high revisiting frequency permitting the multi-temporal assessment of SAV dynamics both seasonally and inter-annually. In the current study, a physics-based IDA (Image Data Analysis) model was used for the reconstruction of past SAV percent cover (%cover) patterns in the Baltic Sea coastal waters based on S2 archived images. First, we aimed at capturing and quantifying intra-annual spatiotemporal SAV dynamics happening during a growing season. Modeling results showed that significant changes took place in SAV %cover: the extent of low-cover (0–30% coverage) and intermediate-cover (30–70% coverage) areas decreased, while high-cover (70–100% coverage) areas increased during the growing period. Secondly, we also aimed at detecting SAV %cover spatiotemporal variations inter-annually (over the years 2016–2022). Inter-annual variability in %cover patterns was greater in the beginning of the vegetation period (May). The peak of the growing period (July/August) showed greater stability in the areal extent of the %cover classes.

Impacts of environmental and socioeconomic factors on gross ecosystem product of the Three Gorges reservoir area, China

AbstractEnvironmental and socioeconomic drivers would alter landscapes, bringing various effects with different directions and magnitudes. Demonstrating these driving effects is key to relieving the conflicts between territorial vegetation restoration and regional economic growth. However, the relationship between ecological protection and economic development due to landscape dynamics has not been systematically demonstrated as environment is difficult to quantify by the monetary value. In this article, we explored the changes in gross ecosystem product (GEP) in the Three Gorges (TG) reservoir area and constructed a conceptual framework to explicate its driving mechanism. Our results suggested that topographic, soil, and climatic factors positively impact on GEP through their important effects on vegetation structure, distribution, and succession. Additionally, reforestation policies promote the conversion of farmland and grassland to forestland in the TG reservoir region, which was the main contributor to enhancing GEP. Conversely, socioeconomic factors negatively impact GEP, of which effects were mainly manifested by changes in the proportion of ecological land. Therefore, it is essential to maintain a suitable land use proportion in this region to optimize GEP, and we proposed a landscape restoration program to enhance four ecosystem productions. This article provides a reference for land resource allocation for environmental protection and sustainable development in ecologically fragile areas.

Vegetation extraction in riparian zones based on UAV visible light images and marked watershed algorithm

The riparian zone is an area where land and water are intertwined, and vegetation is rich and complexly distributed. The zone can be directly involved in ecological regulation. In order to protect the ecological environment of the riparian zone, it is necessary to monitor the distribution of vegetation. However, there are many disturbing factors in extracting riparian vegetation, the most serious of which are water bodies with similar colours to the vegetation. To overcome the influence of water bodies on vegetation extraction from UAV imagery of riparian areas, this paper proposes a novel approach that combines the marked watershed algorithm with vegetation index recognition. First, the image is pre-segmented using edge detection, and the output is further refined with the marked watershed algorithm. Background areas are classified as potential regions for vegetation distribution. Subsequently, the final vegetation distribution is extracted from these potential vegetation areas using the vegetation index. The segmentation threshold for the vegetation index is automatically determined using the OTSU algorithm. The experimental results indicate that our method, when applied to UAV aerial imagery of the riparian zone, achieves an overall accuracy of over 94%, a user accuracy of over 97%, and a producer accuracy of over 93%.