Vegetation Diversity Research Articles

Effects of Habitat Loss on Tenebrionidae in Gravel–Sand Mulching Areas of Desert Steppe in Ningxia, China

The desert steppe in Ningxia is the largest natural steppe type in the region, characterized by a fragile ecological environment and low carrying capacity. Gravel–sand mulching, a local agricultural practice, involves using a sand and gravel covering layer to maintain soil warmth and moisture. However, this method has led to ecological problems, such as habitat loss and biodiversity loss. Tenebrionidae, one of the most widely distributed beetle families, is commonly used to indicate habitat degradation and is a significant steppe pest in desert steppe areas. This study, conducted in the gravel–sand mulching areas of Shapotou District, Zhongwei City, Ningxia, classified the habitat loss from low to high in these areas into five grades (I-V) and examined the effects of habitat loss on Tenebrionidae. We collected 6565 Tenebrionidae, with Blaps femoralis, Anatolica nureti, and Pterocoma vittata being the dominant species. The findings reveal that habitat loss grade I had the highest abundance, diversity index, and evenness index of Tenebrionidae, significantly higher than those of grades II–IV. Habitat loss had a significant negative effect on Tenebrionidae abundance, a significant positive effect on the richness index, no significant effect on the vegetation diversity index, a significant positive effect on soil available potassium (APP), and a significant negative effect on soil total phosphorus (TP). Redundancy analysis indicated a positive correlation between Tenebrionidae abundance and the vegetation diversity index; a negative correlation between Tenebrionidae richness, the diversity index, and vegetation indices; a positive correlation between Tenebrionidae abundance and soil TP; and a negative correlation between the Tenebrionidae diversity index and soil TP and soil APP. These findings will contribute to biodiversity conservation and ecological restoration and provide a theoretical basis for steppe management, sustainable agricultural development, and pest monitoring in desert steppe environments.

Distribution Patterns of Urban Spontaneous Vegetation Diversity and Their Response to Habitat Heterogeneity: A Case Study of Five Cities in Heilongjiang Province, China

Spontaneous vegetation is an important component of urban biodiversity and an excellent agent for exploring the mutual feedback mechanism between urbanization and urban ecosystems. Rapid urbanization has had a significant impact on the composition, structure, and distribution patterns of urban spontaneous vegetation diversity. Studying the diversity distribution patterns and causes of urban plant communities is beneficial for understanding the formation and maintenance mechanisms of plant diversity in specific urban habitats. This study selected five cities in different climate subregions of Heilongjiang Province as research targets and conducted field research using uniform sampling and typical sampling methods. The composition, distribution pattern, and driving factors of spontaneous vegetation were analyzed. The results showed the following: (1) A total of 633 examples of spontaneous vegetation were recorded, belonging to 93 families and 341 genera, mainly consisting of herbaceous plants and native plants. (2) The diversity index and similarity index of spontaneous vegetation in gravel-type abandoned land habitats are higher than those in other habitat types, while the diversity index of spontaneous vegetation in trees and shrubs is lower, and there is no significant difference in regards to different habitats. (3) Urban population density is a key factor affecting the diversity of native plants, while woody plant coverage, patch area, and landscape trait index are key factors affecting non-native plants. (4) The results of canonical correspondence analysis (CCA) showed that the total explanatory power of environmental characteristic factors in regards to the distribution pattern of spontaneous vegetation was 7.5%. The closest distance between adjacent patches, the coverage of woody plants in patches, the distance from the city edge, the patch area, and the surface impermeability of the buffer zones were key factors affecting the distribution of dominant species in spontaneous vegetation communities. The research results will provide an important reference for the conservation of urban biodiversity and the construction of low-maintenance urban green space plant landscapes in Heilongjiang Province.

Evaluasi Fungsi Ekologis Taman Kota pada Lanskap Riparian Sungai Cimanuk, Indramayu

The riparian landscape of the Cimanuk River has been declared a local protected area. Cimanuk Park is located on the northern coast of Java Island, Indramayu Regency which is one of the tourist centers and icons of the city of Indramayu. City parks are closely related to ecological functions that affect user comfort. This study aims to identify the diversity of vegetation, evaluate ecological functions, determine the perception of the people of Indramayu towards Cimanuk Park which is used as an icon of the city of Indramayu and provide recommendations for improving the green system of Cimanuk Park. The method of this research uses the study of aspects of ecological functions including microclimate measurement, and noise level measurement, which consists of preparation, inventory, analysis, assessment and evaluation, and preparation of recommendations. It has 17 species with a total of 333 individuals. This study conducted an assessment of vegetation diversity using the KPI method. Most of Cimanuk Parks have good categories in modifying temperature and controlling air humidity and have moderate categories in resisting wind, and reducing noise. Meanwhile, from the results of the study, the THI value was in the uncomfortable category.

Diversified Vegetation Cover Alleviates Microbial Resource Limitations within Soil Aggregates in Tailings.

Resource demand by soil microorganisms critically influences microbial metabolism and then influences ecosystem resilience and multifunctionality. The ecological remediation of abandoned tailings is a topic of broad interest, yet our understanding of microbial metabolic status in restored soils, particularly at the aggregate scale, remains limited. This study investigated microbial resources within soil aggregates from revegetated tailings and applied a vector model of ecoenzymatic stoichiometry to examine how different vegetation patterns (grassland, forest, or bare land control) impact microbial resource limitation. Five-year vegetation restoration significantly elevated carbon (C) and nitrogen (N) concentrations and their stoichiometric ratios in soil aggregates (approximately 2-fold), although these increases were not translated to in the microbial biomass and its stoichiometry. The activities of C- and phosphorus (P)-acquiring extracellular enzymes in these aggregates increased substantially postvegetation, with the most pronounced escalation in macroaggregates (>0.25 mm). The vector model results indicated soil microbial metabolism was colimited by C and P, most acutely in microaggregates (<0.25 mm). This colimitation was exacerbated by monotypic vegetation cover but mitigated under diversified vegetation cover. Soil nutrient stoichiometric ratios in vegetation restoration controlled microbial resource limitation, overshadowing the impact of heavy metals. Our findings underscore that optimizing resource allocation within soil aggregates through strategic revegetation can enhance microbial metabolism in tailings, which advocates for the implementation of diverse vegetation covers as a viable strategy to improve the ecological development of degraded landscapes.

Hidden Archaeological Remains in Heterogeneous Vegetation: A Crop Marks Study in Fortified Settlements of Northwestern Iberian Peninsula

This study evaluates the effectiveness of multispectral imaging via Unmanned Aerial Systems (UAS), in combination with advanced digital image processing techniques, for the detection and mapping of archaeological sites within diverse landscapes. The research focuses on six case studies located in the northwest of the Iberian Peninsula, a region marked by complex vegetation patterns and varying topography. The primary objective is to assess the potential of these non-invasive remote sensing techniques in identifying crop marks associated with buried structures from ancient, fortified settlements. By means of Principal Component Analysis (PCA) and vegetation indices, the study aims to pinpoint areas of interest that may indicate the presence of archaeological features, while effectively distinguishing them from modern disturbances or natural terrain variations. The research encountered several challenges, including seasonal variations in crop conditions and recent land-use changes. The methodology successfully identified distinct archaeological features. In some instances, natural vegetation variability, typically seen as an obstacle, enhanced the visibility of crop marks, aiding in the detection of underlying structures. These results offer a cost-effective and scalable option for preliminary archaeological surveys, particularly in refining survey methodologies and guiding future excavation efforts aimed at uncovering and preserving ancient, fortified settlements in the region.

Winter Grazing, Not Fencing or Unicast, Promotes Stability of Microbial Community and Function in the Qilian Mountains of Qinghai‐Xizang Plateau

ABSTRACTIn alpine meadows, microorganisms are essential to sustain the stability of terrestrial geochemical processes and vegetation–soil–microbial systems. The present study in order investigate how various management measures impact the microbial communities' composition and functionality, we utilize metagenomic sequencing techniques to examinate the composition and function of soil microbial communities in the southern Qilian Mountains of the Qinghai‐Xizang Plateau in response to the management practices of fencing enclose (FE), winter grazing (WG), transition zone between natural and artificial grasslands (TZ), and artificial unicast oats (AU). Vegetation diversity and soil physicochemical characteristics were dramatically altered by the management measures. The prokaryotic community structure was considerably similar in FE and WG, as well as in TZ and AU. Near‐natural (FE) and artificial establishment (AU) disturbances changed the fungal community structure. Enzymes related to carbon metabolism did not respond significantly to the management measures, whereas those related to nitrogen metabolism did not respond significantly in TZ and AU. The relative abundance of enzymes participating in nitrogen metabolism was higher under TZ and AU than under FE and WG. We concluded that grassland management measures altered the structure of aboveground graminoid and leguminous vegetation communities and belowground biomass allocation, resulting in changes in K uptake, causing striking changes in the structure of fungal communities and nitrogen‐metabolizing enzymes; moderate disturbance (WG) was beneficial for maintaining the stability of microbial communities in alpine grasslands.

Vegetation classification in the Neotropics – Novel insights from Latin America and the Caribbean

Our editorial introduces a Special Collection of scientific articles on current vegetation research in the most biodiverse of all biogeographic realms, the Neotropics. It contains nine scientific contributions dedicated to vegetation data, description and classification. Four research papers provide new vegetation classifications of important Neotropical biomes, namely the Arid Chaco in Argentina, Mexican temperate forests, and Andean wetlands in the Argentine Puna and southern Peru. Furthermore, one study provides a novel bioclimatic-vegetation classification approach applied to Mexican vegetation, while another proposes a new synthesis of the South American terrestrial biomes as geocomplexes. Finally, three vegetation databases are presented in the Special Collection: ArgVeg – Database of Central Argentina (GIVD ID: SA-AR-002), CACTUS – Vegetation database of the Dutch Caribbean Islands (GIVD ID: SA-00-004) and VegAndes: the vegetation database for the Latin American highlands (GIVD ID: SA-00-005). The Special Collection provides fundamental data and tools to better understand the diversity and complexity of Neotropical vegetation. Abbreviations: GIVD = Global Index of Vegetation-Plot Databases, IAVS = International Association for Vegetation Science, IAVS-LACS = IAVS Regional Section for the Latin America and the Caribbean, VCS = Vegetation Classification and Survey

NDVI or PPI: A (Quick) Comparison for Vegetation Dynamics Monitoring in Mountainous Area

Cold ecosystems are experiencing a warming rate that is twice as fast as the global average and are particularly vulnerable to the consequences of climate change. In mountain ecosystems, it is particularly important to monitor vegetation to understand ecosystem dynamics, biodiversity conservation, and the resilience of these fragile ecosystems to global change. Hence, we used satellite data acquired by Sentinel-2 to perform a comparative assessment of the Normalized Difference Vegetation Index (NDVI) and the Plant Phenology Index (PPI) in mountainous regions (canton of Valais-Switzerland in the European Alps) for monitoring vegetation dynamics of four types: deciduous trees, coniferous trees, grasslands, and shrublands. Results indicate that the NDVI is particularly noisy in the seasonal cycle at the beginning/end of the snow season and for coniferous trees, which is consistent with its known snow sensitivity issue and difficulties in retrieving signal variation in dense and evergreen vegetation. The PPI seems to deal with these problems but tends to overestimate peak values, which could be attributed to its logarithmic formula and derived high sensitivity to variations in near-infrared (NIR) and red reflectance during the peak growing season. Concerning seasonal parameters retrieval, we find close concordance in the results for the start of season (SOS) and end of season (EOS) between indices, except for coniferous trees. Peak of season (POS) results exhibit important differences between the indices. Our findings suggest that PPI is a robust remote sensed index for vegetation monitoring in seasonal snow-covered and complex mountain environments.

Temporal Range Dynamics of the Lataste's Viper (Vipera latastei Boscá, 1878) in Doñana (Spain): Insights into Anthropogenically Driven Factors.

Doñana (southern Spain), a region of notable biodiversity richness, is highly threatened by ongoing landscape transformation and climate change. We investigated the local effect of these anthropogenic factors on the temporal range dynamics of Lataste's viper (Vipera latastei), an Iberian endemic Mediterranean reptile that has apparently become rare over the years in Doñana. Using ecological niche-based models, based on climatic and remote sensing variables, we analyzed historical (1959-1999) and contemporary (2000-2022) records of the species to assess range shifts and identify environmental factors that may influence them. Our results show that V. latastei is mostly restricted to the coastal region of Doñana and that one temperature variable is the most important factor explaining this distribution pattern in both periods. Additional climatic and vegetation variables play a role in its historical distribution, but they become less important in contemporary times, suggesting a niche simplification over time. We found 30.5% of reduction in the species suitable area from historical to contemporary conditions, a reduction that would be even greater (83.37%) in the absence of niche shift. These findings underscore the species' heightened vulnerability to ongoing environmental changes and highlight the urgent need for targeted conservation strategies.

Effects of Vegetable Cover on the Regeneration Process in Degraded Dry Forest in Brazil

ABSTRACTThe Brazilian Caatinga is among the most diverse dry forests in the world, yet half of its original coverage has been degraded. Natural regeneration is influenced by climatic and edaphic conditions, as well as the existing adult stratum. Despite its significance, this process remains poorly understood in the Caatinga. Thus, our study aimed to analyze how anthropogenic disturbance, vegetation cover, and soil properties affect the regenerating stratum under different levels of Caatinga vegetation cover. The research was conducted in the driest region of Brazil. The selected sites represent low (Area I) and high (Area II) normalized difference vegetation index. Six vegetable plots (50 × 20 m each) were delimited to study adult stratum, and four vegetable plots (10 × 10 m each) to regeneration stratum. Topsoil was sampled in all vegetable plots. Our results reveal interactions between soil characteristics and the adult and regenerating strata. Area II exhibited higher diversity and a greater number of exclusive species, while Area I was dominated by species more resistant to limiting conditions, such as Aspidosperma pyrifolium Mart. &amp; Zucc. The C and N content in the soil showed a positive and significant correlation with the diversity of the regenerating stratum. The data suggest that the area with less vegetation cover, richness, and diversity shows signs of desertification.

All Deforestation Matters: Deforestation Alert System for the Caatinga Biome in South America’s Tropical Dry Forest

This study provides a comprehensive overview of Phase I of the deforestation dryland alert system. It focuses on its operation and outcomes from 2020 to 2022 in the Caatinga biome, a unique Brazilian dryland ecosystem. The primary objectives were to analyze deforestation dynamics, identify areas with highest deforestation rates, and determine regions that require prioritization for anti-deforestation efforts and conservation actions. The research methodology involved utilizing remote sensing data, including Landsat imagery, processed through the Google Earth Engine platform. The data were analyzed using spectral unmixing, adjusted Normalized Difference Fraction Index, and harmonic time series models to generate monthly deforestation alerts. The findings reveal a significant increase in deforestation alerts and deforested areas over the study period, with a 148% rise in alerts from 2020 to 2022. The Caatinga biome was identified as the second highest in detected deforestation alerts in Brazil in 2022, accounting for 18.4% of total alerts. Hexagonal assessments illustrate diverse vegetation cover and alert distribution, enabling targeted conservation efforts. The Bivariate Choropleth Map demonstrates the nuanced relationship between alert and vegetation cover, guiding prioritization for deforestation control and native vegetation restoration. The analysis also highlighted the spatial heterogeneity of deforestation, with most deforestation events occurring in small patches, averaging 10.9 ha. The study concludes that while the dryland alert system (SAD-Caatinga—Phase I) has effectively detected deforestation, ongoing challenges such as cloud cover, seasonality, and more frequent and precise monitoring persist. The implementation of DDAS plays a critical role in sustainable forestry by enabling the prompt detection of deforestation, which supports targeted interventions, helps contain the process, and provides decision makers with early insights to distinguish between legal and illegal practices. These capabilities inform decision-making processes and promote sustainable forest management in dryland ecosystems. Future improvements, including using higher-resolution imagery and artificial intelligence for validation, are essential to detect smaller deforestation alerts, reduce manual efforts, and support sustainable dryland management in the Caatinga biome.

Research into the Influence Mechanisms of Visual-Comfort and Landscape Indicators of Urban Green Spaces

Urban green spaces play a crucial role in providing social services and enhancing residents’ mental health. It is essential for sustainable urban planning to explore the relationship between urban green spaces and human perceptions, particularly their visual comfort. However, most current research has analyzed green spaces using two-dimensional indicators (remote sensing), which often overlook human visual perceptions. This study combined two-dimensional and three-dimensional methods to evaluate urban green spaces. Additionally, the study employed machine learning to quantify residents’ visual comfort in green-space environments and explored the relationship between green spaces and human visual perceptions. The results indicated that Kitakyushu exhibited a moderate FCV and an extremely low Green View Index (GVI). Yahatanishi-ku was characterized as having the highest visual comfort. Tobata-ku demonstrated the lowest visual comfort. Natural, GVI, openness, enclosure, vegetation diversity, landscape diversity, and NDBI were positively correlated with visual comfort. FCV and ENVI were negatively correlated with visual comfort. Vegetation diversity had the most impact on improving visual comfort. By integrating remote sensing and street-view data, this study introduces a methodology to ensure a more holistic assessment of green spaces. Urban planners could use it to better identify areas with insufficient green space or areas that require improvement in terms of green-space quality. Meanwhile, it could be helpful in providing valuable input for formulating more effective green-space policies and improving overall urban environmental quality. The study provides a scientific foundation for urban planners to improve the planning and construction of healthy and sustainable cities.

Using UAV RGB Images for Assessing Tree Species Diversity in Elevation Gradient of Zao Mountains

Vegetation biodiversity in mountainous regions is controlled by altitudinal gradients and their corresponding microclimate. Higher temperatures, shorter snow cover periods, and high variability in the precipitation regime might lead to changes in vegetation distribution in mountains all over the world. In this study, we evaluate vegetation distribution along an altitudinal gradient (1334–1667 m.a.s.l.) in the Zao Mountains, northeastern Japan, by means of alpha diversity indices, including species richness, the Shannon index, and the Simpson index. In order to assess vegetation species and their characteristics along the mountain slope selected, fourteen 50 m × 50 m plots were selected at different altitudes and scanned with RGB cameras attached to Unmanned Aerial Vehicles (UAVs). Image analysis revealed the presence of 12 dominant tree and shrub species of which the number of individuals and heights were validated with fieldwork ground truth data. The results showed a significant variability in species richness along the altitudinal gradient. Species richness ranged from 7 to 11 out of a total of 12 species. Notably, species such as Fagus crenata, despite their low individual numbers, dominated the canopy area. In contrast, shrub species like Quercus crispula and Acer tschonoskii had high individual numbers but covered smaller canopy areas. Tree height correlated well with canopy areas, both representing tree size, which has a strong relationship with species diversity indices. Species such as F. crenata, Q. crispula, Cornus controversa, and others have an established range of altitudinal distribution. At high altitudes (1524–1653 m), the average shrubs’ height is less than 4 m, and the presence of Abies mariesii is negligible because of high mortality rates caused by a severe bark beetle attack. These results highlight the complex interactions between species abundance, canopy area, and altitude, providing valuable insights into vegetation distribution in mountainous regions. However, species diversity indices vary slightly and show some unusually low values without a clear pattern. Overall, these indices are higher at lower altitudes, peak at mid-elevations, and decrease at higher elevations in the study area. Vegetation diversity indices did not show a clear downward trend with altitude but depicted a vegetation composition at different altitudes as controlled by their surrounding environment. Finally, UAVs showed their significant potential for conducting large-scale vegetation surveys reliably and in a short time, with low costs and low manpower.

The combined nitrogen and phosphorus fertilizer application reduced soil multifunctionality in Qinghai-Tibet plateau grasslands, China

The impact of nitrogen (N) and phosphorus (P) fertilizer inputs on soil nutrient cycling and ecological function processes has garnered significant attention. Soil multifunctionality primarily refers to the soil's ability to perform multiple functions simultaneously, particularly the functions related to the genes involved in carbon (C), nitrogen (N), and phosphorus (P) cycles, which are critical for ecosystem sustainability. Despite this, the effects of N and P fertilizers on the expression of genes involved in soil carbon (C), nitrogen (N), and phosphorus (P) cycles, and their consequent influence on soil multifunctionality, remain unclear. To investigate this, we conducted a long-term nine-year experiment. The experimental site was fenced to prevent grazing and included four treatments: Control (no fertilizer), N (10 g N m−2 y−1, urea), P (5 g P m−2 y−1, Ca(H2PO4)2), and NP (10 g N and 5 g P m−2 y−1, urea and Ca(H2PO4)2). We examined the effects of these treatments on soil microbial functional gene abundance and multifunctionality. Our findings revealed that N addition altered the composition of soil microbial functional genes but did not affect functional diversity. Both N and P inputs, as well as their combination, negatively impacted soil carbon fixation and the genes encoding enzymes for the degradation of starch, hemicellulose, cellulose, and chitin. N input also disrupted soil nitrogen and phosphorus cycling by inhibiting the expression of soil denitrification genes (nirS and nosZ), phytate hydrolase gene (cphy), and a phosphatase gene (phoD). Additionally, P input significantly inhibited functional genes involved in soil nitrification, denitrification, ammonification, nitrogen fixation, and ammonia oxidation processes. It also adversely affected phytate synthesis and degradation. The combined N and P inputs had a substantial negative impact on soil nitrification (hao), denitrification (narG, nirK, nirS, and norZ), ammonification (gdh), nitrogen fixation, annamox, and nitrogen reduction, and inhibited the expression of soil phosphorus cycle genes. Long-term phosphorus application was found to have a more detrimental effect on soil multifunctionality compared to nitrogen application. Furthermore, our study showed that vegetation diversity and abundance are crucial drivers of soil carbon, nitrogen, and phosphorus cycling functional genes and multifunctionality. We concluded that N and P inputs alter soil multifunctionality by influencing vegetation diversity; therefore, maintaining vegetation diversity is essential for sustaining soil multifunctionality.

Identifying Factors Mediating the Carnivore Richness–Productivity Relationship Across a Precipitation‐Driven Ecotone

ABSTRACTAimPrimary productivity is an important mechanism influencing the species richness of animal taxa such as mammals. However, the factors that mediate the relationship between carnivore species richness, for example, and productivity are not well understood. We examined whether the relationship between carnivore species richness and primary productivity followed a hump‐shaped relationship and explored potential pathways by which productivity influences carnivore communities.LocationWestern Great Basin, USA.MethodsWe deployed a camera‐trap grid across a strong precipitation—and the corresponding productivity—gradient and estimated carnivore species richness using a novel application of a multisession community occupancy model. To quantify the relationship between carnivore species richness and productivity, we included the linear and quadratic effects of average annual precipitation as covariates on carnivore species richness. We fit additional community models linking carnivore species richness to vegetation and land cover variables to identify factors that mediate the relationship between carnivore richness and productivity.ResultsThe linear effect of precipitation on carnivore richness was positive and the quadratic effect was negative, supporting the hump‐shaped relationship where richness declines at the highest levels of productivity. Similarly, carnivore species richness followed a quadratic relationship with vegetation height along the productivity gradient. The relationship between carnivore species richness and proportion tree cover was positive, with limited evidence that open vegetation types in the surrounding landscape increased site‐level richness.Main ConclusionsIn addition to supporting the notion that primary productivity has a strong and nonlinear influence on local‐scale carnivore species richness, our results suggest that vegetation structure may be an important mediator of this relationship. Although future changes in precipitation and productivity due to climate change are uncertain, our results indicate that targeting areas of intermediate productivity and vegetation height, such as woodlands, may be key for conserving species‐rich carnivore communities along productivity gradients.

Flora and vegetation in the Lake Arbakalir and the spring Charsky Goryachy Klyuch (Charskaya Basin, Transbaikalia)

As a result of comprehensive researches in the Lake Arbakalir and the Spring Charsky Goryachi klyuch during the growing season in 2021, the physical and chemical parameters of water, species and phytocenotic diversity of vegetation were studied. 56 taxa from 7 divisions of which 31 species belong to flowering plants, 22 species to macroalgae, one species in each to bryophytes, horsetails and lycophytes were identified in the flora of water bodies. Two species are included in the Red Book, both at the federal and regional levels. Two species are classified as relict. The structure of the flora contains species of three ecotypes, of which 38 species (67.9 %) belong to true aquatic plants. 18 associations from 12 formations were identified in the syntaxonomic structure of aquatic and coastal aquatic vegetation. Based on factor analysis, the main factors influencing the distribution of phytocenoses are water temperature, pH, mineralization, and main cation, anion and nutrient contents.

Enhancing highland ecosystems in East Hararge, Ethiopia: evaluating intervention strategies for species diversity, soil organic carbon stock, and carbon sequestration

Forest loss and soil degradation pose significant challenges globally, particularly in developing nations like Ethiopia. Various intervention strategies have been implemented to rehabilitate degraded ecosystems. However, research gaps exist in understanding the most effective approaches, particularly in highland ecosystems. This study aimed to evaluate the effectiveness of different intervention strategies on species diversity and carbon stock in the West Hararghe zone, specifically at the Doba district Hades site. The data was collected from 5 February 2022 to 10 December 2022. The study area was characterized by systematic plots and transects to assess vegetation diversity and soil properties across four intervention categories: (physical; only soil and water conservation structures were used, enclosure; only animal and human interaction was restricted, biological; only different tree species were planted, biophysical; both soil water conservation and tree planting were used). Soil samples were collected at different depths, and biomass estimation was conducted using established formulas. Statistical analyses, including one-way ANOVA and post-hoc tests, were performed to test the level of significance. Biophysical interventions exhibited the highest species diversity index (SDI) (4.65 ± 1.21), followed by enclosure interventions (1.68 ± 0.58), while physical interventions recorded the lowest SDI (0.63 ± 0.18). Enclosure interventions led to the highest soil organic carbon (SOC) stocks at 40.13 t C ha−1, followed by biophysical interventions at 39.26 t C ha−1. Physical interventions resulted in the lowest SOC stocks at 23.9 t C ha−1, underscoring their potential for carbon sequestration. Biophysical interventions, which include both above-ground and below-ground biomass, showed significant carbon stock accumulation, totaling 173.8 t C ha−1 (39.26 t C ha−1 from SOC and 114.6 t C ha−1 from biomass), highlighting their effectiveness in enhancing ecosystem resilience. Other studies support these findings, underscoring the importance of context-specific approaches and long-term monitoring for sustainable land management. Enclosure and biophysical interventions emerge as promising strategies for enhancing species diversity and soil health, as well as promoting carbon sequestration in highland ecosystems. These findings emphasize the need for informed decision-making and community involvement in ecosystem restoration efforts to achieve meaningful and lasting impacts.

Conspectus of the vegetation types of Tajikistan and adjacent areas with special focus on phytosociological classes

Vegetation classification is a tool for organizing the patterns and diversity of plant communities. It is used in nature conservation, and helps to understand the role of vegetation in the biosphere. Given the rapidly diminishing opportunity to understand the vegetation diversity of Tajikistan located in the Middle Asian region, phytosociological surveys using the floristic-ecological approach and the Braun-Blanquet cover-abundance scale were undertaken in 2006. Aer 18 years of research, with a total of 55 research expeditions to Tajikistan, Kyrgyzstan, and Uzbekistan, it is time to summarise and make a first attempt to establish a comprehensive classification system for the entire vegetation of Tajikistan and the surrounding areas. As a first step, the Vegetation of Middle Asia (VMA) database with records from three countries: Tajikistan (4,130 relevés), Kyrgyzstan (1,681 relevés) and Uzbekistan (13 relevés) was created. e internal comparison of all the plots and the analysis of the similarities with the vegetation of Iran, Russia, Afghanistan, Mongolia, Pakistan, and China make it possible to present the comprehensive list of plant communities organized in 45 classes, 47 orders, 83 alliances, 297 associations, and 237 rankless units. In addition to those described in our previous works, we propose also several new sytaxa: &lt;i&gt;Eremogono griffithii-Nepetetea podostachyos, Artemisio persicae-Stipetea drobovii, Festucetea alaico-krylovianae, Carici koshewnikowii-Asperuletea oppositifoliae, Trichodesmo incani-Pachypterygietea brevipes, Aceretalia turkestanici, Juniperetalia seravschanicae, Crataegetalia ponticae, Populetalia pruinoso-euphraticae, Salici capusii- Hippophaeetalia rhamnoidis, Carici stenophylloidis-Stipetalia drobovii, Eritrichion pamirico-subjacquemontii, Stipetum kazachstanicae, Caricetum pamirensis&lt;/i&gt;, and &lt;i&gt;Bolboschoenetum affinis&lt;/i&gt;. Tis systematic compilation of data, based on our fieldwork and literature data, is not definitive, and certainly the rich and diverse vegetation of Middle Asia requires further studies incorporating also modern LIDAR and satellite techniques.

A dataset of 0.05-degree leaf area index in China during 1983–2100 based on deep learning network

Leaf Area Index (LAI) is a critical parameter in terrestrial ecosystems, with high spatial resolution data being extensively utilized in various research studies. However, LAI data under future scenarios are typically only available at 1° or coarser spatial resolutions. In this study, we generated a dataset of 0.05° LAI (F0.05D-LAI) from 1983–2100 in a high spatial resolution using the LAI Downscaling Network (LAIDN) model driven by inputs including air temperature, relative humidity, precipitation, and topography data. The dataset spans the historical period (1983–2014) and future scenarios (2015–2100, including SSP-126, SSP-245, SSP-370, and SSP-585) with a monthly interval. It achieves high accuracy (R² = 0.887, RMSE = 0.340) and captures fine spatial details across various climate zones and terrain types, indicating a slightly greening trend under future scenarios. F0.05D-LAI is the first high-resolution LAI dataset and reveals the potential vegetation variation under future scenarios in China, which benefits vegetation studies and model development in earth and environmental sciences across present and future periods.

Shallow drainage of agricultural peatlands without land-use change: have your peat and eat it too

IntroductionDrainage for agricultural purposes is one of the main drivers of peatland degradation, leading to significant greenhouse gas (GHG) emissions, biodiversity loss, and soil eutrophication. Rewetting is a potential solution to restore peatlands, but it generally requires a land-use shift to paludiculture or nature areas.MethodsThis study explored whether three different water level management techniques (subsoil irrigation, furrow irrigation, and dynamic ditch water level regulation) could be implemented on dairy grasslands to yield increases in essential ecosystem services (vegetation diversity and soil biogeochemistry) without the need to change the current land use or intensity. We investigated vegetation diversity, soil biogeochemistry, and CO2 emission reduction in fourteen agricultural livestock pastures on drained peat soils in Friesland (Netherlands).ResultsAcross all pastures, Shannon-Wiener diversity was below 1, and the species richness was below 5. The plant-available phosphorus (P) was consistently higher than 3 mmol L−1. None of the water level management (WLM) techniques enhanced vegetation diversity or changed soil biogeochemistry despite a notable increase in water table levels. The potential for CO2 emission reduction remained small or even absent. Indicators of land-use intensity (i.e., grass harvest and fertilization intensity), however, showed a strong negative correlation with vegetation diversity. Furthermore, all sites’ total and plant-available P and nitrate exceeded the upper threshold for species-rich grassland communities.DiscussionIn conclusion, our research suggests that incomplete rewetting (i.e., higher water tables while maintaining drainage) while continuing the current land use does neither effectively mitigate GHG emissions nor benefit vegetation diversity. Therefore, we conclude that combining WLM and reducing land-use intensity is essential to limit the degradation of peat soils and restore more biodiverse vegetation.