Trade-off Model Research Articles

Sub-District Level Spatiotemporal Changes of Carbon Storage and Driving Factor Analysis: A Case Study in Beijing

Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area and introduces a framework that combines the Markov model, the Patch-based Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess carbon storage at the sub-district level. This framework allows for a systematic analysis of land use and carbon storage spatiotemporal evolution in Beijing from 2000 to 2020, including the influence of driving factors on carbon storage. Moreover, it enables the simulation and prediction of land use and carbon storage changes in Beijing from 2025 to 2040 under various scenarios. The results show the following: (1) From 2000 to 2020, the overall land use change in Beijing showed a trend of “Significant decrease in cropland area; Forest increase gradually; Shrub and grassland area increase first and then decrease; Decrease and then increase in water; Impervious expands in a large scale”. (2) From 2000 to 2020, the carbon storage in Beijing showed a “decrease-increase” fluctuation, with an overall decrease of 1.3 Tg. In future carbon storage prediction, the ecological protection scenario will contribute to achieving the goals of carbon peak and carbon neutrality. (3) Among the various driving factors, slope has the strongest impact on the overall carbon storage in Beijing, followed by Human Activity Intensity (HAI) and Nighttime Light Data (NTL). In the analysis of carbon storage in the built-up areas, it was found that HAI and DEM (Digital Elevation Model) have the strongest effect, followed by NTL and Fractional Vegetation Cover (FVC). The findings from this study offer valuable insights for the sustainable advancement of ecological conservation and urban development in Beijing.

Assessment of Pluvial Flood Mitigation Ecosystem Service in a Riverside City Using the Integrated Valuation of Ecosystem Services and Tradeoffs Model for Ecological Corridor Mapping

Assessment of Pluvial Flood Mitigation Ecosystem Service in a Riverside City Using the Integrated Valuation of Ecosystem Services and Tradeoffs Model for Ecological Corridor Mapping

Age-dependent decline in sperm quality and function in a naturally short-lived vertebrate

Maximizing the life-long reproductive output would lead to the prediction that short-lived and fast aging species would undergo no – if any – reproductive senescence. Turquoise killifish (Nothobranchius furzeri) are naturally short-lived teleosts, and undergo extensive somatic aging, characterized by molecular, cellular, and organ dysfunction following the onset of sexual maturation. Here, we tested whether naturally short-lived and fast aging male turquoise killifish maximize reproduction and display minimal – if any, reproductive senescence. We analysed age-related changes in sperm traits, the proportion of fertilized eggs, as well as embryo survival. Contrary to the expectation of no reproductive aging, we found that turquoise killifish males undergo extensive reproductive aging, consisting in the age-dependent decline in sperm quality, decreased proportion of fertilized eggs and lower embryo survival. Our results indicate that male turquoise killifish do not trade-off age-dependent soma decline with life-long sustained reproductive fitness. Instead, somatic and reproductive aging appear to occur simultaneously. Our findings question generalized soma vs. reproductive senescence trade-off models and highlight the importance of integrating species-specific ecological and demographic constraints to explain observed life history traits.

An exact bandit model for the risk-volatility tradeoff

An exact bandit model for the risk-volatility tradeoff

Carbon Storage Response to Land Use/Land Cover Changes and SSP-RCP Scenarios Simulation: A Case Study in Yunnan Province, China.

Changes in terrestrial ecosystem carbon storage (CS) affect the global carbon cycle, thereby influencing global climate change. Land use/land cover (LULC) shifts are key drivers of CS changes, making it crucial to predict their impact on CS for low-carbon development. Most studies model future LULC by adjusting change proportions, leading to overly subjective simulations. We integrated the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, the Patch-generating Land Use Simulation (PLUS) model, and the Land Use Harmonization 2 (LUH2) dataset to simulate future LULC in Yunnan under different SSP-RCP scenarios of climate and economic development. Within the new PLUS-InVEST-LUH2 framework, we systematically analyzed LULC alterations and their effects on CS from 1980 to 2040. Results demonstrated that: (1) Forestland had the highest CS, whereas built-up land and water showed minimal levels. Western areas boast higher CS, while the east has lower. From 1980 to 2020, CS continuously decreased by 29.55 Tg. In the wake of population increase and economic advancement, the area of built-up land expanded by 2.75 times. Built-up land encroaches on other land categories and is a key cause of the reduction in CS. (2) From 2020 to 2040, mainly due to an increase in forestland, CS rose to 3934.65 Tg under the SSP1-2.6 scenario, whereas under the SSP2-4.5 scenario, primarily due to a reduction in forestland and grassland areas, CS declined to 3800.86 Tg. (3) Forestland is the primary contributor to CS, whereas the ongoing enlargement of built-up land is causing a sustained decline in CS. Scenario simulations indicate that future LULC changes under different scenarios will have a significant impact on CS in Yunnan. Under a green sustainable development pathway, Yunnan can exhibit significant carbon sink potential. Overall, this research offers a scientific reference for optimizing land management and sustainable development in Yunnan, aiding China's "double carbon" goals.

Integrating river transport processes and seasonal dynamics to assess watershed nitrogen export risk.

Excessive nitrogen exported to water bodies affects the balance of ecosystem and poses a threat to human health. Although the concept of water purification service helps quantify nitrogen export, the impact of river transport remains unclear. This study focused on nitrogen as a pollutant by utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess nitrogen export in the Dongting Lake Basin, taking into account both the processes of sub-basin nitrogen export and river transport. Additionally, the monthly variations within the year were further explored, together with the identification of the priority area of returning cropland to forest land. The results showed that in 2021, the total nitrogen load outside the Dongting Lake was 11.34×108 kg·year-1, with the sub-basins retaining a total of 9.02×108 kg·year-1, accounting for 79.57% of the total nitrogen load. Notably, the total nitrogen retention by the river made up 16.87% of the total nitrogen retention, up to 1.83×108 kg·year-1. In view of monthly variation, water purification service based on the entire process was higher in winter and late autumn, and lower in summer and early autumn. The priority areas for ecological project were mainly distributed around the Dongting Lake, achieving an improvement of 58.15% in water purification service with approximately 7.02% of the total returnable cropland. This study proposed a new approach of water purification service assessment through integrating river transport processes and seasonal dynamics, aiming to assess watershed nitrogen export risk more accurately.

Spatiotemporal Changes in Ecological Network Structure and Enhancing Territorial Space Management in Guilin, China

Accelerated urbanization and the excessive exploitation of the tourism industry are leading to a diminution of ecological spaces in tourist cities. Ecological networks are an effective method for improving patch connectivity and maximizing ecological space. However, previous research on ecological networks predominantly focuses on static snapshots, ignoring the fact that ecological networks are landscape entities with considerable spatiotemporal and structural dynamics changes. To fill this gap, we first constructed ecological networks of Guilin in 1990, 2000, 2010, and 2020, employing the integrated valuation of ecosystem services and tradeoffs (InVEST) model, the morphological spatial pattern analysis (MSPA) method, and circuit theory. Subsequently, we analyzed the spatiotemporal evolution of the ecological networks and proposed strategies for improving territorial space management. The results showed that ecological sources and corridors were generally decreasing in both number and areas (length), coupled with a notable increase in the number of ecological pinch points and barriers over the 30-year period. The spatiotemporal dynamics of ecological corridors, pinch points, and barriers were associated with ecological sources. Structural evaluation of the ecological networks revealed that during 1990~2020, the value of α (network closure) exceeded 0.7, the value of β (line point rate) surpassed 2, and the value of γ (network connectivity) was greater than 0.8, indicating robust overall connectivity within the ecological networks. The observed decline in these three indicators over time suggested a reduction in connectivity and the available dispersal pathways for species within the ecological networks, highlighting the need for protective measures and optimization strategies. Consequently, the ecological network conservation strategies and the development of ecological patterns were proposed to enhance ecological space management in Guilin. This study addresses a critical knowledge gap in the dynamics of ecological networks and offers valuable insights for mitigating habitat fragmentation and enhancing ecological space management of tourist cities.

Assessment of dynamic water yield using multi scenario of LULC in Cisadane Watershed West Java, Indonesia

Uncontrolled economic development often leads to land degradation, a decline in ecosystem services, and negative impacts on community welfare. This study employs water yield (WY) modeling as a method for environmental management, aiming to provide a comprehensive understanding of the relationship between Land Use Land Cover (LULC), Land Use Intensity (LUI), and WY to support sustainable natural resource management in the Cisadane Watershed, Indonesia. The objectives include: (1) analyzing changes in WY for 2010, 2015, and 2021; (2) predicting WY for 2030 and 2050 under two scenarios—Business as Usual (BAU) and Protected Forest Area (PFA); (3) assessing the impacts of LULC and climate change on WY; and (4) exploring the relationship between LUI and WY. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model calculates actual and predicted WY conditions, while the Coupling Coordination Degree (CCD) analyzes the LULC-WY relationship. Results indicate that the annual WY in 2021 was 215.8 × 108 m³, reflecting a 30.42% increase from 2010. Predictions show an increasing trend in WY under both scenarios for 2030 and 2050 with different magnitudes. Rainfall contributes 88.99% more dominantly to WY than LULC. Additionally, around 50% of districts exhibited unbalanced coordination between LUI and WY in 2010 and 2020. This study reveals the importance of ESs in sustainable watershed management amidst increasing demand for natural resources due to population growth.

Regression with reduced rank predictor matrices: A model of trade-offs.

A regression model of predictor trade-offs is described. Each regression parameter equals the expected change in Y obtained by trading 1 point from one predictor to a second predictor. The model applies to predictor variables that sum to a constant T for all observations; for example, proportions summing to T = 1.0 or percentages summing to T = 100 for each observation. If predictor variables sum to a constant T for all observations and if a least squares solution exists, the predicted values for the criterion variable Y will be uniquely determined, but there will be an infinite set of linear regression weights and the familiar interpretation of regression weights does not apply. However, the regression weights are determined up to an additive constant and thus differences in regression weights βv-βv∗ are uniquely determined, readily estimable, and interpretable. βv-βv∗ is the expected increase in Y given a transfer of 1 point from variable v∗ to variable v. The model is applied to multiple-choice test items that have four response categories, one correct and three incorrect. Results indicate that the expected outcome depends, not just on the student's number of correct answers, but also on how the student's incorrect responses are distributed over the three incorrect response types. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The emergence of nonlinear evolutionary trade-offs and the maintenance of genetic polymorphisms.

Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modellers to specify a function linking trait values. The choice of trade-off function can be consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to genetic polymorphisms. Despite their importance, our current theory has little to say on which trade-off functions are the most biologically plausible. To address this gap, we explored how the genetic determination of quantitative traits can lead to different trade-off functions, using resistance to infectious diseases as an example trait. We developed a model where alleles at separate loci pleiotropically increase resistance while decreasing fecundity. We then used this model to generate genotype landscapes and investigate how epistasis effects the trade-off function. Regardless of the strength of epistasis, our model consistently led to accelerating costs. We then incorporated our genotype model into an eco-evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously thought.

Optimization of ecological network to improve water conservation services in the Nianchu River Basin

Against the backdrop of water resource depletion in the Qinghai-Tibet Plateau, water conservation services (WCS) have emerged as critical ecosystem services warranting attention. Adjusting the ecological network (EN) structure and optimizing topological relationships among landscape elements are instrumental in facilitating ecological processes, constituting an effective approach for enhancing WCS. We employed the Integrated Valuation of Ecosystem Services and Tradeoffs model to simulate the WCS value in the Nianchu River Basin and used the Minimum Cumulative Resistance model in combination with the Linkage Mapper to construct an EN. Through topological analysis based on complex network theory, we examined the EN topology and identified ecological pinch points and barriers by applying circuit theory. According to the correlation between EN topology and WCS, and taking into account local vegetation restoration potential, we ultimately optimized the EN to enhance the WCS value. The results revealed a positive correlation between the WCS value and betweenness centrality (r = 0.86, p < 0.01) of forest patches, as well as with the clustering coefficient of grassland patches (r = 0.44, p < 0.05). Following the optimization of key areas with restoration potential, we enhanced the EN structure by adding six new patches, eliminating four redundant corridors, and establishing 11 new corridors. The optimized EN demonstrated enhanced stability in robustness tests, indicated by a reduced slope of edge recovery against malicious attacks (from −0.0224 to −0.0199) and an increase in the WCS value of 630,311.6 m³. This study highlights the importance of landscape spatial structure in enhancing ecosystem services, providing valuable insights for sustainable water resource management in the ecologically sensitive regions of the Qinghai-Tibet Plateau.

Assessing the Interaction Impacts of Multi-Scenario Land Use and Landscape Pattern on Water Ecosystem Services in the Greater Bay Area by Multi-Model Coupling

Water ecosystem services (WESs) are intrinsically associated with the livelihood of urban residents and are frequently disrupted by human activities. Land use and landscape patterns are key driving factors of alterations in WESs. However, existing research primarily quantifies single-factor influences and often overlooks the interactions between these factors. This study addresses this gap by employing a multi-model coupling approach, integrating the Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and Geographical Detector (GD) models alongside various indicators to analyse the evolution of land use, landscape patterns and WESs in the Greater Bay Area from 2000 to 2020, and to simulate spatio-temporal change patterns in different scenarios from 2030 to 2050. Additionally, this study examines the multi-factorial interactions between land use, landscape patterns, and WESs. The results indicate that (1) urbanisation steadily increased, leading to intensified landscape fragmentation, and water yield (WY) and total phosphorus (TP) consistently increased, while total nitrogen (TN) in water gradually decreased; (2) urban areas exerted the most significant impact on WY in the Greater Bay Area while Patch density (PD) had a stronger influence on WY, and Shannon’s diversity index (SHDI) had the most pronounced effect on TN and TP; (3) the interaction between any two land-use types or landscape indices exerted a greater impact on WESs compared with the impact of individual factors alone. The interaction between urban areas and cropland substantially influenced WY (q¯ = 0.634) and most strongly affected TN and TP in water (q¯ = 0.74 and 0.73, respectively). SHDI and PD had the most significant impact on WY in the economic development scenario (q¯ = 0.19) and exhibited the greatest influence on the TN and TP levels in the ecological priority scenario (q¯ = 0.12 and 0.15, respectively). Our findings can provide theoretical and technical support for the integrated scientific planning of regional water ecosystems and the development of comprehensive land use policies in the future.

Research on the coupled evolution of LULCC and habitat quality in the Ganqing section of the Yellow River Basin based on multi-scenario simulations

IntroductionThis study focuses on the Ganqing section of the Yellow River Basin, exploring four land use scenarios: natural development, cropland protection, ecological protection, and rapid development. Given the ecological importance of this area, the research aims to evaluate how each scenario impacts habitat quality and land use sustainability by 2030.MethodsThe Future Land Use Simulation (FLUS) model and the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) model were applied to simulate land use for each scenario. A habitat quality pattern and coupling coordination degree model was used to assess the interactions between land use and land cover change (LULCC) and habitat quality under different scenarios.ResultsFindings show that over 70% of the Ganqing section of the Yellow River Basin is primarily grassland. By 2030, the ecological protection scenario is predicted to have the highest habitat quality, followed by the natural development, rapid development, and cropland protection scenarios. Between 1990 and 2030, the area demonstrates predominantly high or moderate coordination between land use and habitat quality. Spatial analysis reveals lower coordination values in the southeast and higher values in the northwest, with imbalanced recession zones distributed around valley basins.DiscussionThis study highlights the value of strategic scenario planning in enhancing habitat quality and promoting sustainable land management in the Ganqing section of the Yellow River Basin. The ecological protection scenario shows the most promise for balancing development with habitat preservation, underscoring the importance of adopting land use policies that support ecological sustainability in vulnerable areas.

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 −0.0334, 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.

Integrated spatial prioritization of urban nature-based solutions for climate adaptation, mitigation, and justice

ABSTRACT In densely populated cities, people confront multiple impacts of climate change, including stormwater runoff, flooding, heat waves, and health issues. To address these impacts, nature-based solutions (NbS) have gained significant attention in recent years due to their potential to contribute to sustainability, resilience, and ecosystem services. Nevertheless, more research is required to understand the wider potential of NbS and to identify priority areas for their deployment. This study developed an analytical approach and implemented it in the Tehran Metropolitan Area (TMA) by considering factors related to NbS co-benefits. The approach included spatial prioritization, spatial correlation analysis, and suitability analysis. It combines a Geographic Information System, Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, Zonation, Best-Worst Method, Bivariate Local Indicator of Spatial Autocorrelation analysis (BiLISA), a Fuzzy Inference System, and Boolean overlay analysis. The results include maps showing priority areas for different types of NbS and spatial co-benefits and mismatches. High-priority areas are located in disadvantaged areas. In total, 105.73 km2 (17% of the TMA) was designated as highly prioritized. We show that various NbS interventions are applicable, with green roofs and rainwater harvesting being the most feasible. This study can assist decision-makers in optimizing NbS to deliver maximum co-benefits.

Land use modeling and carbon storage projections of the Bosten Lake Basin in China from 1990 to 2050 across multiple scenarios

Given the escalating issue of global climate change, it is imperative to comprehend and quantify the effects of land use change on carbon storage (CS), which pertains not only to the preservation of ecosystem functions but also directly influences the equilibrium and stability of the global carbon cycle. This study examines the correlation between CS and land use change, forecasts the future spatial distribution of CS, and offers a reference for the rational planning of watershed space. Focusing on the Bosten Lake Basin of Xinjiang in China, employing the land use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model to forecast the spatial distribution of carbon stocks across three developmental scenarios, while also examining the shift in the center of gravity of CS and the autocorrelation of their spatial distribution. The findings derived from the study are as follows: (1) From 1990 to 2020, the predominant land use type in the Bosten Lake Basin was grassland, while there was an upward trend in the areas of cropland, forest land, built-up land, and wetland, alongside a downward trend in the areas of grassland, water, and unused land. (2) In the long term, the regional CS exhibits an upward trend, with the most significant increase anticipated in the EPS scenario. Grassland constitutes the most extensive carbon reservoir in the Bosten Lake Basin, while wetlands exhibit the highest carbon sequestration potential. (3) The alteration in the center of gravity of CS is associated with the expansion or reduction of the major regional carbon reservoirs and types characterized by significant carbon sequestration potential. (4) In the long term, the spatial correlation of CS in the Bosten Lake Basin exhibits a consistent upward trend, with the most pronounced spatial correlation observed under EPS.

Quantifying the Effect of Land Use and Land Cover Changes on Spatial-Temporal Dynamics of Water in Hanjiang River Basin

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by 96.275×108t, 81.210×108t, and 84.13×108t relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply.

Eco-evolutionary dynamics of structured populations in periodically fluctuating environments: a G function approach.

Understanding the ecological and evolutionary dynamics of populations is critical for both basic and applied purposes in a variety of biological contexts. Although several modeling frameworks have been developed to simulate eco-evolutionary dynamics, many fewer address how to model structured populations. In a prior paper, we put forth the first modeling approach to simulate eco-evolutionary dynamics in structured populations under the G function modeling framework. However, this approach does not allow for accurate simulation under fluctuating environmental conditions. To address this limitation, we draw on the study of periodic differential equations to propose a modified approach that uses a different definition of fitness more suitable for fluctuating environments. We illustrate this method with a simple toy model of life history trade-offs. The generality of this approach allows it to be used in a variety of biological contexts.

Mapping Biodiversity Conservation Priorities for Protected Areas for Spatial Optimization: A Case Study in the Songnen Plain, China.

The decline in biodiversity poses a serious threat to natural ecosystems and has become one of the most pressing global environmental issues. Establishing conservation priorities for protected areas (PAs) is one of the most direct and effective biodiversity conservation measures. However, conservation gaps arise as a result of existing problems in spatial layout of PAs, including overlapping protection scopes, artificial fragmentation of natural ecological regions, as well as "over-protection" and "over-exploitation." To optimize the spatial layout of PAs and improve the efficiency of biodiversity conservation, we employed the Habitat Quality module of the Integrated Assessment of Ecosystem Services and Tradeoffs (InVEST) model and the Maximum Entropy (MaxEnt) model to assess the PAs in the Songnen Plain, China. The combined model (MaxEnt-InVEST) revealed that the conservation priorities for PAs in the Songnen Plain occupied a total area of 14,764.14 km2 (10.24% of the total area of the Songnen Plain). The conservation priorities outside PAs occupied a total area of 7858.45 km2 (5.45% of the total area of the Songnen Plain) and were primarily distributed in the northeastern, central, and southwestern regions of the Songnen Plain. This indicated that existing PAs did not offer adequate protection for local biodiversity. The consistency of our combined modeling framework was 72.11%, which enabled a more accurate assessment of biodiversity hotspots and respects the land uses of the Songnen Plain. In addition, the modeling framework successfully created maps of conservation gaps of biodiversity hotspots based on actual species distribution data and considers current land uses. Our study was aimed at optimizing the spatial conservation efficiency of the Songnen Plain by assessing the conservation gaps in the Songnen Plain. It could provide a reference for the future development of a PA system centering on national parks.

Analyst cliques coverage and the speed of leverage adjustment: Evidence from China

This study examines how analyst cliques influence firm leverage adjustment by investigating the potential echo chamber effect within complex analyst networks. Using a multilayer network framework based on information exchanges—such as teammate cooperation, cross-team communication, and stock co-coverage—we apply the Louvain algorithm to identify analyst cliques, where analysts are likely to have similar perspectives. Our findings indicate that firms covered by a higher number of analyst cliques experience slower leverage adjustment. This result remains consistent after addressing potential endogeneity concerns. The delay in leverage adjustment is attributed to the echo chamber effect within cliques, where analysts share homogeneous views that significantly diverge from those of other cliques, creating a chaotic information environment. Furthermore, from the perspective of moderating effect, we find that the negative effects of analyst cliques on leverage adjustment become more pronounced in firms with weaker governance structures and higher financing constraints. This research offers new insights into the relationship between the information environment and leverage adjustment within the dynamic trade-off model, providing valuable implications for regulators and investors in understanding the role of analyst networks in emerging financial markets.