Coupled effects of climate change and human activities on vegetation dynamics in the Southwestern Alpine Canyon Region of China

The driving effects of climate change and human activities on vegetation change have always been a focal point of research.However,the coupling mechanisms of these driving factors across different temporal and spatial scales remain controversial.The Southwestern Alpine Canyon Region of China(SACR),as an ecologically fragile area,is highly sensitive to the impacts of climate change and human activities.This study constructed a vegetation cover dataset for the SACR based on the Enhanced Vegetation Index(EVI)from 2000 to 2020.Spatial autocorrelation,Theil-Sen trend,and Mann-Kendall tests were used to analyze the spatiotemporal characteristics of vegetation cover changes.The main drivers of spatial heterogeneity in vegetation cover were identified using the optimal parameter geographic detector,and an improved residual analysis model was employed to quantify the relative contributions of climate change and human activities to interannual vegetation cover changes.The main findings are as follows:Spatially,vegetation cover exceeds 60%in most areas,especially in the southern part of the study area.However,the border area between Linzhi and Changdu exhibits lower vegetation cover.Climate factors are the primary drivers of spatial heterogeneity in vegetation cover,with temperature having the most significant influence,as indicated by its q-value,which far exceeds that of other factors.Additionally,the interaction q-value between the two factors significantly increases,showing a relationship of bivariate enhancement and nonlinear enhancement.In terms of temporal changes,vegetation cover shows an overall improving trend from 2000 to 2020,with significant increases observed in 68.93%of the study area.Among these,human activities are the main factors driving vegetation cover change,with a relative contribution rate of 41.31%,while climate change and residual factors contribute 35.66%and 23.53%,respectively.By thoroughly exploring the coupled mechanisms of vegetation change,this study provides important references for the sustainable management and conservation of the vegetation ecosystem in the SACR.

Quantitative contributions of climate change and human activities to vegetation dynamics in the Zoige Plateau from 2001 to 2020

Climate change and human activities such as overgrazing and rapid development of tourism simultaneously affected the vegetation of the Zoige Plateau.However,the spatiotemporal variations of vegetation and the relative contributions of climate change and human activities to these vegetation dynamics remain unclear.Therefore,clarifying how and why the vegetation on the Zoige Plateau changed can provide a scientific basis for the sustainable development of the region.Here,we investigate NDVI trends using the Normalized Difference Vegetation Index(NDVI)as an indicator of vegetation greenness and distinguish the relative effects of climate changes and human activities on vegetation changes by utilizing residual trend analysis and the Geodetector.We find a tendency of vegetation greening from 2001 to 2020,with significant greening accounting for 21.44%of the entire region.However,browning area expanded rapidly after 2011.Warmer temperatures are the primary driver of vegetation changes in the Zoige Plateau.Climatic variations and human activities were responsible for 65.57%and 34.43%of vegetation greening,and 39.14%and 60.86%of vegetation browning,respectively,with browning concentrated along the Yellow,Black and White Rivers.Compared to 2001-2010,the inhibitory effect of human activity and climate fluctuations on vegetation grew dramatically between 2011 and 2020.

Impacts of climate change and human activities on vegetation dynamics on the Mongolian Plateau, East Asia from 2000 to 2023

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world.Under the impacts of climate change and human activities,desertification is becoming increasingly severe on the Mongolian Plateau.Understanding the vegetation dynamics in this region can better characterize its ecological changes.In this study,based on Moderate Resolution Imaging Spectroradiometer(MODIS)images,we calculated the kernel normalized difference vegetation index(kNDVI)on the Mongolian Plateau from 2000 to 2023,and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test.We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis,and quantified the effects of climate change and human activities on kNDVI change by residual analysis.The results showed that kNDVI on the Mongolian Plateau was increasing overall,and the vegetation recovery area in the southern region was significantly larger than that in the northern region.About 50.99%of the plateau showed dominant climate-driven effects of temperature,precipitation,and wind speed on kNDVI change.Residual analysis showed that climate change and human activities together contributed to 94.79%of the areas with vegetation improvement.Appropriate human activities promoted the recovery of local vegetation,and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau.This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Typology and Agroecology of Agroecosystems in Vegetation Dynamics in the Ecotones of the Mbam and Inoubou

Agroforestry systems strongly characterize the Cameroonian agrarian landscape. Agroforests are among those structuring the ecotones of Mbam and Inoubou in the Central Cameroon region. Numerous works on agroecosystems of Central and South Cameroon, few have come out contribution of the structure of these traditional systems in the dynamics of the vegetation of these forest-savannah ecotones. The present contribution has the overall objective of demonstrating the structural efficiency of agroforests the dynamics of ecotone vegetation, but also in the conservation of biodiversity. To do this, a participatory analysis was carried out with 56 farmers distributed in the five villages of Makénéné. Botanical inventories supplemented socio-economic household surveys. The data collected was subjected to various analyzes (univariate test, analysis of variance, multivariate test, PCA, CAH). The results reveal that 55.2% of agroforests are less than 15 years old and those with an area greater than 1500 m2 predominate (33%). They are mainly young with generally small surface areas. The horizontal structure reveals that the largest diameter classes are those of [20 - 30 cm[ and [10 - 20 cm[ with a very low rate of basal area. Agroforests with trees over 10 m high are dominant in five villages of Makénéné. Two types of structural profiles characterize the agroforestry flora of the area, namely intensive pluristratified home gardens on savannah and intensive pluristratified agroforests under forest-savannah transition vegetation. Principal Component Analysis (PCA) and Ascending Hierarchical Clustering (HAC) show three Agroforest Clusters each. The PCA distribution reveals that woody biomass (Y) is strongly correlated with tree diameter (DBH) and significantly with height (Cluster 2). The age (AAG) (Cluster 1) of these agroforests, on the other hand, remains independent of the density (DST) of these trees (Cluster 3). The agroforests in the Nyokon, Carrière and Mocksud villages are the most effective in terms of conserving woody diversity while the agroforests of the Kinding ndé and Nyokon villages are more efficient in the reforestation processes. These results could be considered as effective and quantifiable tools for the certification of numerous cash crops such as cocoa and coffee, which will make it possible to valorize this local knowledge in terms of scientific and in the development of various programs and writing of technical notes.

Analysis and prediction of global vegetation dynamics:past variations and future perspectives

Spatiotemporal dynamic vegetation changes affect global climate change,energy balances and the hydrological cycle.Predicting these dynamics over a long time series is important for the study and analysis of global environmental change.Based on leaf area index(LAI),climate,and radiation flux data of past and future scenarios,this study looked at historical dynamic changes in global vegetation LAI,and proposed a coupled multiple linear regression and improved gray model(CMLRIGM)to predict future global LAI.The results show that CMLRIGM predictions are more accurate than results predicted by the multiple linear regression(MLR)model or the improved gray model(IGM)alone.This coupled model can effectively resolve the problem posed by the underestimation of annual average of global vegetation LAI predicted by MLR and the overestimate predicted by IGM.From 1981 to 2018,the annual average of LAI in most areas covered by global vegetation(71.4%)showed an increase with a growth rate of 0.0028 a-1;of this area,significant increases occurred in 34.42%of the total area.From 2016 to 2060,the CMLRIGM model has predicted that the annual average global vegetation LAI will increase,accounting for approximately 68.5%of the global vegetation coverage,with a growth rate of 0.004 a-1.The growth rate will increase in the future scenario,and it may be related to the driving factors of the high emission scenario used in this study.This research may provide a basis for simulating spatiotemporal dynamic changes in global vegetation conditions over a long time series.

Recent Vegetation Cover Dynamics and Climatic Parameters Evolution Study in the Great Green Wall of Senegal

The drought recorded in 1970s and 1980s, particularly in the Sahara and Sahel region has greatly affected the population as well as the economies and the eco-systems of this area. In 2007, the African Union launched a Pan-African program, the Great Green Wall for the Sahara, the Sahel Initiative (GGWSSI) to reverse land degradation and desertification by planting a wall of trees stretching from Dakar to Djibouti. The objective is to improve food security, and support local people to adapt to climate change. This paper aims to evaluate the impacts of the reforestation program in Senegal, fifteen years after it was launched. This study uses a time series of satellite-derived vegetation cover and climatic parameters data to analyze the sustainability of these interventions. Change detection approaches were applied to identify and characterize the drives of the eventual changes. A comparative analysis of reforestation on climatic parameters was explored through the temporal analysis of the vegetation index over the periods 2000-2008 and 2009-2020. An increase in vegetation activity was noted through the NDVI at the interannual (+2% to +8%) and seasonal (+1.5% to 7% for the wet season and 1% to 4% for the dry season) scale and a positive and significant evolution is noted on the trace of the GGW. Also, the period 2009-2020 recorded an increase in rainfall of 2% to 8% of the average value 2000-2020 and 4% to 8% of the rainy season. Soil moisture is the climatic parameter that has increased the most, with an increase of 25% to 54% of the 2000-2020 average, i.e. between 20 mm and 70 mm more. This study shows a significant improvement in the relationship between NDVI and climate parameters after the different reforestation actions of the GGW.

Community structure and species diversity dynamics of a subtropical evergreen broad-leaved forest in China:2005 to 2020

Here,we characterize the temporal and spatial dynamics of forest community structure and species diversity in a subtropical evergreen broad-leaved forest in China.We found that community structure in this forest changed over a 15-year period.Specifically,renewal and death of common species was large,with the renewal of individuals mainly concentrated within a few populations,especially those of Aidia canthioides and Cryptocarya concinna.The numbers of individual deaths for common species were concentrated in the small and mid-diameter level.The spatial distribution of community species diversity fluctuated in each monitoring period,showing a more dispersed diversity after the 15-year study period,and the coefficient of variation on quadrats increased.In 2010,the death and renewal of the community and the spatial variation of species diversity were different compared to other survey years.Extreme weather may have affected species regeneration and community stability in our subtropical monsoon evergreen broad-leaved forests.Our findings suggest that strengthening the monitoring and management of the forest community will help better understand the long-and short-term causes of dynamic fluctuations of community structure and species diversity,and reveal the factors that drive changes in community structure.

The impact of demographic dynamics on food consumption and its environmental outcomes:Evidence from China

With increasing population and changing demographics,food consumption has experienced a significant transition in quantity and quality.However,a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics,particularly in emerging economies like China.Using the two-stage Quadratic Almost Demand System(QUAIDS)model,this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China.Under various scenarios,according to changes in demographics,we extend our analysis to project the long-term trend of food consumption and its environmental impacts,including greenhouse gas(GHG)emissions,water footprint(WF),and land appropriation(LA).The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry,egg,and aquatic products,particularly for urban residents.Moreover,an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products.Correspondingly,in the current scenario of an increased aging population and sex ratio,it is anticipated that GHG emissions,WF,and LA are likely to decrease by 1.37,2.52,and 3.56%,respectively.More importantly,in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022,GHG emissions,WF,and LA in urban areas would increase by 12.78,20.94,and 18.32%,respectively.Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption.

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

Analysis of CH_(4) and H_(2) Adsorption on Heterogeneous Shale Surfaces Using aMolecular Dynamics Approach

Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand multiplicity.Moreover,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive capacity.In thisstudy,the adsorption of adsorbates,methane(CH_(4)),and hydrogen(H_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical technique.The results show that these behaviors are influenced by pressure and potentialenergy.On increasing the pressure from 500 to 2000 psi,the sorption effect for CH_(4)significantly increasesbut shows a decline at a certain stage(if compared to H_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb CH_(4)compared to hydrogen.However,in shale,this difference is negligible.

Millisecond dynamics of colloidal suspension studied by X-ray photon correlation spectroscopy at the Shanghai Synchrotron Radiation Facility

X-ray photon correlation spectroscopy(XPCS)has emerged as a powerful tool for probing the nanoscale dynamics of soft condensed matter and strongly correlated materials owing to its high spatial resolution and penetration capabilities.This technique requires high brilliance and beam coherence,which are not directly available at modern synchrotron beamlines in China.To facilitate future XPCS experiments,we modified the optical setup of the newly commissioned BL10U1 USAXS beamline at the Shanghai Synchrotron Radiation Facility(SSRF).Subsequently,we performed XPCS measurements on silica suspensions in glycerol,which were opaque owing to their high concentrations.Images were collected using a high frame rate area detector.A comprehensive analysis was performed,yielding correlation functions and several key dynamic parameters.All the results were consistent with the theory of Brownian motion and demonstrated the feasibility of XPCS at SSRF.Finally,by carefully optimizing the setup and analyzing the algorithms,we achieved a time resolution of 2 ms,which enabled the characterization of millisecond dynamics in opaque systems.

Dynamics and genetic regulation of macronutrient concentrations during grain development in maize

Nitrogen(N), phosphorus(P), and potassium(K) are essential macronutrients that are crucial not only for maize growth and development, but also for crop yield and quality. The genetic basis of macronutrient dynamics and accumulation during grain filling in maize remains largely unknown. In this study, we evaluated grain N, P, and K concentrations in 206 recombinant inbred lines generated from a cross of DH1M and T877 at six time points after pollination. We then calculated conditional phenotypic values at different time intervals to explore the dynamic characteristics of the N, P, and K concentrations. Abundant phenotypic variations were observed in the concentrations and net changes of these nutrients. Unconditional quantitative trait locus(QTL) mapping revealed 41 non-redundant QTLs, including 17, 16, and 14 for the N, P, and K concentrations, respectively. Conditional QTL mapping uncovered 39 non-redundant QTLs related to net changes in the N, P, and K concentrations. By combining QTL, gene expression, co-expression analysis, and comparative genomic data, we identified 44, 36, and 44 candidate genes for the N, P, and K concentrations, respectively, including GRMZM2G371058 encoding a Doftype zinc finger DNA-binding family protein, which was associated with the N concentration, and GRMZM2G113967encoding a CBL-interacting protein kinase, which was related to the K concentration. The results deepen our understanding of the genetic factors controlling N, P, and K accumulation during maize grain development and provide valuable genes for the genetic improvement of nutrient concentrations in maize.

Numerical study of submerged bending vegetation under unidirectional flow

Submerged vegetation commonly grows and plays a vital role in aquatic ecosystems,but it is also regarded as a barrier to the passing flow.Numerical simulations of flow through and over submerged vegetation were carried out to investigate the effect of vegetation density on flow field.Numerical simulations were computationally set up to replicate flume experiments,in which vegetation was mimicked with flexible plastic strips.The fluid-structure interaction between flow and flexible vegetation was solved by coupling the two modules of the COMSOL packages.Two cases with different vegetation densities were simulated,and the results were successfully validated against the experimental data.The contours of the simulated time-averaged streamwise velocity and Reynolds stress were extracted to highlight the differences in mean and turbulent flow statistics.The turbulence intensity was found to be more sensitive to vegetation density than the time-averaged velocity.The developing length increased with the spacing between plants.The snapshots of the bending vegetation under instantaneous velocity and vorticity revealed that flexible vegetation responded to the effects of eddies in the shear layer by swaying periodically.The first two rows of vegetation suffered stronger approaching flow and were prone to more streamlined postures.In addition,the origin of tip vortices was investigated via the distribution of vorticity.The results reveal the variation of flow properties with bending submerged vegetation and provide useful reference for optimizationofrestorationprojects.

Inflammatory markers,oxidative stress,and mitochondrial dynamics:Repercussions on coronary artery disease in diabetes

Inflammatory markers and mediators that affect the development of cardiovascular diseases have been the focus of recent scientific work.Thus,the purpose of this editorial is to promote a critical debate about the article titled“Nε-carboxymethyl-lysine and inflammatory cytokines,markers,and mediators of coronary artery disease progression in diabetes”,published in the World Journal of Diabetes in 2024.This work directs us to reflect on the role of advanced glycation end products,which are pro-inflammatory products arising from the metabolism of fatty acids and sugars whose main marker in tissues is Nε-carboxymethyllysine(NML).Recent studies have linked high levels of pro-inflammatory agents with the development of coronary artery disease(CAD),especially tumor necrosis factor alpha,interleukins,and C-reactive protein.These inflammatory agents increase the production of reactive oxygen species(ROS),of which people with diabetes are known to have an increased production.The increase in ROS promotes lipid peroxidation,which causes damage to myocytes,promoting myocardial damage.Furthermore,oxidative stress induces the binding of NML to its receptor RAGE,which in turn activates the nuclear factor-kB,and consequently,inflammatory cytokines.These inflammatory cytokines induce endothelial dysfunction,with increased expression of adhesion molecules,changes in endothelial permeability and changes in the expression of nitric oxide.In this sense,the therapeutic use of monoclonal antibodies(inflammatory reducers such as statins and sodium-glucose transport inhibitors)has demonstrated positive results in the regression of atherogenic plaques and consequently CAD.On the other hand,many studies have demonstrated a relationship between mitochondrial dynamics,diabetes,and cardiovascular diseases.This link occurs since ROS have their origin in the imbalance in glucose metabolism that occurs in the mitochondrial matrix,and this imbalance can have its origin in inadequate diet as well as some pathologies.Photobiomodulation(PBM)has recently been considered a possible therapeutic agent for cardiovascular diseases due to its effects on mitochondrial dynamics and oxidative stress.In this sense,therapies such as PBM that act on pro-inflammatory mediators and mitochondrial modulation could benefit those with cardiovascular diseases.

A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

Feature extraction and analysis of reclaimed vegetation in ecological restoration area of abandoned mines based on hyperspectral remote sensing images

The vegetation growth status largely represents the ecosystem function and environmental quality.Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information.In this study,the abandoned mining area in the Helan Mountains,China was taken as the study area.Based on hyperspectral remote sensing images of Zhuhai No.1 hyperspectral satellite,we used the pixel dichotomy model,which was constructed using the normalized difference vegetation index(NDVI),to estimate the vegetation coverage of the study area,and evaluated the vegetation growth status by five vegetation indices(NDVI,ratio vegetation index(RVI),photochemical vegetation index(PVI),red-green ratio index(RGI),and anthocyanin reflectance index 1(ARI1)).According to the results,the reclaimed vegetation growth status in the study area can be divided into four levels(unhealthy,low healthy,healthy,and very healthy).The overall vegetation growth status in the study area was generally at low healthy level,indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes.Furthermore,the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated,indicating that the original mining activities have had a large effect on vegetation ecology.After ecological restoration of abandoned mines,the vegetation coverage in the study area has increased to a certain extent,but the amplitude was not large.The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part,due to abandoned mines mainly concentrating in the northern part of the Helan Mountains.The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation,accurately analyze the plant growth status,and provide technical support for vegetation health evaluation.

Modelling analysis embodies drastic transition among global potential natural vegetations in face of changing climate

Potential natural vegetation(PNV)is a valuable reference for ecosystem renovation and has garnered increasing attention worldwide.However,there is limited knowledge on the spatio-temporal distributions,transitional processes,and underlying mechanisms of global natural vegetation,particularly in the case of ongoing climate warming.In this study,we visualize the spatio-temporal pattern and inter-transition procedure of global PNV,analyse the shifting distances and directions of global PNV under the influence of climatic disturbance,and explore the mechanisms of global PNV in response to temperature and precipitation fluctuations.To achieve this,we utilize meteorological data,mainly temperature and precipitation,from six phases:the Last Inter-Glacial(LIG),the Last Glacial Maximum(LGM),the Mid Holocene(MH),the Present Day(PD),2030(20212040)and 2090(2081–2100),and employ a widely-accepted comprehensive and sequential classification sy–stem(CSCS)for global PNV classification.We find that the spatial patterns of five PNV groups(forest,shrubland,savanna,grassland and tundra)generally align with their respective ecotopes,although their distributions have shifted due to fluctuating temperature and precipitation.Notably,we observe an unexpected transition between tundra and savanna despite their geographical distance.The shifts in distance and direction of five PNV groups are mainly driven by temperature and precipitation,although there is heterogeneity among these shifts for each group.Indeed,the heterogeneity observed among different global PNV groups suggests that they may possess varying capacities to adjust to and withstand the impacts of changing climate.The spatio-temporal distributions,mutual transitions and shift tendencies of global PNV and its underlying mechanism in face of changing climate,as revealed in this study,can significantly contribute to the development of strategies for mitigating warming and promoting re-vegetation in degraded regions worldwide.

Taxonomic Study of Five Parasitic Polypores of the Hymenochaetaceae Family of TIN Vegetation in Western Burkina Faso

The aim of this work is to inventory and study the lignicolous parasitic macrofungi of the Tin plant formation. The mycological outings from July to September 2018 and 2019, collected forty-four (44) basidiomes through a random sampling device over an area of 40,000 m2 including 1000 m long by 40 m2 wide. The standard methods and techniques used in mycology for taxonomic studies were used to describe and classify the carpophores collected in three families: Hymenochaetaceae, Ganodermataceae and Polyporaceae, into eight genera: Onnia (4.55%), Amauroderma (4.55%), Ganoderma (20.45%), Phellinus (52.27%), Inonotus (4.55%), Phellinopsis (6.82%), Grammothele (2.27%) and Trametes (4.55%). The genera Phellinus and Ganoderma were the most abundant. Finally, eight species were identified: Inonotus cf. ochroporus, Inonotus cf. pachyphloeus, Phellinus cf. cryptarum, Phellinus cf. hartigii, Phellinus cf. hippophaecola;Phellinus cf. robustus, Phellinus cf. igniarius, et Amauroderma cf. fasciculatum. Seven fungal species belong to the family Hymenochaetaceae and only the species Amauroderma cf. fasciculatum is a Ganodermataceae. However, all these fungal species are shown to be parasites of trunks and/or branches of the following woody: Parkia biglobosa (50%), Anogeissus leiocarpus (25%), Annona senegalensis (12.5%) and Mangifera indica (12.5%). Authors attest that the presence of phytoparasitic polypores in a plant formation is an indicator of aging hence the urgency to put in place the appropriate measures to safeguard and restore Tin’s plant formation.

Response of vegetation variation to climate change and human activities in the Shiyang River Basin of China during 2001-2022

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment,and maintaining ecosystem stability.Here,we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature(SVT)and the sensitivity of vegetation to precipitation(SVP)in the Shiyang River Basin(SYRB)of China during 2001-2022.The climate data from climatic research unit(CRU),vegetation index data from Moderate Resolution Imaging Spectroradiometer(MODIS),and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices,climate,and land use in the SYRB and its sub-basins(i.e.,upstream,midstream,and downstream basins)during 2001-2022.Linear regression analysis and correlation analysis were used to explore the SVT and SVP,revealing the driving factors of vegetation variation.Significant increasing trends(P<0.05)were detected for the enhanced vegetation index(EVI)and normalized difference vegetation index(NDVI)in the SYRB during 2001-2022,with most regions(84%)experiencing significant variation in vegetation,and land use change was determined as the dominant factor of vegetation variation.Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022.There were spatial differences in vegetation variation,SVT,and SVP.Although NDVI and EVI exhibited increasing trends in the upstream,midstream,and downstream basins,the change slope in the downstream basin was lower than those in the upstream and midstream basins,the SVT in the upstream basin was higher than those in the midstream and downstream basins,and the SVP in the downstream basin was lower than those in the upstream and midstream basins.Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities(land use change)dominated vegetation variation in the downstream basin.We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB.These findings can enhance our understanding of the relationship among vegetation variation,climate change,and human activities,and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

Impact of climate and human activity on NDVI of various vegetation types in the Three-River Source Region, China

The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.