Future Projects Research Articles

Differential Water Conservation Capacity in Broadleaved and Mixed Forest Restoration in Latosol Soil-Eroded Region, Hainan Province, China.

The water conservation capacity of the litter and soil layers of forest ecosystems improves the function of forest ecosystems in conserving soil and water. Plantation restoration plays a key role in preventing soil erosion. In order to evaluate the water conservation capacity of plantation restoration in Latosol soil-eroded region, we analyzed the litter thickness and mass, water absorption process, water holding recovery process, and soil water holding capacity of five restoration types (Hevea brasiliensis, Acacia mangium, Eucalyptus robusta, Acacia-Eucalyptus, and Acacia-Hevea) in the Mahuangling Watershed, Hainan province. The results showed that the thickness of the litter ranged from approximately 3.42 ± 0.24 to 4.73 ± 0.81 cm, and the litter mass ranged from 5.04 ± 1.52 t·ha-1 to 13.16 ± 1.76 t·ha-1, with higher litter mass in the SL layer than in the UL layer. The litter mass of A. mangium was higher than that of H. brasiliensis, E. robusta, Acacia-Eucalyptus, and Acacia-Hevea, which was 3.16 ± 1.76 t·ha-1. A. mangium forest was significantly higher than other plantation restoration types in terms of the maximum water retention capacity (Qmax) and the effective water retention capacity (Qeff). The soil bulk weight ranged from approximately 1.52 ± 0.09 to 1.59 ± 0.08 g·cm-3, and porosity ranged from 31.77 ± 4.72 to 35.62 ± 3.02%, both of which increased with the depth of the soil layer. The water holding capacity of 0-60 cm soil varied from approximately 12.94 ± 7.91 to 45.02 ± 31.79 t·ha-1, with A. mangium having the best soil permeability and the strongest soil water holding capacity. The entropy weight method was used to conduct a comprehensive evaluation, and the results showed that the water conservation capacity of the soil layer was 1.26 times higher than that of the litter layer, in which the water conservation capacity of A. mangium was the strongest, with a comprehensive evaluation value of 0.2854, which effectively intercepted rainfall and reduced surface runoff. Hence, we suggest that the planting of A. mangium should be considered in future ecological restoration projects of the erosion area of Mahuangling in order to improve the function of conserving soil and water in a restoration forest ecosystem.

Relation between beluga whale aggregations and sea temperature on climate change forecasts

Climate change has been shown to alter the spatial distribution of whales and other marine mammals. Fast changing ocean temperatures may also affect the spatial distribution of whales at a finer scale, namely within populations, including aggregation behaviour. Our ability to analyze the impact of climate change on whale aggregation behavior, however, has been limited by our ability to collect spatial observation data over large areas. To overcome this limitation, this study analyzed open-access satellite imagery obtained between 2007 and 2020 in Canada, Russia, and Alaska using Deep Convolutional Neural Networks (CNN) to detect 1,980 beluga whales in 11 populations and to quantify their aggregation patterns within their populations. Subsequently, we examined the relationship between sea surface temperature (SST) and the intra-population spatial patterns of beluga whales during summer seasons, when these whales normally aggregate. We detected a negative correlation between SST and the frequency of beluga whale aggregation, suggesting that warming temperatures may impact beluga whale spatio-behavioral dynamics. Considering that the relative abundance of beluga whales is declining and the future SST projections in these Arctic Ocean locations, climate change may pose yet another threat to beluga whales and other ice-dependent species.

Emergent constraints on carbon budgets as a function of global warming

Earth System Models (ESMs) continue to diagnose a wide range of carbon budgets for each level of global warming. Here, we present emergent constraints on the carbon budget as a function of global warming, which combine the available ESM historical simulations and future projections for a range of scenarios, with observational estimates of global warming and anthropogenic CO2 emissions to the present day. We estimate mean and likely ranges for cumulative carbon budgets for the Paris targets of 1.5 °C and 2 °C of global warming of 812 [691, 933] PgC and 1048 [881, 1216] PgC, which are more than 10% larger than the ensemble mean values from the CMIP6 models. The linearity between cumulative emissions and global warming is found to be maintained at least until 4 °C, and is consistent with an effective Transient Climate Response to Emissions (eTCRE) of 2.1 [1.8, 2.6] °C/1000PgC, from a global warming of 1.2 °C onwards.

Integrated project delivery (IPD) capabilities on reducing claims in urban underground projects: A hybrid FAHP-FTOPSIS approach

Participatory planning practices - associated with integrated project delivery (IPD) can influence the cost and time claims of construction projects. However, there is a lack of research providing a quantitative holistic assessment of implementing IPD practices for reducing claims. In order to fill this knowledge gap, the present study aims to present a hybrid prioritization model to assess and mitigate the impact of claims on urban underground projects using IPD capabilities. The fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) methods are combined to prioritize traditional project delivery systems claims and rank IPD capabilities to reduce critical claims. FAHP identifies eight critical claims, including incorrect selection of the project contract system, lack of use of legal experts in setting contracts, exchange rate fluctuations and changes in currency conditions, lack of manpower skilled personnel in the region, ambiguities and shortcomings in the contract, restrictions on the supply of materials, machinery and equipment, delays in payments and financial obligations of the employer and lack of equipment and machinery appropriate to the type of work in the region. FTOPSIS ranks organizational and leadership, planning enhancement, and appropriate technology as the most effective capabilities in reducing claims. These capabilities should be implemented according to the obtained ranking to accept IPD in reducing the conventional claims future projects. The main innovation lies in the development of a hybrid prioritization framework to evaluate conventional contractual claims and rank IPD capabilities. The framework proposed in the study provides a valuable tool for construction managers to make informed decisions and mitigate the impact of contractual claims during the project delivery phase.

Using Free Air CO2 Enrichment data to constrain land surface model projections of the terrestrial carbon cycle

Abstract. Predicting the responses of terrestrial ecosystem carbon to future global change strongly relies on our ability to model accurately the underlying processes at a global scale. However, terrestrial biosphere models representing the carbon and nitrogen cycles and their interactions remain subject to large uncertainties, partly because of unknown or poorly constrained parameters. Parameter estimation is a powerful tool that can be used to optimise these parameters by confronting the model with observations. In this paper, we identify sensitive model parameters from a recent version of the ORgainzing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model that includes the nitrogen cycle. These sensitive parameters include ones involved in parameterisations controlling the impact of the nitrogen cycle on the carbon cycle and, in particular, the limitation of photosynthesis due to leaf nitrogen availability. We optimise these ORCHIDEE parameters against carbon flux data collected on sites from the FLUXNET network. However, optimising against present-day observations does not automatically give us confidence in future projections of the model, given that environmental conditions are likely to shift compared to the present day. Manipulation experiments give us a unique look into how the ecosystem may respond to future environmental changes. One such type of manipulation experiment, the Free Air CO2 Enrichment (FACE) experiment, provides a unique opportunity to assess vegetation response to increasing CO2 by providing data under ambient and elevated CO2 conditions. Therefore, to better capture the ecosystem response to increased CO2, we add the data from two FACE sites to our optimisations, in addition to the FLUXNET data. We use data from both CO2 conditions of FACE, which allows us to gain extra confidence in the model simulations using this set of parameters. We find that we are able to improve the magnitude of modelled productivity. Although we are unable to correct the interannual variability fully, we start to simulate possible progressive nitrogen limitation at one of the sites. Using an idealised simulation experiment based on increasing atmospheric CO2 by 1 % yr−1 over 100 years, we find that optimising against only FLUXNET data tends to imply a large fertilisation effect, whereas optimising against FLUXNET and FACE data (with information about nutrient limitation and acclimation of plants) decreases it significantly.

Sensitivity of Rainfall Extremes to Unprecedented Indian Ocean Dipole Events

AbstractStrong positive Indian Ocean Dipole (pIOD) events like those in 1997 and 2019 caused significant flooding in East Africa. While future projections indicate an increase in pIOD events, limited historical data hinders a comprehensive understanding of these extremes, particularly for unprecedented events. To overcome this we utilize a large ensemble of seasonal reforecast simulations, which show that regional rainfall continues to increase with pIOD magnitude, with no apparent limit. In particular we find that extreme rain days are highly sensitive to the pIOD index and their seasonal frequency increases super‐linearly with higher pIOD magnitudes. It is vital that socio‐economic systems and infrastructure are able to handle not only the increasing frequency of events like 1997 and 2019 but also unprecedented seasons of extreme rainfall driven by as‐yet‐unseen pIOD events. Future studies should prioritize understanding the hydrological implications and population exposure to these unprecedented extremes in East Africa.

Predictive analytics in climate finance: Assessing risks and opportunities for investors

Predictive analytics is increasingly recognized as a pivotal tool in climate finance, offering investors invaluable insights into both the risks posed by climate change and the opportunities for sustainable investment. This Review delves into the burgeoning field of predictive analytics within climate finance, emphasizing its significance in aiding investors to navigate the multifaceted landscape of climate-related risks and opportunities. By leveraging advanced data analytics techniques, predictive analytics empowers investors to anticipate and mitigate climate-related risks, ranging from physical risks such as extreme weather events and sea-level rise to transition risks associated with regulatory changes and technological shifts. Moreover, predictive analytics enables investors to identify emerging opportunities in sectors poised for sustainable growth, such as renewable energy, clean technology, and climate resilient infrastructure. This Review also sheds light on the methodologies and data sources utilized in predictive analytics for climate finance, encompassing climate models, satellite imagery, socioeconomic indicators, and financial data. Through the analysis of historical trends and future projections, predictive analytics provides investors with actionable insights to inform their investment decisions and align their portfolios with climate-related goals and mandates. Despite its potential benefits, the adoption of predictive analytics in climate finance is not without challenges. This Review examines the hurdles associated with data quality, model uncertainty, regulatory complexities, and the integration of climate-related factors into financial decision-making processes. Addressing these challenges necessitates interdisciplinary collaboration, robust risk assessment frameworks, and ongoing innovation in predictive analytics methodologies. In conclusion, this Review underscores the critical role of predictive analytics in climate finance and its transformative potential in enhancing the resilience and sustainability of investment portfolios. By harnessing the power of data-driven insights, investors can proactively manage climate-related risks, capitalize on sustainable investment opportunities, and contribute to the transition towards a low-carbon economy. As climate change continues to exert profound impacts on financial markets, the integration of predictive analytics represents a strategic imperative for investors seeking to navigate the evolving landscape of climate finance effectively.

Determining sediment deposition dynamics influenced by check dams in a semi‐arid mountainous watershed

AbstractSemi‐arid environments are characterized by infrequent large magnitude rainfalls that produce flash flood events with high sediment concentration. Control structures such as check dams are widely used in this environment for mitigation. However, their impact on the overall sediment balance of watersheds, particularly those severely affected by anthropogenic activity, is sparsely documented. This study used topographic measurements, sediment analysis, and fallout isotope techniques to assess the effectiveness and service life of 18 rock and masonry check dams that were constructed in the 1930s for controlling sediment fluxes in an 11 ha mountainous watershed in southern Arizona. All of the dams are currently filled with sediment resulting in reduction of local channel gradients by 35 to 71% to between 0.04 and 0.28 depending on location within the reach. Sedimentation occurred over multiple decades at a relatively slow average rate of 0.59 t ha−1 y−1 indicating low instantaneous retention efficiency. The smaller headwater dams were filled soon after construction; however, their share of the overall storage capacity was minor. Although evaluation of 137Cs was an effective method for dating sediment, the 210Pb dating method was not satisfactory because of sediment sorting effects and complex deposition patterns. The abundance of similar control structures in the region points to the opportunity to better understand the process impacts of check dams over multiple decades to inform planning and design of their use in future mitigation projects.

Identifying site-specific circularity potential in the built environment through socio-spatial visualizations

ABSTRACT This article tackles contextual challenges in spatial plans and circularity strategies in the built environment. It highlights the issue of using generic circularity toolboxes with limited consideration of site-specific contexts. To address this, the paper proposes socio-spatial visualizations as an alternative approach. Two case studies of industry parks demonstrate the effectiveness of this method. By employing socio-spatial visualizations, future design projects can better understand and integrate site-specific circularity potential, bridging the gap between generic circularity concepts and specific contexts. The aim is to facilitate the implementation of circular economy principles while addressing contextual challenges in the built environment.

Technology in community development: A comparative review of USA and African Projects

This paper conducts a comprehensive comparative review of technology-driven community development initiatives in the United States and various regions across Africa. The study aims to shed light on the diverse approaches and outcomes of projects leveraging technology to empower communities in different socio-cultural and economic contexts. The review begins by examining the landscape of community development in both the USA and Africa, emphasizing the challenges faced by urban and rural communities alike. It establishes a foundation for understanding the increasing role of technology in addressing these challenges, framing it as a dynamic and evolving field with vast potential for positive impact. Key findings from the comparative analysis are distilled, emphasizing the importance of context-specific approaches in technology-driven community development. Projects that demonstrate a nuanced understanding of local needs, cultural dynamics, and infrastructural realities exhibit greater success. The review underscores that successful implementation requires more than the transfer of technology; it demands a deep integration into the fabric of community life. The paper also touches upon overarching insights, highlighting the transformative power of technology when thoughtfully applied to community development. It acknowledges the significance of community engagement, adaptability, and a holistic understanding of local nuances as critical factors influencing project success. In concluding remarks, the paper encourages continued research and collaboration. It recognizes the ongoing journey towards harnessing technology's potential for global community empowerment and emphasizes the importance of cross-cultural partnerships, interdisciplinary collaboration, and knowledge sharing. Ultimately, the paper seeks to contribute to the ongoing discourse on technology in community development, offering insights that can inform future projects, policies, and academic pursuits in this dynamic field.

A dataset for predicting cloud cover over Europe

Clouds are important factors when projecting future climate. Unfortunately, future cloud fractional cover (the portion of the sky covered by clouds) is associated with significant uncertainty, making climate projections difficult. In this paper, we present the European Cloud Cover dataset, which can be used to learn statistical relations between cloud cover and other environmental variables, to potentially improve future climate projections. The dataset was created using a novel technique called Area Weighting Regridding Scheme to map satellite observations to cloud fractional cover on the same grid as the other variables in the dataset. Baseline experiments using autoregressive models document that it is possible to use the dataset to predict cloud fractional cover.

Satellite-based ensemble intelligent approach for predicting forest fire: a case of the Hyrcanian forest in Iran.

A machine learning-based approach is applied to simulate and forecast forest fires in the Golestan province in Iran. A dataset for no-fire, medium confidence (MC) fire events, and high confidence (HC) fire events is constructed from MODIS-MOD14A2. Nine climate variables from NASA's FLDAS are used as input variables, and 12 dates and 915 study points are considered. Three machine learning ensemble multi-label classifiers, gradient boosting (GBC), random forest (RFC), and extremely randomized tree (ETC), are used for forest fire simulation for the period 2000 to 2021, and ETC is found to be the most accurate classifier. Future fire projection for the near-future period of 2030 to 2050 is carried out with the ETC model, using CMIP6 EC-Earth3-SSP245 General Circulation Model (GCM) data. It is projected that MC forest fire occurrences will decrease, while HC forest fire occurrences will increase, and that the summer months, especially September, will be the most affected by fire.

Aculturación psicológica y salud en migrantes latinos en Estados Unidos: Revisión Sistemática

Health studies on migrant population globally highlights psychological acculturation, which refers to the stress of cultural change during migration. Such stress can affect vulnerable groups’ health. However, measuring this in highly mobile populations is challenging due to scattered scientific evidence. We aimed to identify instruments for assessing psychological acculturation in health studies with Latin participants in the United States, using PRISMA methodology. We found 56 instruments used in diverse health studies between 1978 and 2021, 33 were acculturation scales, five ethnic identity measures and 18 evaluations of migratory status. These instruments explored the relationship between cultural change and health in the Latino Population in the United States. This systematic review offers a comprehensive overview of available tools for future social intervention and research projects in the context of diverse migrations in Latin America.

A Field Study to Measure the Surrounding Stress of Rock and Supporting Structure of a Steep Tunnel with a Combination of Hard and Soft Rock Layers under Plate Compression

Tunnels excavated in a combination of hard and soft rock strata with high ground stress are prone to large deformations, collapse, and other disasters. The Yongfeng Tunnel, a reconstruction and expansion of the G544 line, suffered severe high ground stress from plate compression. This paper studied the surrounding rock pressure and supporting structure stress characteristics of tunnels with a combination of hard and soft rock strata with high ground stress by using earth pressure cells, surface strain gauges, and embedded strain gauges to test all stress related to the surrounding rock, primary support, and secondary lining. It was found that the contact pressure (P1) between the initial support and the surrounding rock and the contact pressure (P2) between the initial support of the leading tunnel were distributed in the direction of vertical stratification, while the contact pressures (P1 and P2) of the lagging tunnel were different due to the excavation unloading of the leading tunnel. The maximum stress positions of the initial support of the leading tunnel and the lagging tunnel were located in the left arch waist and the vault, respectively. However, the maximum stress position of the secondary lining was generally located on the side wall. The research results presented herein can guide future tunnel construction projects.

A novel approach for environmental impact assessment of road construction projects in India

The road sector is one of the basic pillars for national economic growth owing to its role in movement of goods and people and can contribute positively towards several sustainable development goals (SDGs). On the other hand, road construction using conventional methods can jeopardize the global progress towards climate action and other environmental related SDGs owing to large raw material requirements, fuel demand and pollution associated with it. Life cycle assessment (LCA) is a useful quantitative tool to figure out which products and processes are responsible for majority of road's environmental impact at different stages. This information can then be used to design interventions and adopt alternative materials for improving the environmental profile of roads. However, the application of LCA in road sector in developing countries such as India has been limited owing to unavailability of funds to compile information regarding quantities of all materials used (inventory data) and their environmental characterization factors. Here we present a new approach that connects the publicly available road's bill of quantity (BOQ) and analysis of rates (AOR) documents with national construction materials environmental footprint database to calculate the road footprint. A case study on calculating the environmental impacts of a recently built 43 km state highway road in the Indian state of Gujarat is presented to demonstrate the steps involved in the new approach. The environmental impacts per kilometre of the road section came out to be 6.86 million MJ energy use, 281 tons CO2eq. GHG emissions, 0.013 kg CFC-11 eq. ozone depletion, 2.16 tons SO2eq. acidification, 0.35 tons PO4eq. eutrophication and 0.11 tons ethene eq. of photochemical oxidant formation. Among all life cycle phases, the material production stage contributes the highest to the total environmental footprint of the road section. Of the 52 materials used, bitumen, diesel, coarse/fine aggregate, galvanized iron (GI) pipe, concrete, thermoplastic paint used in road markings and steel corrugated sheet and channel post are responsible for majority of impacts. The template presented can be used in India and other developing countries to evaluate the environmental footprint of existing and future road projects.

Comparative analysis of swine leukocyte antigen gene diversity in Göttingen Minipigs.

Worldwide, pigs represent economically important farm animals, also representing a preferred preclinical large animal model for biomedical studies. The need for swine leukocyte antigen (SLA) typing is increasing with the expanded use of pigs in translational research, infection studies, and for veterinary vaccine design. Göttingen Minipigs (GMP) attract increasing attention as valuable model for pharmacological studies and transplantation research. This study represents a first-time assessment of the SLA gene diversity in Göttingen Minipigs in combination with a comparative metadata analysis with commercial pig lines. As Göttingen Minipigs could harbor private as well as potential novel SLA allele combinations, future research projects would benefit from the characterization of their SLA background. In 209 Göttingen Minipigs, SLA class I (SLA-1, SLA-2, SLA-3) and class II (DRB1, DQB1, DQA) genes were characterized by PCR-based low-resolution (Lr) haplotyping. Criteria and nomenclature used for SLA haplotyping were proposed by the ISAG/IUIS-VIC SLA Nomenclature Committee. Haplotypes were assigned based on the comparison with already known breed or farm-specific allele group combinations. In total, 14 SLA class I and five SLA class II haplotypes were identified in the studied cohort, to manifest in 26 SLA class I but only seven SLA class II genotypes. The most common SLA class I haplotypes Lr-24.0 (SLA-1*15XX or Blank-SLA-3*04:04-SLA-2*06:01~02) and Lr-GMP-3.0 (SLA-1*16:02-SLA-3*03:04-SLA-2*17:01) occurred at frequencies of 23.44 and 18.66%, respectively. For SLA class II, the most prevalent haplotypes Lr-0.21 (DRB1*01XX-DQB1*05XX-DQA*04XX) and Lr-0.03 (DRB1*03:02-DQB1*03:01-DQA*01XX) occurred at frequencies of 38.28 and 30.38%. The comparative metadata analysis revealed that Göttingen Minipigs only share six SLA class I and two SLA class II haplotypes with commercial pig lines. More importantly, despite the limited number of SLA class I haplotypes, the high genotype diversity being observed necessitates pre-experimental SLA background assessment of Göttingen Minipigs in regenerative medicine, allo-transplantation, and xenograft research.

Situating Evaluation and Authority: Direct Sponsorship in Letters of Recommendation

The letter of recommendation (LOR) is a stylized form of direct sponsorship, a rhetorical appeal that confers favor on a person or object in keeping with the writer’s—or sponsor’s—character, authority, and expertise. In response to Swales’s call to “unveil” the rhetorical features of occluded genres, this research employs a move-step analysis to determine the rhetorical features of a sample of 83 LORs written by college faculty and administrators for a nationally competitive, postgraduate fellowship. This study finds five core moves expressed in its LOR sample: (1) sponsor positioning, (2) applicant performance, (3) applicant attributes, (4) future projection, and (5) audience appeals. Our discussion offers three key insights and provides macro-level takeaways in an effort to raise rhetorical awareness for LOR writers and requestors alike.

National Projects as a tool for Implementing the Welfare State in Modern Russia

Introduction. A national project is a strategic plan for the development of the country in any specific area, adopted for a certain period, including target indicators, tasks necessary for implementation to achieve them, designation of methods and means of achieving goals, implying financing in the required amount. In Russian political practice, national projects in their content are primarily related to social policy. National projects in modern Russia can be considered as a tool for implementing the policy of the welfare state.Methodology and sources. The author used foreign and Russian theories of the welfare state and legal acts of the Russian Federation. The methodological basis of the study was: the theory of social representations by S. Moscovici, namely the idea that representations are a specific way of understanding and communication, which creates reality and common sense; modern theories of public administration efficiency. The empirical basis was data from sociological surveys and official statistics.Results and discussion. The current results of the implementation of national projects are considered within the framework of compliance with the following components of the welfare state: creating a comfortable social environment; creating conditions and opportunities for self-realization and revealing the talent of each person; the emergence of incentives for the creation and functioning of non-state institutions aimed at improving the quality of life of citizens.Conclusion. National projects in the near future can be considered as potential opportunities for overcoming a number of difficulties and social problems within the framework of the socio-economic development of Russia, and thereby ensuring the strengthening of the welfare state.

Questioning the use of ensembles versus individual climate model generated flows in future peak flood predictions: Plausibility and implications

AbstractAccurate estimation of design floods is necessary for developing effective flood‐management strategies. Climate change (CC) studies on floods generally consider alterations in mean runoff using ensembles compared to a base period. In this study, we examined the plausibility and implications of applying individual climate model‐generated flows versus their ensembles to estimate peak floods (magnitude and timing of occurrence), using Budhigandaki River Basin of Nepal as a case study. Annual maximum one‐day floods were derived for four future climate scenario projections (cold‐dry, cold‐wet, warm‐wet, and warm‐dry) from simulated daily flow series. Future floods of six return periods estimated for the individual climate scenarios were compared with their “Ensemble” (combiner for the ensemble series is the arithmetic mean of daily floods), “Average,” and ‘Baseline.” Results showed that magnitudes of the flood peaks are such that those estimated using “Ensemble” < “Average” < individual series. We conclude that ensemble series should not be used for flood estimation because of the averaging effect. Designers should consider at the least the “Average” instead of the “Ensemble” series while designing climate‐resilient flood structures. Furthermore, the occurrences of flood peaks are likely to be confined within the monsoon season for the “Ensemble” but spread out in the other months for the individual climate scenarios. This could have direct implications on the availability and mobilization of resources as well as the need for a year‐round operational early warning system for flood risk management.

Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework

Guanling-Zhenfeng County, a microcosm of the ecologically fragile karst area in southwest China, experiences rapid population growth and urban expansion which intensifies land use transformation and ecological landscape fragmentation. Exploring the spatiotemporal characteristics of landscape fragmentation and its causes in Guanling-Zhenfeng County is of great significance in maintaining the stability of the ecosystem and ecological protection in karst areas. In this study, a comprehensive landscape fragmentation index (FI), geographic probe, multi-scale geographically weighted regression (MGWR), and PLUS model were used to quantitatively explore the spatiotemporal characteristic heterogeneity, causes, and future scenario projections of landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020. The results showed that: (1) the distribution of each landscape index was characterized by obvious spatial differentiation. Among them, the spatial distribution trends of patch density (PD) and largest patch index (LPI) were opposite and the distribution trends of Shannon diversity index (SHDI) and Shannon evenness index (SHEI) were similar. There were fewer heterogeneous patches in the study area from 2000 to 2020, and the landscape shape was more regular and less fragmented. (2) The overall landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020 was dominated by moderate fragmentation, with the smallest percentage of extreme fragmentation, and heavy fragmentation was mainly distributed in the north-central part of the study area. (3) Natural and social factors jointly affect the landscape fragmentation in Guanling-Zhenfeng County, and there is a significant interactive enhancement effect among the factors, with population density being the most important influence factor. In addition, the effects of the factors on landscape fragmentation showed significant spatial non-stationarity. (4) The characteristics of landscape fragmentation changes in Guanling-Zhenfeng County under different scenarios varied significantly, with the largest percentage of increase in heavy landscape fragmentation under the business-as-usual scenario (BAU), the next under the land use planning scenario (LUP), and the smallest under the ecological protection scenario (ESP).