RESUMEN

The coastal regions of India, particularly the Bay of Bengal, are highly vulnerable to the severe weather conditions induced by tropical cyclones. This study presents a comprehensive analysis of the changes in vegetation cover, shoreline dynamics, and meteorological variations resulting from Cyclone Michaung and subsequent post-monsoon events along the coastal zones of Andhra Pradesh and Tamil Nadu, India. A suite of vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Modified Vegetation Condition Index (mVCI), and Disaster Vegetation Damage Index (DVDI), were employed to assess changes in vegetation cover. The Digital Shoreline Assessment System (DSAS) was utilized to evaluate shoreline changes, and a range of meteorological variables were analyzed to assess the impacts of Cyclone Michaung and post-monsoon events. The findings reveal significant ecological impacts, with a notable decrease in Very Healthy Vegetation from 5.71% to 1.30%. The mean value of mVCI shifted from -0.2 to -0.16, indicating vegetation stress. DVDI analysis showed that 56.49% of the area experienced moderate damage, while 40.24% suffered severe vegetation damage. Additionally, erosion was observed along 79.46% of the shoreline transects in the study area. These insights are critical for assisting coastal managers in developing resilient coastal systems. Remarkably, a significant change in rainfall was recorded between the pre-cyclone period and the landfall day, with maximum rainfall intensifying from 13.93 mm/h on December 3rd to 164.26 mm/h on December 4th, and subsequently decreasing to 144.39 mm/h on December 5th.

RESUMEN

The arid region of northwest China (ARNC) is the most ecologically fragile region in China, and is characterized by harsh natural conditions, severe soil erosion, and poor soil fertility. Understanding long-term vegetation changes in this region is critical for effective environmental monitoring and climate change adaptation. Fractional vegetation coverage (FVC) is a key parameter for characterizing the ecological conditions of the ARNC. However, the reliance on low-resolution FVC and NDVI data due to the lack of medium-resolution data has limited our understanding of the environmental dynamics in this region. Therefore, this study addressed this gap by utilizing Landsat data to generate FVC data, enabling a detailed investigation of the spatial-temporal variations and driving factors of vegetation in the ARNC from 2000 to 2020. The results indicated the following: (1) The FVC was generally low, with an average of 0.191. The FVC was greater in the northwest and lower in the southeast in terms of spatial distribution features. The trend of FVC change in ARNC showed significant spatial variability, with degradation outweighing improvement. (2) The coefficient of variation of FVC was 0.377, indicating significant temporal fluctuations, with more stable conditions in the northwest than in the southeast. (3) The spatial differentiation of the FVC in ARNC was primarily driven by land cover types, evapotranspiration, and precipitation, with explanatory powers exceeding 30 % each. This study is significant because it provides a comprehensive understanding of vegetation dynamics in one of China's most vulnerable regions, offering critical insights for ecological restoration, desertification control, and sustainable development. The findings underscore the importance of targeted ecological governance to address the challenges posed by environmental degradation in the ARNC.

RESUMEN

Clarifying vegetation changes and the driving factors can provide references for ecological restoration and sustainable social development. We analyzed vegetation distribution and trend changes in Henan Province and its basin zoning (Haihe River basin zoning, Yellow River basin zoning, Huaihe River basin zoning, Yangtze River basin zoning), with fractional vegetation cover data from 2000 to 2020 based on the Google Earth Engine platform, and by combining Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index. We also utilized factor detection and factor interaction to explore the individual and mutual influences of natural and anthropogenic factors on vegetation at different scales. The results showed that the fractional vegetation cover (FVC) in Henan Province exhibited a distribution pattern of higher coverage in the south and lower in the north during the study period, predominantly characterized by moderate to high vegetation coverage. The Yangtze River basin zoning had the highest coverage. FVC in Henan Province and its zoning exhibited a consistent pattern of fluctuating upward trends, with all areas showing significant improvement. Particularly, the Yangtze River basin zoning had the largest area of improvement. According to the Hurst index, apart from the possibility of continued improvement in the Huaihe River basin zoning, other zoning would be likely to shift from improvement to degradation in the future. Vegetation changes in Henan Province and its zoning were the result of combined effects of anthropogenic and natural factors, with the influence of these factors changing over time and the dominant factors varying by region. Anthropogenic factors such as land use/cover type and nighttime lighting had a stronger impact on vegetation than natural factors like elevation, slope, and annual mean low temperature. The interaction between factors, particularly between anthropogenic and natural factors, exhibited a nonlinear enhancing pattern.

Asunto(s)

RESUMEN

Exploring the temporal and spatial dynamics of vegetation coverage in the Heilongjiang Basin and its response to climate change can provide a theoretical basis and data support for integrated basin management for three countries (Mongolia, China and Russia) in the region. We used MOD13Q1 remote sensing data from Google Earth Engine (GEE) platform between 2000 and 2020 to process the normalized vegetation index (NDVI) through the maximum value composites method, and calculated the vegetation coverage (FVC) using the dimidiate pixel model. The Sen+MK trend analysis method was employed to monitor the dynamics of FVC, while the Pearson correlation coefficient was utilized to quantify the responses of FVC to climate change. The results showed that the overall FVC in the Heilongjiang Basin exhibited a slight decreasing trend during 2000-2020, with an annual rate of 0.1%. The FVC in Mongolia showed a fluctuating increase trend (0.13%), while slight decrease trends were observed for Russia (0.15%) and China (0.08%). The FVC predominantly slightly degraded and severely degraded, accounting for 34% and 17% of the area, respectively, while the significantly improved area only accounted for 9%. The impact of precipitation on FVC in the study area was significantly greater than that of temperature. The proportion of areas where precipitation and temperature had a significant impact on FVC was 8.2% and 2.2%, respectively. The correlation coefficient between precipitation and FVC was the highest in Mongolia (r=0.446, P<0.05), and the lowest in Russian region (r=-0.442, P< 0.05).

Asunto(s)

RESUMEN

Introduction: As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. Methods: This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Results and discussion: Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

RESUMEN

ABSTRACTDrought presents a major challenge to the management of rocky desertification and ecological restoration in the delicate karst ecosystems of Guangxi. In this study, the normalized difference vegetation index (NDVI), fractional vegetation cover (FVC) and net primary productivity (NPP) were selected as vegetation remote sensing parameters, and the spatial response characteristics of different types of vegetation in karst areas of Guangxi Province to light, moderate, severe and extreme drought were analyzed to provide scientific basis for the evaluation of the impact of drought on vegetation in karst areas. The results are as follows: (1) NDVI, FVC and NPP showed a fluctuating increasing trend from 2000 to 2022, and the increasing rates were 0.058, 6.90%, and 43.3gC.m-2 per decade respectively. During this period, the number of light, moderate and severe drought days showed a decreasing trend, but the number of extreme drought days tended to increase. (2) The negative correlation of NDVI, FVC and NPP and drought increased from moderate to extreme drought, and from light to extreme drought, the negative correlation between NDVI and FVC and drought decreased, while that of NPP increased. (3) Light and moderate droughts had obvious negative impact on Chinese fir and broad-leaved forest, whereas severe and extreme droughts had obvious negative effect on eucalyptus and bamboo forest.

RESUMEN

Harvesting or degradation of forest ecosystems directly affects the microclimate, causing changes in air and soil temperatures and soil moisture in the forestlands. The objectives of this study were to investigate the effect of frequent clearcutting of forest cover on some selected soil properties, ambient and soil temperatures, soil moisture, and herbaceous vegetation cover and determine their recovery in a short period in the area subject to frequent clearcutting under the powerline corridors (PLCs). The study was conducted in the research forest of Istanbul University-Cerrahpasa, Faculty of Forestry. The treatment plots were selected from the clearcut area, and control plots were selected from an untouched oak-hornbeam forestland. Soil temperature and moisture and maximum and minimum ambient temperatures were measured in the treatment and control plots between 2020 and 2021 and topsoil sampled between 2019 and 2021. Data were analyzed using analysis of variance (ANOVA) to test the effects of clearcutting on some selected soil properties in the short term after cutting. Clearcutting caused a significant increase in soil bulk density (BD) and a decrease in the soil total porosity (TP), soil hydraulic conductivity (HC), and saturation capacity (SC). Forest cover removal significantly decreased the soil organic matter (SOM) content by 3%, increased average soil temperature by 2.1 °C, and the difference between maximum and minimum temperatures by 8.8 °C. Additionally, clearcutting reduced the average soil moisture from 36 to 35%. The findings revealed that clearcutting negatively affected some hydro-physical soil properties and soil microclimate conditions that may not recover to their previous states within the next few years.

Asunto(s)

RESUMEN

Human activities and climate change impact ecosystem services, thereby affecting economic and social sustainable development. Measuring the heterogeneity in space and time of how human activities affect ecosystem services poses a challenge for the sustainable management of land resources. Based on "human appropriation of net primary production (HANPP) - Fractional Vegetation Cover (FVC) - Soil Conservation Service (SCS)" cascading effect, first, a geographically and temporally weighted regression (GTWR) model was employed to assess the impact of HANPP in percent of potential NPP (hereafter HANPP%) on the FVC; second, changes in the FVC caused by human activities were quantified; and third, the potential soil conservation service (SCSp) and actual soil conservation service (SCSa) were estimated using the Revised Universal Soil Loss Equation (RUSLE) model, and the difference between them represented the changes in soil conservation service caused by human activities (SCSh). Taking the Qinghai-Tibet Plateau as a case study, we found that the GTWR model was well suited for analyzing the relationship between the HANPP% and the FVC (R2 = 0.897). The HANPP resulted in a decrease in the FVC from 0.222 in 2001 to 0.199 in 2019 and correspondingly resulted in a decrease in the ratio of SCSh to SCSp from 8.95% to 7.24%. This study provides a quantitative method that allows quantifying the influence of human activity on ecosystem services closely related to the FVC.

Asunto(s)

RESUMEN

Coastal dunes result from complex interactions between sand transport, topography and vegetation. However, uncertainty still persists due to limited quantitative analyses, integrating plant distribution and morphologic changes. This study aims to assess the initiation and maintenance of feedback processes by analysing the early development stages of incipient foredunes, combining data on the evolution of the plant cover and communities and dune morphology. Over three years, the monitoring of a newly formed dune (1 ha plot) reveals the progressive plant colonisation and the episodic accumulation of sand around vegetated areas controlled by sediment availability. Distinct colonisation rates were observed, influenced by inherited marine conditions, namely topography and presence of beach wrack. Berm-ridges provided elevations above the critical threshold for plant colonisation and surface roughness, aiding sediment accumulation. Beach wrack above this threshold led to rapid expansion and higher plant concentration. In the initial stages, vegetation cover significantly influenced sediment accumulation patterns, with higher accumulation around areas with high plant cover and low slopes or around areas with sparse vegetation but milder slopes. As the dune system matured and complexity grew, the link between vegetation cover and accumulation became nonlinear. Mid to low coverages (5-30 %) retained most of the observed accumulation, especially when coupled with steep slopes, resulting from positive feedbacks between vegetation, topography and sand transport. As foredune developed, vegetation cover and diversity increased while inherited morphologies grew vertically, explaining the emergence of dune ridge morphological types. Flat surfaces lacking wrack materials experienced a three-year delay in colonisation and sand accumulation, leading to the formation of terrace-type incipient foredunes. These observations underline feedback processes during the early stages of dune formation, with physical feedbacks primarily driving initiation and biophysical feedbacks prevailing in subsequent colonisation stages.

Asunto(s)

RESUMEN

Understanding the spatiotemporal variations and driving factors of regional vegetation coverage is crucial for developing scientific plans for ecological environment protection and maintaining regional ecological balance. Based on the Google Earth Engine (GEE) platform and using Landsat Collection 2 data, we investigated the spatiotemporal variation and driving factors of vegetation coverage in Shanxi Province, China, from 1990 to 2020, by employing methods such as pixel-based binary model, trend analysis, zonal statistics, and geodetector. The results showed that vegetation coverage in Shanxi Province showed a fluctuating upward trend from 1990 to 2020. Vegetation coverage in 44.4% of this region had been significantly improved, and the area with significant degradation accounted for 7.4%. Vegetation coverage in Shanxi Province was positively correlated with elevation, slope, and mountain terrain relief. The area proportion of vegetation coverage growth was the highest in the plateau and hilly regions. Factor detection results showed that land use type, landform type, annual average precipitation, and soil type were the main influencing factors of the spatial differentiation of vegetation coverage in Shanxi Province. Results of the interaction detection showed that the interaction between driving factors all showed enhancement. The interaction between natural factors showed a downward trend, while the interaction results of social factors showed an upward trend, reflecting that the impacts of human activities on vegetation coverage in Shanxi Province were gradually increasing.

Asunto(s)

RESUMEN

There is limited information regarding the influence of mangrove growth on the morphological evolution of intertidal mudflats. In this study, Tan Phu Dong district, Tien Giang Province, Vietnam, was selected for investigating how mangrove growth influenced the morphological evolution of an intertidal mudflat. The authors analyzed a series of satellite images (from 1995 and 2022), calculated the enhanced vegetation index (EVI), and documented field visits and observations in pursuit of the objective of the study. The findings revealed that fine-grained sediment accumulated as unconsolidated substratum (US) in the first step of the morphological evolution of the intertidal mudflat, with sediment accumulation of 910 ha in 1995. The US provided favorable conditions for mangroves to grow, while mangrove growth helped compact the US into a compact substratum (CS) in addition to promoting continuous sediment accumulation, increased the vegetation cover of the island, and elevated the substrate density of the remaining areas. As a result, the US and CS decreased steadily between 1995 and 2020, from 910 ha in 1995 to 401 ha in 2020 and from 433 ha in 2005 to 111 ha in 2020, respectively. Meanwhile, the low-vegetation area (LVA), medium-vegetation area (MVA), and high vegetation area (HVA) gradually increased between 1995 and 2015, from 0 ha in 1995 to 104 ha in 2015, from 0 ha in 1995 to 96 ha in 2015, and from 0 ha in 1995 to 114 ha in 2015, respectively. However, the LVA decreased slightly between 2015 and 2020 due to significant sand accumulation, which significantly killed the mangrove trees. In contrast, the MVA and HVA steadily increased between 2015 and 2020, from 96 ha in 2015 to 116 ha in 2020 and from 114 ha in 2015 to 221 ha in 2020, respectively. In 2022, there was a steady increase in HVA (298 ha in 2022), although the date of the 2022 satellite retrieval was 28 January 2022. This study recommends that the technical design of the existing coastal protection works should be revised or adapted to take account of sediment accumulation as the first step in the morphological evolution of the examined intertidal mudflat, rather than mangrove growth.

RESUMEN

Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000-2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

Asunto(s)

RESUMEN

Climate change has profoundly impacted Tibetan Plateau grasslands, necessitating a comprehensive analysis of the historical and future responses across diverse grassland types, with the integration of an elevated atmospheric CO2 concentration (eCO2) and climatic factors. In this study, the response of the Tibetan Plateau grassland was investigated, with a focus on the fractional vegetation cover (FVC). By employing an enhanced ecohydrological model for the baseline (1985-2014) and future (2031-2070) periods under shared socioeconomic pathway (SSP) scenarios, the responses of FVC to climate change were predicted across all grassland types. The alpine steppe exhibited the most rapid growth, with average FVC increases projected to reach 37 ± 7 %-81 ± 15 % for alpine meadow, 82 ± 22 %-185 ± 55 % for alpine steppe, and 50 ± 8 %-95 ± 23 % for temperate grassland by the 2060s. During the baseline, eCO2 primarily caused the FVC increases in alpine meadow and temperate grassland, while warming governed alpine steppe growth. Interannual variability in the FVC of alpine grasslands was temperature-driven, while that of the temperate grasslands was driven by precipitation. An increase in the FVC of the alpine steppe was caused by warming under both low- and high-emissions scenarios. For the alpine meadow and temperate grasslands, precipitation was dominant for FVC changes in the SSP1-2.6 scenario, and eCO2 was dominant in the SSP3-7.0 and SSP5-8.5 scenarios. These findings provide a vital foundation for grassland management, carbon cycling comprehension, and vegetation feedback estimations on the Tibetan Plateau.

RESUMEN

Exploring vegetation dynamics in arid areas and their responses to different natural and anthropogenic factors is critical for understanding ecosystems. Based on the monthly MOD13Q1 (250 m) remote sensing data from 2000 to 2019, this study analyzed spatio-temporal changes in vegetation cover in the Aksu River Basin and predicted future change trends using one-dimensional linear regression, the Mann-Kendall test, and the Hurst index. Quantitative assessment of the magnitude of anthropogenic and natural drivers was performed using the Geodetector model. Eleven natural and anthropogenic factors were quantified and analyzed within five time periods. The influence of the driving factors on the changes in the normalized difference vegetation index (NDVI) in each period was calculated and analyzed. Four main results were found. (1) The overall vegetation cover in the region significantly grew from 2000 to 2019. The vegetation cover changes were dominated by expected future improvements, with a Hurst index average of 0.45. (2) Land use type, soil moisture, surface temperature, and potential vapor dispersion were the main drivers of NDVI changes, with annual average q-values above 0.2. (3) The driving effect of two-factor interactions was significantly greater than that of single factors, especially land use type interacts with other factors to a greater extent on vegetation cover. (4) The magnitude of the interaction between soil moisture and potential vapor dispersion and the magnitude of the interaction between anthropogenic factors and other factors showed an obvious increasing trend. Current soil moisture and human activities had a positive influence on the growth of vegetation in the area. The findings of this study are important for ecological monitoring and security as well as land desertification control.

Asunto(s)

RESUMEN

Quantifying pollutant removal by stormwater wetlands requires intensive sampling which is cost-prohibitive for authorities responsible for a large number of wetlands. Wetland managers require simple indicators that provide a practical means of estimating performance and prioritising maintenance works across their asset base. We therefore aimed to develop vegetation cover and metrics derived from monitoring water level, as simple indicators of likely nutrient pollutant removal from stormwater wetlands. Over a two-year period, we measured vegetation cover and water levels at 17 wetlands and used both to predict nitrogen (N) and phosphorus (P) removal. Vegetation cover explained 48 % of variation in total nitrogen (TN) removal; with a linear relationship suggesting an approximate 9 % loss in TN removal per 10 % decrease in vegetation cover. Vegetation cover is therefore a useful indicator of TN removal. Further development of remotely-sensed data on vegetation configuration, species and condition will likely improve the accuracy of TN removal estimates. Total phosphorus (TP) removal was not predicted by vegetation cover, but was weakly related to the median water level which explained 25 % of variation TP removal. Despite weak prediction of TP removal, metrics derived from water level sensors identified faults such as excessive inflow and inefficient outflow, which in combination explained 50 % of the variation in the median water level. Monitoring water levels therefore has the potential to detect faults prior to loss of vegetation cover and therefore TN removal, as well as inform the corrective action required.

RESUMEN

The quantitative analysis of spatio-temporal variations of vegetation cover and its correlation with climate are of great significance for understanding of ecological environment, ecological civilization construction, and sustainable development in semi-arid areas. We investigated the spatio-temporal variations of normalized difference vegetation index (NDVI) and its response to climate change during 2000-2020 in Xilin Gol, Inner Mongolia, by using trend analysis, regression analysis and partial correlation analysis based on the data of MODIS-NDVI, tempe-rature, precipitation, digital elevation model. The results showed that vegetation cover in Xilin Gol had been increased from 2000 to 2020, which generally included three phases, i.e., stable fluctuation, rapid growth, and steady growth. The mean NDVI showed a zonal increasing distribution from southwest to northeast, and had a strong correlation with elevation and population density in Xilin Gol region. The high values of NDVI were mainly in the east, with a significant increasing trend, and the low values were in the southwest, with a local degradation. The sensitivity of vegetation cover to climate change showed spatial and temporal variations. The spatial variation of vegetation was more sensitive to temperature and the interannual variation was sensitive to annual precipitation. In summary, vegetation cover improved overall in Xilin Gol, but there was degradation in some areas. We should formulate differentiated and precise vegetation restoration and ecological environmental protection policies.

Asunto(s)

RESUMEN

Fractional vegetation cover (FVC) is a crucial indicator to estimate degradation and desertification for grasslands. However, traditional small-scale FVC analysis methods, such as visual estimation and point-sampling, are cumbersome and imprecise. Innovative methods like image-based FVC analysis methods, while accurate, face challenges such as complex analytical procedures and the necessary training for operations. Therefore, in this study, a combined application of ImageJ and Photoshop was employed to achieve a more effective analysis of FVC values in desertification areas. Our results showed that the FVC results obtained by combination of Photoshop and ImageJ were dependable and precise (R2 > 0.98), demonstrating equivalency to results obtained through either visual estimation or Photoshop-based methods. Furthermore, even in the face of background interference and varied shooting angles, the combination of ImageJ and Photoshop software was still able to maintain a low error rate when analyzing FVC values (average error rate = - 2.6%). In conclusion, the imaged-based combined FVC analysis method employed in our research was an effective, precise, and efficient technique for analyzing small-scale FVC, promising substantial improvement over conventional methods.

Asunto(s)

RESUMEN

Fractional vegetation cover (FVC) has changed significantly under various disturbances over northern China in recent decades. This research examines the dynamics of FVC and how it is affected by climate and human activity during the period of 1990-2018 in northern China. The effects of climate change (i.e., temperature, precipitation, solar radiation, and soil moisture) and human activity (socioeconomic data and land use) on vegetation coverage change in northern China from 1990 to 2018 were quantified using the Sen + Mann-Kendall test, partial correlation analysis, and structural equation modelling (SEM) methods. The findings of this research indicate the following: (1) From 1990 to 2018, the overall trend in FVC in northern China was increased. The areas with obvious increases were mainly situated on the northern slope of Tianshan Mountains, Xinjiang, the Loess Plateau, the Northeast China Plain, and the Sanjiang Plain, while the areas with distinct degradation were located in the Inner Mongolia Plateau, the Changbai Mountain and the eastern part of north China. (2) In the past 29 years, the FVC in northern China has been mainly affected by precipitation and soil moisture. (3) Based on structural equation modelling, we discovered that certain variables impacted the main factors influencing the amount of FVC in northern China. Human activity has had a larger impact on FVC than climate change. Our findings can accelerate the comprehension of vegetation dynamics and their underlying mechanisms and provide a theoretical basis for regional ecological environmental protection.

Asunto(s)

RESUMEN

Soil degradation in Middle Guinea is increasing over the years. While it's good to have precautions to deal with it, it's even more important to go back to the source of the scourge in order to lessen its effects over time, or even eradicate it. At the center of the factors that are often mentioned is the destruction of the vegetation cover, and the aim of this study is to clear it (in all its forms: trees, grass, savannah, etc.) by following its variation in time [1982 and 2021] and in space. The present study was conducted by combining the remote sensing and GIS results, developed with data from geotechnical survey data and laboratory tests. On the Mali Labé Linsan axis, between [1982 and 1992], 63 % of the territory explored was occupied by fresh vegetation cover, compared to 13 % of dry vegetation, as well as 12 % of sterile soil and 12 % of sand mineral soil. For the periods [1992-2002] and [2002-2012], these same parameters increased to: 67 %; 11 %; 11 % and 11 %. The period [2012-2021] was marked by changes of 73 %; 10 %; 9 % and 9 %, respectively. The bearing capacity of soils varies from one point to another. In all six boreholes presented, their maximum values are greater than or equal to 400 Kpa (≥400 Kpa). The minimum values calculated for 2.1 ≤ B(m)≤7.3 fluctuate between 291 Kpa and 806 Kpa. The investigations carried out on this subject show that the overall movement of the positive variation of the vegetation cover in time (63 % < 67 % < 73 %) and very contrasted in space, would not be responsible for the degradations (which are local and mainly caused by erosion: wind and water). In addition, they open up to a (geoscientific and geotechnical) approach of a deep analysis, the purpose of which suggests the adoption of slab/concrete/grating foundations (depth of anchorage specific to each soil analyzed).

RESUMEN

Terrestrial moisture recycling (TMR), characterized by a continuous process comprising green water flow (i.e., terrestrial evaporation), atmospheric transport, and terrestrial precipitation, functions as a nexus connecting hydrosphere, atmosphere, biosphere, and anthroposphere. During this process, land cover changes that impact green water flow can modify regional and remote precipitation patterns, potentially yielding far-reaching effects on water resources and human livelihoods. However, the comprehensive patterns of moisture recycling and transfer across eco-geographical regions in China, and their connection with various land cover types and vegetation transitions, remain insufficiently evaluated. This study employed an atmospheric moisture tracking model to quantify China's TMR pattern and evaluate the hydrological impacts of vegetation cover changes in China's ecosystems through TMR. The results demonstrate a significant moisture recycling ratio (52.4 %) and a considerable recycled volume (1.9 trillion m3/a) over China, characterized by pronounced moisture transfer from south to north and southwest to northeast. Among various land cover types, grasslands, croplands, and forests play pivotal supportive roles in China's TMR, contributing 738.8, 470.0, and 450.0 billion m3/a of precipitation in China, respectively. Moreover, the potential transition of vegetation between forest and cropland exerts the most significant and extensive impact on China's hydrological cycle. The conversion from forest to cropland leads to a total decrease of 44.7 billion m3/a in precipitation, whereas reforestation from cropland corresponds to a precipitation increase of 74.9 billion m3/a. This study provides a quantitative approach to comprehending the TMR pattern and its relationship with ecosystems, substantiating the significance of a comprehensive water management framework that considers the contribution of atmospheric moisture recycling and the impact of vegetation cover change.