Regional Ecosystem Research Articles

Leaf habit drives leaf nutrient resorption globally alongside nutrient availability and climate

Abstract. Nutrient resorption from senescing leaves can significantly affect ecosystem nutrient cycling, making it an essential process to better understand long-term plant productivity under environmental change that affects the balance between nutrient availability and demand. Although it is known that nutrient resorption rates vary strongly between different species and across environmental gradients, the underlying driving factors are insufficiently quantified. Here, we present an analysis of globally distributed observations of leaf nutrient resorption to investigate the factors driving resorption efficiencies for nitrogen (NRE) and phosphorus (PRE). Our results show that leaf structure and habit, together with indicators of nutrient availability, are the two most important factors driving spatial variation in NRE. Overall, we find higher NRE in deciduous plants (65.2 % ± 12.4 %, n=400) than in evergreen plants (57.9 % ± 11.4 %, n=551), likely associated with a higher share of metabolic N in leaves of deciduous plants. Tropical regions show the lowest resorption for N (NRE: 52.4 % ± 12.1 %), and tundra ecosystems in polar regions show the highest (NRE: 69.6 % ± 12.8 %). At the same time, the PRE is lowest in temperate regions (57.8 % ± 13.6 %) and highest in boreal regions (67.3 % ± 13.6 %). Soil clay content, N and P atmospheric deposition (globally available proxies for soil fertility), and mean annual precipitation (MAP) play an important role in this pattern. The statistical relationships developed in this analysis indicate the important role of leaf habit and type for nutrient cycling and guide improved representations of plant-internal nutrient recycling and nutrient conservation strategies in vegetation models.

Integrating ecosystem stress into the assessment of ecosystem health in karst areas and exploring its driving factors

Accurately evaluating the degree of ecosystem health and comprehending its drivers are of crucial importance for ecosystem management and restoration in fragile ecoregions. Adopting an ecosystem stress perspective, this investigation scientifically diagnosed ecosystem health in Guizhou Province, a typical karst fragile ecological area, by developing a “Vigor-Organization-Resilience-Stress” (VORS) regional ecosystem health assessment framework. The principal driving factors and their spatio-temporal heterogeneity influencing ecosystem health in karst regions were investigated using geographic detectors and geographically and temporally weighted regression. Our findings indicated that: (1) The ecosystem health in Guizhou province presents a spatial distribution pattern of lower in the western region and higher in the eastern region, and the average ecosystem health index (EHI) in 2000, 2010 and 2020 is 0.194, 0.246 and 0.254 respectively, indicating that the overall ecosystem health level in Guizhou province has improved with the passage of time. (2) The spatiotemporal variation of ecosystem stress in Guizhou Province is substantial; the pressure associated with land use is projected to increase, whereas the intensity of stress attributed to rocky desertification and soil erosion is anticipated to diminish over time. (3) The primary determinants influencing the health of ecosystems in karst environments are the social and economic elements. These factors progressively amplify their effect on ecosystem health as time passes. The new assessment framework we have established includes ecosystem integrity and ecological threats faced by the ecosystem, which provides a new perspective for understanding the complex internal characteristics of karst areas and the coupling relationship between human and natural ecosystems. The results of this study can provide scientific reference for land use and ecological management policies in fragile ecological areas.

Redefining the modified water benefit-based ecological index to evaluate the impact of cropland expansion on the ecological environment in an arid area

Global land-use changes have a significant impact on the environment and food security, and escalating human activity and uncontrolled agricultural land expansion pose a grave threat to regional ecosystems. This study aims to assess the challenges faced by the environment and food security, with a particular focus on the impact of land use change on ecosystems. The study selected the Ebinur Lake Basin, a typical arid region in China, as the object and analyzed the land type changes from 2013 to 2021 using the Google Earth Engine platform and the China Land Cover Dataset. We created an Improved Water-Benefit-Based Ecological Index (IWBEI) based on the poor air quality environment in the watershed, and then calculated the ecological index of the watershed. The results indicate that the grassland and bare land areas in the Ebinur Lake Basin have fluctuated and shown an overall downward trend. The trend of farmland expansion is to expand to surrounding areas on the basis of existing farmland. The overall center of gravity of cultivated land in the watershed is moving from northwest to southeast, mainly towards the water source area. The IWBEI index is more prominent in identifying cultivated land and wetlands in arid regions. According to IWBEI's calculations, the priority order of land types is: forest > cultivated land > wetland > water > snow > grassland > impermeable surface > bare land. The overall ecological environment quality of the watershed is showing a deteriorating trend. Therefore, relevant departments should pay attention to the impact of farmland expansion on the local ecological environment to avoid the continuous deterioration of the ecological environment.

Spatial Distribution Patterns and Beta Diversity of Fish Communities in a Tropical River Basin of Deccan Plateau

ABSTRACTRiverine ecosystems exhibit significant spatial variations in their communities, and understanding of these variances is vital to comprehend the mechanisms that maintain biodiversity. This study was conducted to understand pattern of distribution and beta diversity of fish communities in the Bhima River basin in the Deccan Plateau region of India. Fish distribution data from 59 sites across 11 rivers of the Bhima River basin were collected, and pair‐wise βDissimilarity and site‐wise local contribution to beta diversity (LCβDSorensen) and its components (LCβDTurnover and LCβDNestedness) were calculated. Power function regression was analysed to understand the decay in community similarity with geographical and environmental distances. Redundancy analysis was performed to investigate the relationship between fish distribution and environmental variables. Results indicated that species richness declined with increasing longitude from west to east. A negative relationship was observed between species richness and LCβDSorensen. LCβDTurnover formed Ո‐shaped curve at both ends of the species richness gradient, while LCβDNestedness values exhibited Ս‐shaped curve. No significant difference between mean LCβDTurnover and mean LCβDNestedness across the sites was observed. The distance decay relationship between community similarity and both geographical and environmental distances follows the power law shape, and the slope of this relationship flattened with increasing distance. Precipitation, topography, temperature variation and dissolved oxygen played a pivotal role in shaping fish assemblages. This study provides insight into the spatial distribution of fish communities in the Bhima River basin, which will be helpful to comprehend the ordination of biodiversity in the riverine ecosystem of the Deccan Plateau region.

Evaluation and Optimization of Landscape Spatial Patterns and Ecosystem Services in the Northern Agro-Pastoral Ecotone, China

The alteration of landscape spatial patterns (LSPs) and ecosystem services (ESs) in watersheds can have detrimental effects on the local environment and community. However, a comprehensive understanding of the current state of LSPs and ESs in watersheds around Winter Olympic venues in China is limited. Here, we assessed current LSPs and ESs and developed optimization strategies for the Xigou watershed around Winter Olympic venues in the northern agro-pastoral ecotone of China. The results indicated that the main land use type was grassland in the Xigou watershed, and landscape types were relatively homogenous. All three ESs (water yield, sediment retention, and carbon storage) generally improved from 2004 to 2020. For ESs, there was the lowest total volume of water yield in 2004 (637.44 × 104 m3). But sediment retention (10.54 × 106 t, 18.13 × 106 t, 13.28 × 106 t, and 16.85 × 106 t) had an upward, then downward, then upward trend before and after ERP. Carbon storage grew steadily. Correlation analysis suggested that the three ESs were closely related to the landscape spatial indices of average patch area (AREA_MN), contagion index (CONTAG), and Shannon’s evenness index (SHEI). AREA_MN, CONTAG, and SHEI in the eastern part of the study area promoted sediment retention and carbon storage, while in the southwestern part of the study area, they inhibited water yield and sediment retention. The results suggest that improving sediment retention by optimizing land use and cover change (LUCC) and LSPs is the main approach to further enhance ESs in the study area. Our study suggests that the inclusion of multiple landscape pattern indices can provide a more comprehensive representation of regional ecosystem service.

Urban Sprawl and Imbalance between Supply and Demand of Ecosystem Services: Evidence from China’s Yangtze River Delta Urban Agglomerations

The contradiction between ecological resource protection and urban sprawl in urban agglomeration areas is becoming more and more prominent, facing a serious imbalance between the supply and demand of ecosystem services. To analyze the impact of urban agglomeration expansion on regional ecosystem services, based on multi-source data, an assessment model of supply and demand of ecosystem services for water conservation, carbon sequestration, soil conservation and crop production was constructed. With the help of value transformation model and spatial analysis method, this paper explores the risk of ecosystem service supply and demand imbalance faced by the Yangtze River Delta urban agglomeration in the process of expansion. This study found that the supply capacity of ecosystem services in the YRDUA has continued to decline at the spatial pixel scale; ecosystem service value deficits are a common problem in the YRDUA, with cities around Taihu Lake, such as Shanghai and Suzhou, being the most serious; the value surplus areas are concentrated in the southern cities, such as Xuancheng and Chizhou, but the balance between the supply of and demand for ecosystem services in these cities is also facing a challenge as the cities are expanding. This study analyzed the spatial pattern changes in the Yangtze River Delta region in the context of urban sprawl from the perspective of ecosystem service supply and demand, which helps to clarify the changing ecosystem service dynamics of the region and guide the formulation of urban planning policies and to achieve a balance between ecological supply and demand as well as sustainable development.

The Innovative Construction of Provinces, Regional Artificial Intelligence Development, and the Resilience of Regional Innovation Ecosystems: Quasi-Natural Experiments Based on Spatial Difference-in-Differences Models and Double Machine Learning

Based on the theory of regional innovation niches, this study calculates the resilience of regional innovation ecosystems and constructs a comprehensive evaluation index system for regional artificial intelligence development, resulting in a panel dataset for 30 provinces in China from 2009 to 2021 (excluding Tibet, Hong Kong, Macao, and Taiwan). Within the framework of the construction of innovative provinces, regional artificial intelligence, and the resilience of regional innovation ecosystems, spatial double-difference and double machine learning models are employed for a quasi-natural experiment. The main research conclusions are as follows: (1) Both the construction of innovative provinces and artificial intelligence have a significant positive impact on the resilience of regional innovation ecosystems. (2) However, regional artificial intelligence exhibits a negative spatial spillover effect on the resilience of regional innovation ecosystems. (3) The construction of innovative provinces can positively moderate the effect of artificial intelligence on the resilience of regional innovation ecosystems. (4) Through the promotion of regional artificial intelligence, the construction of innovative provinces can indirectly enhance the diversity, evolutionary potential, buffering capacity, fluidity, and coordination of regional innovation ecosystems, thereby driving a leap in resilience. (5) The mechanisms by which the construction of innovative provinces stimulates regional intelligent input, application, innovation, and market dynamics to further enhance the resilience of regional innovation ecosystems are effective not only in the treatment group but also in the control group.

The Social Economy and Contemporary Challenges: Innovation and Sustainability

This article explores the relevance of the social economy in addressing contemporary challenges through innovative and sustainable practices, supported by public policies. The research investigates the management models that social and solidarity economy organizations (SSEOs) employ to respond to the challenges of innovation and sustainability. The study includes an in-depth analysis of diverse operational models and accomplishments across various cases, presenting evidence on how the sector adopts innovative and sustainable practices. The article scrutinizes essential characteristics of SSEOs, such as democratic governance, reinvestment of surpluses in social businesses based on innovation and entrepreneurship, and a strong community orientation. These characteristics are examined for their relevance in addressing issues like social inequalities, digital transformation, and climate change. Additionally, the research includes an examination of four diverse cases of SSEOs established in mainland Portugal. It reveals the wide range of activities and significant interactions that these organizations have with various stakeholders in different economic and social contexts, contributing to regional social innovation ecosystems. The empirical study, based on a descriptive case study methodology applied to multiple and heterogeneous cases (in terms of fields of intervention and scale of resources), demonstrates that sustainability has become a driver in the social economy, within a framework of democratic governance and community involvement. Moreover, the research fills a gap in empirical literature by providing strong evidence through real cases of collaborative social innovation, the integration of environmental, social, and governance practices, as well as financial and regulatory support from the state for the resilience of SSEOs. The social value of the research lies in its empirical contribution to demonstrating how social business is a crucial element for communities to address global challenges, promoting economic growth and employment, social justice, including the fight against poverty, and environmental sustainability.

Some critical thinking on the integrative assessment of ecosystem service supply and demand relationships.

In the past decade, research on the relationships between the supply and demand of ecosystem services has been flourishing. To address issues such as the misuse of supply and demand concepts, methods, and results in current research, we proposed five key aspects that need to be considered to enhance the scientific rigor and practical value in assessing relationships between ecosystem service supply and demand. Firstly, it is essential to clarify the distinctions and connections between the concepts related to ecosystem service supply and demand, which are crucial prerequisites and starting points for assessing their relationships. Secondly, it is necessary to integrate relevant environmental standards or policy objectives to develop reliable methods for assessing the demand for ecosystem regulating services. Furthermore, it is important to properly address the modifiable areal unit problem by determining the most appropriate spatial scale and unit for evaluating relationships between ecosystem service supply and demand. Additionally, it is crucial to differentiate between quantitative and qualitative methods for characterizing (im)balances or (mis)matches between ecosystem service supply and demand, particularly avoiding the use of qualitative methods to represent quantitative relationships between supply and demand. Lastly, it is imperative to integrate ecosystem service flows into the assessment of supply and demand relationships, and evaluate the dynamic supply and demand relationships of regional ecosystem services from a coupled "supply-flow-demand" perspective.

Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development

The pivotal aspects of enhancing regional ecosystem services and augmenting socioeconomic growth lie in optimizing the land-space development and protection strategies, coupled with the establishment of a robust ecological network (EN). This article examines the Poyang Lake area and employs the MOP model, NSGA-II, and PLUS model to determine the best sustainable land use strategy. Subsequently, the MSPA, InVEST model, circuit theory, complex network, and others are employed to construct and analyze the land-space EN across three time periods. Ultimately, the EN is optimized based on spatial protection priority, ecological obstacle areas, and ecological nodes. The results show the following: (1) From 2005 to 2035, more construction land will be developed around the Greater Nanchang area and other urban centers. In the BAU scenario, construction land will expand faster, while cultivated land, forest, grassland, and bare land will continue to decline. In the SD scenario, the alteration to comparable land is minimal, the growth rate of construction land will slow, cultivated land, forest, grassland, and bare land will all decline little, and the water area will increase slightly; (2) While the area of ecological sources is decreased and ecological corridors become longer and narrower in the BAU scenario, the spatial distribution of ENs in different periods is small, and the quantitative structure and spatial distribution of ecological sources and corridors are essentially unchanged in the SD scenario; (3) Based on the topological structure of ENs, it is found that the clustering of nodes in the SD scenario is more obvious, the importance of ecological sources is enhanced, the efficiency of information transmission is improved, and the radiation range is wider and more stable; (4) The greatest priority ecological sources in each period are concentrated around Poyang Lake. In the SD scenario, the priority of ecological sources improves, and 7025 km2 of ecological obstacle restoration area is identified, with 41, 31, and 36 ecological breakpoints in the first, second, and third levels. The study’s findings can assist and shape theoretical and practical approaches to land governance and sustainable development in great lake areas.

What do we know about biocrust lichens in Argentina? A comprehensive review and new records

Lichens are among the most distinctive and colorful organisms found in biological soil crusts (biocrusts). Along with cyanobacteria, green algae, and bryophytes, they inhabit the top few millimeters of the soil surface, forming the living skin of the soil. They cover large areas of the planet's arid and semiarid regions, as well as degraded terrestrial ecosystems in other regions. Although global studies of biocrusts have tripled in the last two decades, South America remains one of the least studied continents. In Argentina, ecological studies of biocrusts are increasing, but knowledge of the taxonomic diversity of the lichens that comprise them remains limited. Therefore, it is crucial to increase studies on terrestrial lichens, which, although often inconspicuous, may be more abundant than previously thought. To contribute to the knowledge of biocrust lichens taxonomy in Argentina, we proposed to 1) perform a bibliographic review of the works that reported species lists to confirm and update the taxonomic nomenclature and distribution, and 2) expand knowledge in less studied regions through the study of specimens from central Argentina. The results reveal that between 2002 and 2022, 78 crust-forming lichen species were recorded in Argentina. The richest family was Verrucariaceae, along with Collemataceae, Peltulaceae, and Lichinaceae distributed in the northern, western, and central-southern regions of the country, mainly in the arid and semiarid areas of Mendoza, San Juan, Neuquén, and San Luis. The most common lichen species found in the crusts were Placidium squamulosum, Endocarpon pusillum, Enchylium tenax, Peltula obscurans, and Psora decipiens, in descending order. We have expanded this lichen diversity with three new species records for Argentina: Gloeoheppia erosa, Heppia adglutinata, and Heteroplacidium divisum, as well as the distribution of Enchylium coccophorum, Peltula obscurans, Placidium squamulosum, and Psora icterica in the central region of the country. In this way, we hope that this study can serve as a starting point for future research on lichen composition in soil crusts.

Incorporating Ecosystem Service Trade-Offs and Synergies with Ecological Sensitivity to Delineate Ecological Functional Zones: A Case Study in the Sichuan-Yunnan Ecological Buffer Area, China

Enhancing regional ecosystem stability and managing land resources effectively requires identifying ecological function zones and understanding the factors that influence them. However, most current studies have primarily focused on ecosystem service bundles, paying less attention to the trade-offs, synergies, and ecological sensitivity, leading to a more uniform approach to functional zoning. This study aimed to analyze and describe the spatial and temporal patterns of four essential ecosystem services, including water yield (WY), net primary productivity (NPP), soil conservation (SC), and habitat quality (HQ), in the Sichuan-Yunnan ecological buffer area over the period from 2005 to 2019. Spatial overlay analysis was used to assess ecological sensitivity, trade-offs, synergies, and ecosystem service bundles to define ecological functional zones. Geographic detectors were then applied to identify the primary drivers of spatial variation in these zones. The findings showed a progressive improvement in ecosystem service functions within the Sichuan-Yunnan ecological buffer zone. Between 2005 and 2019, NPP, soil conservation, and water yield all demonstrated positive trends, while HQ displayed a declining trend. There was significant spatial heterogeneity and distinct regional patterns in ecosystem service functions, with a general decrease from southwest to northeast, particularly in NPP and HQ. Trade-offs were evident in most ecosystem services, with the most significant between WY and HQ and most in the northeast and east regions. Ecological sensitivity decreased from southwest to northeast. Regions with a higher ecological sensitivity were primarily situated in the southwestern region, and their spatial distribution pattern was comparable to that of high habitat quality. The spatial overlay analysis categorized areas into various types, including human production and settlement zones, ecologically vulnerable zones, ecological transition zones, and ecological conservation zones, accounting for 17.28%, 22.30%, 7.41%, and 53.01% of the total area, respectively. The primary environmental factor affecting ecological function zoning was identified as precipitation, while the main social variables were human activity and population density. This study enhances the understanding of ecological functions and supports sustainable development in the Sichuan-Yunnan ecological buffer area, offering important guidance for ecological zoning.

Mathematical model for managing marine ecosystem risks

The article presents the results of the research aimed at developing and verifying a mathematical model for managing the ecosystem risks of marine areas. The main purpose of the research is to create an effective tool for assessing and managing the risks arising from anthropogenic influence, climate change and other natural factors. The proposed model is based on the existing theory of sea ecosystem risks management and takes into account the relationship between natural and anthropogenic factors, condition of marine ecosystems, their vulnerability and ecosystem services. The model uses mathematical methods, in particular, differential equations, statistical analyses, simulation modeling and network analysis, allowing creation of detailed models that reflect marine ecosystems' dynamics and their response to external influence. Numerous experiments were conducted in order to verify the model. They demonstrate its ability to predict changes in the condition of marine ecosystems under influence of various factors. The results of the research show that the proposed model can be an effective tool for optimizing management strategies, minimizing ecosystem risks and improving sustainability of marine ecosystems. Practical recommendations developed on the basis of the results of the research include strategies for preventing, minimizing and adapting to potential threats, taking into consideration each region's and ecosystem's specifics. The proposed model helps to optimize management decisions, reducing risks and improving the condition of marine ecosystems affected by anthropogenic impact and climate change. It is a reliable tool for ensuring sustainability and preservation of marine ecosystems. This approach allows for evidence-based risk management that increases sustainability of marine ecosystems and their preservation for future generations. The model also considers key factors influencing marine ecosystems, including biological diversity, water quality, industrial fisheries, tourism and recreation, and allows evaluation of effectiveness of various management decisions in the context of such factors. The application of this model in ecosystem management practices allows making more informed decisions regarding protection and preservation of marine resources. It contributes to their sustainable development and provision of ecosystem services having critical importance for society.

Resilience evaluation and spatio-temporal evolution analysis of China's science and technology financial ecosystem

ABSTRACT This paper discusses the resilience of science and technology (sci-tech) financial ecosystem. It constructs an evaluation system from four dimensions: resistance, adaptability, recovery and innovation. The data are from 29 provinces in China from 2010 to 2020. It is evaluated using entropy weights–TOPSIS and dynamic evaluation model. The spatial evolution law is revealed by spatial autocorrelation analysis. The results show that: (1) The overall resilience level of sci-tech financial ecosystem is not high. Its evolution and development are generally in a relatively stable state. It has significant regional heterogeneity, showing a distribution pattern of ‘high east and low west’. (2) It has significant spatial positive correlation. The structure of the sci-tech financial ecosystem in the eastern region is highly complex, most provinces are in high–high agglomeration area. Provinces in other regions are mainly in low–low agglomeration area. Only a few provinces have experienced changes in the spatial distribution. (3) The dynamic value in the eastern region shows polarisation characteristics. Although the static value of resilience in the central and western regions is low, the dynamic evaluation value in some provinces in the central and western regions is high. The subsequent growth momentum of resilience in the north-eastern region is insufficient.

The university as an intellectual capital catalyst for sustainable organisations: conceptualising the nexus

Purpose Intellectual capital (IC) is an increasingly important strategic asset for sustainable value creation in organisations. This paper aims to provide a conceptual perspective on the university’s role as a catalyst for IC creation and development within the dynamic landscape of organisations, exploring the nexus to capture its essence. Design/methodology/approach Adopting a conceptual framework development approach, key concepts were cohesively and coherently synthesised from various theoretical underpinnings, namely, the multiple capitals approach to maximising corporate value creation, the evolved triple bottom line approach to corporate sustainability, the triple helix innovation model and its subsequent extensions, the upper echelons theory and the social licence construct linked to stakeholder, legitimacy and institutional theories. Findings A comprehensive conceptual framework was developed that outlines universities’ role in catalysing four corporate IC forms crucial to sustainable organisational value creation: human capital, governance capital, social/relational capital and structural/organisational capital. The framework interprets this role of universities as dynamic IC reservoirs serving regional ecosystems for sustainable development. It highlights the synergistic sustainable value creation between universities and organisations in host communities and broader society, with university governance acting as a key driver. Originality/value This paper offers a theoretically grounded interpretation of universities’ pivotal role in catalysing essential forms of IC to support contemporary organisations’ sustainable value-creation processes. The proposed framework has the potential to ignite conversations on the crucial connection between universities and corporate IC development relevant to sustainable organisations, inspiring future empirical research, reflection and discussion.

Effects of Nitrogen Addition on Soil Organic Carbon and Its Fractions in Karst Farmland and Forest Ecosystems of China Based on Meta-analysis

In recent decades, with the intensification of human activities, atmospheric nitrogen （N） deposition has been increasing. N deposition affects carbon （C） cycling in terrestrial ecosystems, especially in fragile karst ecosystems. Karst ecosystems are considered to be an important C pool. To evaluate the impact of N deposition on soil organic C （SOC） and its fractions in karst ecosystems of China, we collected and collated 14 English literature published through the end of March 2023, yielding a total of 460 sets of experimental data. The meta-analysis examined the effect of N addition levels [low N: ≤50 kg·（hm2·a）-1, medium N: 50-100 kg·（hm2·a）-1, and high N: >100 kg·（hm2·a）-1, in terms of N] on SOC and its fractions [particular organic C （POC）, readily oxidized organic C （ROC）, microbial biomass C （MBC）, and dissolved organic C （DOC）]. The results showed that N addition levels significantly affected the responses of farmland and forest soil SOC and their active fractions to N addition. Specifically, low and high N additions significantly increased SOC concentration in farmland ecosystems, whereas medium N addition significantly increased SOC concentration in forest ecosystems. In addition, soil active C fraction concentrations increased under high N addition in farmland ecosystems and under low and medium N addition in forest ecosystems. Without considering the level of N addition, N addition significantly enhanced soil organic matter （SOM） mineralization in both farmland and forest ecosystems and increased the SOC concentration in farmland ecosystems but not forest ecosystems. The responses of different active C fractions to N addition were diverse. In farmland ecosystems, the POC and ROC concentrations increased, but DOC did not change with N addition. In forest ecosystems, the DOC and POC concentrations increased, but there was no significant effect on MBC. Moreover, the response ratios （RR） of SOC and its fractions in different ecosystems to N addition were influenced by different environmental factors. In farmland ecosystems, the response ratio of SOC was related to the annual average temperature and soil pH. The response ratio of DOC was affected by the annual average temperature, mean annual precipitation, and N addition rate. The POC response ratio was related to the N addition rate. In forest ecosystems, the effects of N addition on the SOC response ratio were significantly altered by the annual average temperature, mean annual precipitation, and soil pH. However, the response ratios of DOC, POC, and MBC were not affected by the annual average temperature, mean annual precipitation, soil pH, and N addition rate. Consequently, these findings indicate that N addition could enhance soil SOC concentration and promote soil C sequestration in farmland and forest ecosystems in karst regions, but this effect relies on the level of N addition. This provides a scientific basis for predicting the soil C sink function in karst ecosystems under climate change scenarios.

How can regional innovation ecosystems attain and maintain stable operation? - an investigation utilising NCA and fsQCA

ABSTRACT This study uses the Multi-Level Perspective (MLP) on socio-technical transitions to develop a theoretical model for analyzing the stable operation of regional innovation ecosystems. Focusing on 30 provinces in China, it employs Necessary Condition Analysis (NCA) and Fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine the configuration paths driving their stability. First, the findings reveal that innovation actors, resources, driving policies, industrial regulations, infrastructures, and the innovation environment are not individually necessary for stability. However, infrastructure is identified as a critical core condition. The study highlights a complex causal relationship and synergistic interplay among the six antecedent conditions. Second, the research identifies two paths to highly stable operation in regional innovation ecosystems: the ‘Innovation Actor + Infrastructure’ path and the ‘Infrastructure’ path. Finally, the results show that configurations for highly and non-highly stable operations exhibit causal asymmetry, indicating ‘different paths to the same destination.’ This study deepens theoretical insights into regional innovation ecosystems and offers actionable strategies for their stable operation.

Effect of bedrock, tree size and time on growth and climate sensitivity of Norway spruce in the High Tatras

AbstractTree growth is a multifaceted process influenced by various factors at different spatial and temporal scales, including intrinsic tree traits and environmental conditions. Climate factors have a significant impact on tree growth dynamics, while geological controls can also play a crucial role. However, our understanding of the interplay between these factors concerning tree growth is currently limited. This study focuses on Norway spruce (Picea abies [L.] Karst.), one of the economically most important coniferous tree species in Europe, to investigate the interplay of growth, climate, and environment at the forest and corresponding treeline sites in the High Tatra Mountains of Slovakia. Specifically, we developed chronologies of tree-ring width (TRW) and late-wood density (MXD) for different tree size classes across two limestone and granitic sites. Growth rates of Norway spruce trees have been increasing in forests since the 1930s and from the 1950s at treelines. Growth rates were consistently higher on limestone bedrock compared to granitic bedrock conditions. Variability of radial growth is primarily driven by climate at both geological settings with trees on granitic bedrock displaying more pronounced responses to climatic variables. We observed weakening (non-stationarity) in climate signals over time and across all size classes in both geological settings. The magnitude of these effects is small, but varies across size classes, with larger trees generally displaying stronger climate sensitivities compared to smaller ones. Therefore, our findings accentuate the potential implications of geological settings, climate, and environmental factors on the absolute growth and growth dynamics of Norway spruce, highlighting the need for further research to fully understand and manage forest ecosystems in mountainous regions.

Analysis of Spatial and Temporal Evolution of Ecosystem Services and Driving Factors in the Yellow River Basin of Henan Province, China

The Henan Yellow River Basin is an ecological support belt for the entire basin. It holds a significant position in high-quality development and ecological conservation within the Yellow River Basin. However, due to improper development activities, such as urban expansion and deforestation of farmland, certain areas of the region have encountered a series of ecological issues, posing significant challenges to ecosystem services. The scientific foundation for the sustainable development of the ecological environment in the Henan Yellow River Basin is established by research on the evolution characteristics and driving factors of ecosystem service functions. This study focuses on the Henan Yellow River Basin, by introducing remote sensing data and biomass data, assessing the spatiotemporal variations in ecosystem service by the InVEST model—including carbon stock, water yield, and soil conservation—from 2000 to 2020. It analyzes the ecosystem service functions of different land use types. It employs the Geodetector to identify the dominant driving factors behind the changes in these functions based on the improved InVEST model evaluated results. The findings reveal that from 2000 to 2020, total carbon stock increased by 1.86%, carbon stock per unit area rose by 1.81%, and the spatial distribution remained largely stable. The high-value regions were clustered in the west and part of the north, primarily consisting of forest land. Carbon stock capacity in other regions, mainly farmland and construction land, was poor, with forest land having the strongest carbon sequestration capacity, followed by grassland. Total water yield decreased by 20.08%, and water yield per unit area decreased by 20.03%, with a spatial distribution closely following the trend of precipitation distribution. The high-value regions were clustered in the south, primarily in forest land and farmland. The total amount of soil conservation decreased by 19.96%, and soil conservation per unit area decreased by 19.93%, with spatial distribution patterns similar to those of carbon stock and water yield. The high-value regions were concentrated in the southwestern and northern forested regions, while soil conservation capacity in areas primarily consisting of farmland and construction land was weaker. The divergence of carbon stock was most influenced by population density, water yield by precipitation, and soil conservation by slope. In conclusion, during the study period, while carbon storage increased, the significant decline in water yield and soil conservation highlighted critical issues in the ecosystem service functions of the region. These findings indicate the need for targeted conservation measures and sustainable development strategies to address the decline in ecosystem services and mitigate adverse environmental impacts, ensuring the long-term health of the region’s ecosystems. This study offers an in-depth understanding of the differentiation of ecosystem service functions and their driving factors, enabling precise assessment of regional ecosystem services, and providing a theoretical foundation for formulating effective regional ecological conservation policies.

A dataset of NDVI for the vegetation growing season in Central Asia with a resolution of 250 m (2001–2020) and 30 m (2020)

Central Asia is the largest arid and semi-arid region in the Northern Hemisphere, and its ecological environment is extremely fragile and susceptible to the effects of global climate change. Maintaining the stability of the region's ecosystem is crucial to global economic and social development due to its unique geographic location. Vegetation serves as a significant indicator of the ecological environment, and the spatial and temporal distribution pattern, as well as the change trend of vegetation, are important indicators in evaluating the ecological status of the region. The Normalized Difference Vegetation Index (NDVI) is a commonly used remote sensing index to study vegetation, which characterizes the spatio-temporal changes of vegetation. This dataset utilized MODIS13Q1 to generate long-term time series growing season mean NDVI data with a spatial resolution of 250m in Central Asia from 2001 to 2020. To obtain the 2020 growing season mean NDVI data with a higher spatial resolution of 30m, the Cubist algorithm based on rule segmentation regression was utilized to fuse the Landsat data and MODIS data. Meanwhile, this dataset carried out quality control of data products from three aspects: data source quality control, model training optimization, and model independent verification to ensure the accuracy and reliability of data. The generation of this dataset provides powerful data support for the analysis of vegetation dynamic change and spatial pattern in Central Asia.