Regional Ecosystem Research Articles

Impact of the innovation promotion strategy on digital technology diffusion in regional innovation ecosystems

Impact of the innovation promotion strategy on digital technology diffusion in regional innovation ecosystems

Spatiotemporal Evolution, Driving Mechanisms, and Zoning Optimization Pathways of Ecosystem Health in China

The health status of ecosystems is an important prerequisite for ensuring regional ecological security. Exploring the spatiotemporal patterns, driving mechanisms, and zoning regulation pathways of ecosystem health is of great significance for achieving co-ordinated and sustainable regional ecosystems. This study uses China as a case area and applies the InVEST model to measure integrated ecosystem services and incorporates it into an evaluation framework for ecosystem health based on the “Vigor-Organization-Resilience-Ecosystem Services” (VORS) model. It reveals the spatiotemporal evolution characteristics of ecosystem health in China from 2000 to 2020 and employs the geodetector and spatiotemporal geographically weighted regression model to analyze the main influencing factors and spatial differentiation characteristics, thereby exploring ecological management zoning and optimization pathways. The study results show that (1) during the study period, the overall ecosystem health level in China showed a declining trend, dropping from 0.397 in 2000 to 0.377 in 2020. (2) Overall, China’s ecosystem health exhibits strong spatial positive correlation and spatial clustering characteristics, with a basic pattern of lower values in the northwest and higher values in the southeast. (3) Vegetation coverage, population density, density of road network, and per capita GDP are the main influencing factors of ecosystem health in China. (4) China is divided into five types of Ecological Management Zones: Ecological Conservation Zone, Ecological Enhancement Zone, Ecological Buffer Zone, Ecological Remediation Zone, and Ecological Reshaping Zone, with differentiated strategies proposed for optimizing ecosystem health in each zone.

Trophic ecology, based on stable isotope values, of long-finned pilot whales Globicephala melas stranded on the Icelandic coast

In Iceland, occurrences of long-finned pilot whales Globicephala melas and strandings in coastal waters are irregular and thought to be related to prey movements; however, little is known about the population’s trophic ecology, making it difficult to assess its role in the regional ecosystem. To investigate the trophic niche of the species, we measured δ13C and δ15N values from skin and muscle samples collected from 16 strandings (12 single and 4 mass strandings) spanning 33 yr (1988-2021). We tested the effects of sex, age class and body length on δ13C and δ15N values within the species. We found that δ13C values did not differ between sexes or age classes, nor did they vary with body length. Values of δ15N did not vary with sex or body length, but varied slightly between adults and juveniles, albeit not sufficiently to support a difference in trophic levels. Whales from different mass stranding events showed similar stable isotope niche widths (approximately 0.20‰2) and overlapping isotope niches (generally >45% of the standard ellipse area corrected for small sample size). Overall, pilot whales in this region showed a narrow isotopic niche width and low intraspecific variation in isotopic niche. Future analyses using complementary chemical tracers and stomach contents will be important to identify the factors driving these patterns. The first measurements of the stable isotope niche of pilot whales presented here provide a baseline for future studies to determine niche overlap between cetaceans in Iceland, contributing to their management and conservation.

Spatio-temporal changes in atmospheric aridity over the arid region of Central Asia during 1979–2019

The arid region of Central Asia (CA) is the largest non-zonal arid region in the world. It has experienced significant changes in climate and hydrological cycle systems owing to global warming, which has posed serious impacts on the water resources and ecological environment in this region. Although the atmospheric water vapor pressure deficit (VPD) can directly reflect the atmospheric moisture condition, studies on the change of atmospheric moisture deficit in CA are scarce. Thus, we investigated the changes in VPD in the arid region of CA from the perspective of atmospheric aridity based on the CRU TS4.04 and ERA5 data. Our results showed that the VPD in more than 95 % of grids in the arid region had a significantly increasing trend during 1979–2019. Seasonally, VPD trends were increasing in spring, summer, and autumn but decreasing in winter. The changes in saturated water vapor pressure and actual water vapor pressure determined the VPD changes. The saturated water vapor pressure showed a clearly upward trend, whereas the actual water vapor pressure did not increase at the same rate, resulting in the increase of VPD. The first four leading modes revealed by empirical orthogonal function (EOF) analysis represented the patterns by explaining 81.4 % of the total variance. The positive phase of EOF1 was characterized by a monopole pattern, and this mode continued to increase. Contrastingly, EOF2 (and EOF3) showed dipole patterns over east–west CA (and north–south CA), with a mainly interannual variability. Due to the combined effect of increasing temperatures and decreasing relative humidity, the VPD has been intensifying since the mid-to-late 1990 s in CA, and the atmosphere has become significantly drier. These research results can deepen the scientific understanding of global warming impacts on atmospheric moisture and provides a reference for revealing the VPD changes and their impacts on the climate system and ecosystem in arid regions. Our results highlight that the impacts of VPD change should be adequately considered in environmental management and policy-making processes in Central Asia.

Climate and Altitude Drive Spatial and Temporal Changes in Forests on the Eastern Tibetan Plateau—Evidence from the Shaluli Mountain

Forests are widely distributed in terrestrial ecosystems, covering about one-third of the global land area. They play a key role in sequestering carbon, releasing oxygen, mitigating climate change, and maintaining ecosystem balance. The ecology of the Tibetan Plateau is very fragile, but the impact of environmental change on regional forest ecosystems is not yet clear. Located in the Eastern Tibetan Plateau, the Shaluli Mountain has the richest biodiversity and the widest distribution of forests on the Tibetan Plateau. Assessing the dynamics of forest change is the basis for correctly formulating forest management measures, and is important for regional biodiversity conservation. However, traditional field surveys have the shortcomings of high cost, being time-consuming, and having poor regional coverage in forest dynamics monitoring. Remote sensing methods can make up for these shortcomings. Therefore, in this study, satellite remote sensing images were used to extract forest information from 2000 to 2020 in Shaluli Mountain, and the main drivers of forest change were analyzed with full consideration of the Spatially Stratified Heterogeneity (SSH) of environmental factors. The results found that the forest area increased from 23,144.20 km2 in 2000 to 28,429.53 km2 in 2020, and the average Percentage of Forest Cover (PFC) increased from 19.76% to 21.67%, with significant improvement in forest growth. The annual minimum temperature (TMN), altitude, annual maximum temperature (TMX), and annual precipitation (PRE) were the main driving factors of forest change, with an average driving power (q-value) of 0.4877, 0.2706, 0.2342, and 0.2244, and TMN was the primary limiting factor for forest growth. In addition, the driving power of all environmental factors on forest change increased from 2000 to 2020. The results of this study can provide a basis for the development of forest management strategies, and provide reference materials for regional biodiversity conservation.

Detection of spatial and temporal variation characteristics of vegetation cover in the Lower Mekong region and the influencing factors

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

Significant negative impact of human activities on carbon storage in the Yellow River Delta over the past three decades

With the increasing intensification of human activities, significant changes in land use and land cover (LULC) have posed a severe threat to the carbon storage capacity of wetland ecosystems. A deep understanding of this impact is crucial for protecting regional ecosystems and promoting sustainable development. This study utilized the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the human activity intensity (HAI) index to conduct detailed grid analysis and global analysis of carbon storage through creating fishnet system and explored the complex relationship between carbon storage and HAI in the Yellow River Delta (YRD), China. The results indicated that over the past 30 years, natural wetlands such as meadow wetlands and salt marshes in the study area had undergone significant degradation due to escalating human activities, while artificial wetlands and non-wetland areas expanded. Concurrently, the total regional carbon storage had declined by 2.08 Tg, representing a significant drop of 8.22 % in the YRD from 1990 to 2020. Among them, dry land, as the primary land type, served as the most crucial carbon pool. Additionally, the human activity intensity of land surface (HAILS) increased significantly, with a growth rate of 37.27 %. HAI mapping revealed a continuous expansion of areas with high HAI. In contrast, the Yellow River Delta National Nature Reserve (YRDNNR) maintained relatively low HAI. Correlation analysis further showed the significant negative correlation (p < 0.01) between carbon storage and HAI, with r values of grid analysis ranging from −0.1395 to −0.0344, while that for global analysis was −0.9643, respectively. This reflected the spatial heterogeneity and agglomeration effects of data analysis across different scales. This study provides valuable insights for achieving the “dual carbon” goals and supporting the conservation and management of wetland ecosystems.

Vegetation restoration strategies in arid or semi-arid regions-From the perspective of optimal control.

Inappropriate human activities contribute to the degradation of ecosystems in arid or semi-arid regions. Therefore, emphasizing the importance of strategies for restoring vegetation in these areas cannot be overstated. However, there has been insufficient research on how to develop effective restoration strategies at minimal cost. This paper addresses this gap by studying how optimizing the spatiotemporal distribution of human activities through local and boundary controls can reduce the level of desertification in vegetation pattern structures, thereby facilitating the recovery of arid land vegetation. The results indicate that vegetation restoration depends on the proportion and number of human activity areas, with a trade-off between them. Furthermore, consistent conclusions were obtained on circular regions, demonstrating the robustness of the approach to boundary shapes. This paper aims to offer new insights into the restoration of arid land vegetation and the prevention of catastrophic ecosystem changes from the perspective of optimal control.

Thawing Permafrost Is Affecting Climate, but It’s Unclear by How Much

Models produce widely varying estimates of how ecosystems in the northern permafrost region are currently affecting the global greenhouse gas budget.

Mastering Snow Analysis: Enhancing Sampling Techniques and Introducing ACF Extraction Method with Applications in Svalbard

Semi-volatile organic contaminants (SVOCs) are known for their tendency to evaporate from source regions and undergo atmospheric transport to distant areas. Cold condensation intensifies dry deposition, particle deposition, and scavenging by snow and rain, allowing SVOCs to move from the atmosphere into terrestrial and aquatic ecosystems in alpine and polar regions. However, no standardized methods exist for the sampling, laboratory processing, and instrumental analysis of persistent organic pollutants (POPs) in snow. The lack of reference methods makes these steps highly variable and prone to errors. This study critically reviews the existing literature to highlight the key challenges in the sampling phase, aiming to develop a reliable, consistent, and easily reproducible technique. The goal is to simplify this crucial step of the analysis, allowing data to be shared more effectively through standardized methods, minimizing errors. Additionally, an innovative method for laboratory processing is introduced, which uses activated carbon fibers (ACFs) as adsorbents, streamlining the analysis process. The extraction method is applied to analyze polychlorobiphenyls (PCBs) and chlorinated pesticides (α-HCH, γ-HCH, p,p′-DDE, o,p′-DDT, HCB, and PeCB). The entire procedure, from sampling to instrumental analysis, is subsequently tested on snow samples collected on the Svalbard Islands. To validate the efficiency of the new extraction system, quality control measures based on the EPA methods 1668B and 1699 for aqueous methods are employed. This study presents a new, reliable method that covers both sampling and lab analysis, tailored for detecting POPs in snow.

A Model that Explains the Contrasting SST Trends in the Southern Pacific Ocean

Sea surface temperature (SST) of the southern Pacific Ocean plays an important role in ocean-atmospheric interactions, influencing both regional and global climate and ecosystems. The contrasting SST trends in the southern Pacific Ocean during 1993-2021 are noted by analyzing satellite and in-situ datasets, consisting of SST warming trend (0.05℃·yr−1) in the region of 80°W-180,30°S-50°S and cooling trend (−0.04℃·yr−1) in the area of 60°W-150°W, 55°S-70°S. A detailed trend analysis for the wind and sea ice concentration suggest that Ekman transport and sea ice radiative positive feedback are the two key contributors to the contrasting SST trends. The intensified downwelling (upwelling), induced by the Ekman transport and strengthened westerlies, gives rise to warm (cold) water swarming in (upturning) from lower latitudes (deeper ocean), which causes SST warming (cooling). Moreover, the sea ice increase at higher latitudes, due to both the cold water transport from deeper ocean layers and broken ice transport from polar regions, strengthens the cooling trend through sea ice positive radiative feedback. In conclusion, these findings underscore the complexity of SST trends in the southern Pacific Ocean, highlighting the critical roles of Ekman transport and sea ice radiative feedback in shaping regional climate dynamics.Plain Language Summary: The southern Pacific Ocean is an indispensable part in the climate system while it still remained poorly observed. The SST trend is regarded as a critical indicator of global climate change. Using the satellite and in-situ datasets, we find that the contrasting SST trends from 1993 to 2021, one area in this region is warmed by 0.3℃ per decade, while another area is cooled by -0.1℃ per decade. Considering impacts of various factors such as wind, sea ice and radiation, the primarily explanation is that wind-driven warm (cold) water from the subtropics (deeper ocean) flows in and goes downward (goes upward and flow away) in the warm (cold) area through oceanic circulation and leads to the SST warming (cooling). Additionally, the cooling trend is also related to the cold water that flows to higher latitudes and forms ice there and at the same time, trash ice from polar regions driven by enhanced south wind speed will be transported there. As a result, ice increases, reflects more shortwave radiation to space, and surface downward shortwave radiation decreases which contributes to SST decreases.

Space-Based Mapping of Pre- and Post-Hurricane Mangrove Canopy Heights Using Machine Learning with Multi-Sensor Observations

Coastal mangrove forests provide numerous ecosystem services, which can be disrupted by natural disturbances, mainly hurricanes. Canopy height (CH) is a key parameter for estimating carbon storage. Airborne Light Detection and Ranging (LiDAR) is widely viewed as the most accurate method for estimating CH but data are often limited in spatial coverage and are not readily available for rapid impact assessment after hurricane events. Hence, we evaluated the use of systematically acquired space-based Synthetic Aperture Radar (SAR) and optical observations with airborne LiDAR to predict CH across expansive mangrove areas in South Florida that were severely impacted by Category 3 Hurricane Irma in 2017. We used pre- and post-Irma LiDAR-derived canopy height models (CHMs) to train Random Forest regression models that used features of Sentinel-1 SAR time series, Landsat-8 optical, and classified mangrove maps. We evaluated (1) spatial transfer learning to predict regional CH for both time periods and (2) temporal transfer learning coupled with species-specific error correction models to predict post-Irma CH using models trained by pre-Irma data. Model performance of SAR and optical data differed with time period and across height classes. For spatial transfer, SAR data models achieved higher accuracy than optical models for post-Irma, while the opposite was the case for the pre-Irma period. For temporal transfer, SAR models were more accurate for tall trees (&gt;10 m) but optical models were more accurate for short trees. By fusing data of both sensors, spatial and temporal transfer learning achieved the root mean square errors (RMSEs) of 1.9 m and 1.7 m, respectively, for absolute CH. Predicted CH losses were comparable with LiDAR-derived reference values across height and species classes. Spatial and temporal transfer learning techniques applied to readily available spaceborne satellite data can enable conservation managers to assess the impacts of disturbances on regional coastal ecosystems efficiently and within a practical timeframe after a disturbance event.

The Spatiotemporal Dynamics of Temperature Variability Across Mts. Qinling: A Comparative Study from 1971 to 2022

Analyzing the spatiotemporal patterns of atmospheric temperature in sensitive areas is critically important for understanding the broader implications of global climate change, which remains a prominent topic in geosciences. It also plays a crucial role in advancing sustainable development. This study utilized daily minimum, maximum, and mean temperature data from twelve meteorological stations across the South and North Mts. Qinling (Qinling Mountains). Employing trend analysis, the Mann–Kendall mutation test, and Morlet wavelet analysis, we explored the predominant temperature trends and characteristics from 1971 to 2022. Our findings revealed consistent inter-annual warming trends in both regions, with more rapid temperature increases in the North compared to the South. Notably, significant shifts occurred in 2003 for both mean and minimum temperatures in the North, while the maximum and minimum temperature values were recorded in the 2010s and 1980s, respectively. Both regions exhibited a primary temperature fluctuation cycle of 28 years. Seasonally, the strongest warming effects appeared in spring, with the weakest in autumn, and moderate effects in winter and summer, indicating that spring contributes most significantly to regional warming. Monthly analysis showed positive temperature trends across all months, with higher rates in the North. The weakening temperature boundary effect of the Mts. Qinling suggested a weakening North–South division, particularly highlighted by the northward shift of the 1 °C isotherm curve for the coldest month, moving away from the previously observed 0 °C isotherm. This northward shift highlights the differential warming rates between the northern and southern regions. Overall, the analysis confirms a robust warming trend, with notable fluctuations in January’s temperatures since 1998, suggesting the Mts. Qinling’s emerging role as a climatic divider in the Chinese Mainland. This introduces new challenges for regional ecosystems, agricultural production, and water resource management, highlighting the pressing need to advance regional sustainable development in the face of climate change.

Saltwater intrusion simulations in coastal karstic aquifers related to climate change scenarios

Coastal zones are crucial ecosystems supporting significant biodiversity and pertinent socio-economic activities. However, anthropogenic development contributes to socio-environmental complexities, particularly public water supply threats caused by climate change. This research presents a case study on the north-western coast of Yucatan, Mexico, which models potential saltwater intrusion in groundwater for multiple projections of sea level rise and recharge change due to climate change and its implications for the public water supply of the regional population and ecosystem. For this purpose, a previously calibrated and validated numerical model is employed, adapting its boundary conditions, keeping its calibrated hydrogeologic parameters, and considering the 2040 and 2100 climate change projections. Simulation results show that under these projections, significant saltwater intrusion may occur, reducing freshwater thickness due to increased salinity in groundwater and a loss of freshwater sources resulting from brackish-saline wedge intrusion. These scenarios are of particular concern as freshwater in this coastal region is the main source for public water supply and for freshwater input in coastal ecosystems. Moreover, this study underscores the susceptibility of karstic aquifers to salinization, especially in the face of rising sea levels, given their unique hydrogeological characteristics and substantial responsiveness to marine forcings. In spite of the uncertainties in global climate change predictions, this study enhances our understanding of the dynamics of these unique aquifers, and presents future saltwater intrusion projections that offer valuable technical insights to design and implement pertinent and resilient coastal aquifer management strategies.

Anomalous wet summers and rising atmospheric CO2 concentrations increase the CO2 sink in a poorly drained forest on permafrost

At the northern high latitudes, rapid warming, associated changes in the hydrological cycle, and rising atmospheric CO2 concentrations, [CO2], are observed at present. Under rapid environmental changes, it is important to understand the current and future trajectories of the CO2 budget in high-latitude ecosystems. In this study, we present the importance of anomalous wet conditions and rising [CO2] on the long-term CO2 budget based on two decades (2003-2022) of quasicontinuous measurements of CO2 flux at a poorly drained black spruce forest on permafrost peat in interior Alaska. The long-term CO2 budget for the black spruce forest was a small sink of -53 ± 63 g C m-2 y-1. The CO2 sink increased from 49 g C m-2 y-1 for the first decade to 58 g C m-2 y-1 for the second decade. The increased CO2 sink was attributed to an 11.3% increase in gross primary productivity (GPP) among which 9% increase in GPP was explained by a recent increase in precipitation. Furthermore, a 3% increase in GPP in response to a 37-ppm increase in [CO2] was estimated from the data-model fusion. Our study shows that understanding the coupling between hydrological and carbon cycles and the CO2 fertilization effect is important for understanding the current and future carbon budgets of high-latitude ecosystems in permafrost regions.

Is a balanced entrepreneurial ecosystem essential for success? A configurational analysis of European regional entrepreneurial ecosystems

Is a balanced entrepreneurial ecosystem essential for success? A configurational analysis of European regional entrepreneurial ecosystems

A novel multi-criteria decision making method to evaluate green innovation ecosystem resilience

Green innovation ecosystem resilience evaluation is crucial for ensuring sustainable development in dynamic environments. By comprehensively assessing resilience, it helps identify risks and facilitate effective responses, thus promoting sustainable development. To effectively evaluate the resilience of green innovation ecosystems, this paper proposes a model based on the interval-valued intuitionistic fuzzy multi-criteria decision-making (MCDM) method, designed to support decision-makers (DMs) in resilience evaluation. In this model, we improve the Criteria Importance Through Intercriteria Correlation (CRITIC) method by introducing Spearman's correlation coefficient to more accurately determine the objective weights of various indicators based on their interrelationships. Furthermore, we propose an Interval-Valued Intuitionistic Fuzzy Hybrid Average Aggregation (IVIFHAA) operator, which considers both the subjective and objective weight order for aggregating expert evaluation results. Additionally, a scoring function is introduced to generate ranked evaluation results. We also establish a resilience evaluation criteria system covering interconnectivity, sustainability, and diversity within green innovation ecosystems to assist DMs in resilience evaluation. Finally, to validate this method, we apply it to assess the resilience of regional green innovation ecosystems and compare it with other methods. The results demonstrate that the improved operator effectively reduces information loss and improves evaluation efficiency, while the improved CRITIC method handles outliers during the evaluation process.

Spatial optimization strategies for China’s hydrogen infrastructure industry chain

Promoting the development of China’s hydrogen energy industry is crucial for achieving green energy transition. However, existing research lacks systematic studies on the spatial layout of the hydrogen industry chain. This study constructed a comprehensive theoretical framework encompassing hardware infrastructure, software systems, and soft power. Using multi-source heterogeneous data, GIS analysis, and NVivo text coding methods, the current regional layout and challenges of China’s hydrogen infrastructure industry chain were systematically evaluated. The findings determined that economically developed eastern regions lead in infrastructure and soft power, while central and western regions leverage their resource and manufacturing advantages. Major challenges include regional imbalances in hardware infrastructure, uneven distribution of soft power, and misalignment between software systems and actual needs. Analysis of the “14th Five-Year Plan” of various regions elucidated deep insights into the diversity of local hydrogen energy development strategies, identifying five types of hydrogen cities: resource-advantaged, market-oriented, regionally collaborative, innovation-driven, and policy-supported. Accordingly, strategies to enhance industry chain synergy, clarify city roles, and optimize regional ecosystems were proposed. It is recommended to integrate hydrogen infrastructure with urban planning and incorporate environmental impact assessments into spatial optimization decisions. This study provides a systematic analytical framework and progressive policy recommendations for the efficient and green layout of China’s hydrogen infrastructure, offering important implications for the sustainable development of the hydrogen industry and other rapidly developing economies.

How to Achieve the Ecological Sustainability Goal of Ecologically Fragile Areas on the Qinghai-Tibet Plateau: A Multi-Scenario Simulation of Lanzhou-Xining Urban Agglomerations

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future.

Living labs as orchestrators in the regional innovation ecosystem: a conceptual framework

ABSTRACT This research explores the conceptual integration of Living Labs (LLs) into the Regional Innovation Ecosystem (RIE) to understand their potential as facilitators of Responsible Innovation. While previous studies explored the role of Living Labs, they lack comprehensive integration strategies for addressing wicked problems. A conceptual framework is developed to understand the main role, detailed functions, and key elements for integration. Seven expert interviews were conducted to develop the conceptual framework, using the Interuniversity Microelectronics Centre (imec) within the Flemish Innovation Ecosystem as empirical context. The findings emphasise Living Labs as central orchestrators, enabling user-centric innovation, real-world experimentation, and stakeholder engagement. We identify four key elements that facilitate the proposed integration: government policy and funding, strategic integration, formal collaborations, and proof of concept. These findings have implications for advancing the theoretical understanding of Living Labs' integration into the Regional Innovation Ecosystem, and for practitioners who aim to foster Responsible Innovation.