Land Management Research Articles

Simulation of soil carbon and nitrogen stocks in conservation systems in Cerrado of Northeastern Brazil

Aim of study: Conservation management is an important alternative for the mitigation of environmental problems caused by conventional agriculture; however, information about long-term benefits of conservation systems is still incipient. Simulation modeling of soil organic matter dynamics has been applied using different types of land use and management. The models are essential tools for building scenarios for sustainable production systems. This study aims to use the Century model to simulate the effects of no-till and integrated crop-livestock system on soil carbon and nitrogen stocks and to establish scenarios in sandy soils at the Cerrado Brazil. Area of study: Barbosa Farm in the municipality of Brejo, eastern Maranhão state, Northeastern Brazil. Material and methods: An area that has been under no-till farming for fourteen years (NT), an area under both no-till and crop-livestock integration (NT-CLI), and an area under native Cerrado vegetation (reference) were selected. In each area, simulations of real scenarios and three future scenarios were carried out. Main results: The simulated total organic carbon (TOC) stock values for the real scenarios were 41.15 Mg ha-1 and 44.91 Mg ha-1 with NT and NT-CLI systems, respectively; whilst for simulated total nitrogen (TN) stock were 2.29 Mg ha-1 with NT and 2.59 Mg ha-1 with NT-CLI systems. However, TOC values were more accurate compared to TN values. The complexity of TN dynamics may not be fully represented by the simulation. Research highlights: Models show that future scenarios up to 2060, integrated crop-livestock system were more effective, storing up to 85.92 Mg ha-1 of TOC stock and 8.94 Mg ha-1 of TN stock.

Crisi idrogeologica e marginalità urbana. Le disuguaglianze sociali di fronte alla crisi ambientale di Jakarta

The characteristics of Jakarta's urban development have over time exacerbated social inequalities, pushing low-income communities into areas of high hydrogeological risk. Uncontrolled expansion, extensive cementification, and top-down land management have worsened these risks, while eviction policies have further marginalized informal communities. This study examines the city's historical evolution and patterns of exclusion, highlighting the resilience strategies adopted by these communities to cope with housing and environmental emergencies in the context of increasing social vulnerability.

Assessing Geohazards on Lefkas Island, Greece: GIS-Based Analysis and Public Dissemination Through a GIS Web Application

This research paper presents an assessment of geohazards on Lefkas Island, Greece, using Geographic Information System (GIS) technology to map risk and enhance public awareness through an interactive web application. Natural hazards such as landslides, floods, wildfires, and desertification threaten both the safety of residents and the island’s tourism-dependent economy, particularly due to its seismic activity and Mediterranean climate. By combining the Sendai Framework for Disaster Risk Reduction with GIS capabilities, we created detailed hazard maps that visually represent areas of susceptibility and provide critical insights for local authorities and the public. The web application developed serves as a user-friendly platform for disseminating hazard information and educational resources, thus promoting community preparedness and resilience. The findings highlight the necessity for proactive land management strategies and community engagement in disaster risk reduction efforts. This study underscores GIS’s pivotal role in fostering informed decision making and enhancing the safety of Lefkas Island’s inhabitants and visitors in the face of environmental challenges.

Land Use Changes and Their Impacts on Soil Erosion in a Fragile Ecosystem of the Ethiopian Highlands

Land cover changes have significant implications for ecosystem services, influencing agricultural productivity, soil stability, hydrological processes, and biodiversity. This study assesses the impacts of land use and land cover (LULC) change on soil erosion in the Upper Guder River catchment, Ethiopia, from 1986 to 2020. We analyzed Landsat imagery for three periods (1986, 2002, and 2020), achieving a classification accuracy of 89.21% and a kappa coefficient of 0.839. Using the Revised Universal Soil Loss Equation (RUSLE) model, we quantified spatial and temporal variations in soil erosion. Over the study period, cultivated land expanded from 51.89% to 78.40%, primarily at the expense of shrubland and grassland, which declined to 6.61% and 2.98%, respectively. Forest cover showed a modest decline, from 13.60% to 11.24%, suggesting a partial offset by reforestation efforts. Built-up areas nearly tripled, reflecting increasing anthropogenic pressure. Mean annual soil loss increased markedly from 107.63 to 172.85 t ha−1 yr−1, with cultivated land exhibiting the highest erosion rates (199.5 t ha−1 yr−1 in 2020). Severe erosion (>50 t ha−1 yr−1) was concentrated on steep slopes under intensive cultivation. These findings emphasize the urgent need for integrated land management strategies that stabilize erosion-prone landscapes while improving agricultural productivity and ecological resilience.

Assessing species diversity and abundance in farm fallow: Seasonal dynamics across wet and dry seasons

Nigeria is endowed with exceptional ecological diversity, which supports a broad spectrum of wildlife species. Despite this richness, escalating anthropogenic pressures have accelerated habitat loss. Ecologically valuable yet understudied landscapes, such as fallow farmlands, remain overlooked in biodiversity assessments and conservation planning. This study examines the potential for wildlife diversity in fallow farmlands. A systematic line transect was employed across 11 transects to record wildlife presence across wet and dry seasons. A total of 253 individual organisms representing 23 taxonomic families were documented, with avian species comprising the majority (60%), followed by insects (28%), mammals (9%), amphibians (2%), and reptiles (1%). Species abundance exhibited substantial seasonal variation, with higher abundance and variability during the wet season. Conversely, diversity indices (Shannon H′, Simpson’s 1-D) indicated a more even species distribution in the dry season. Overall, diversity was high (Shannon H′ = 2.839; Simpson’s 1-D = 0.9249), and low dominance values (Berger-Parker = 0.1462; dominance = 0.0751) affirmed the presence of a functionally balanced community. These findings highlight the ecological value of fallow farmlands as supplementary habitats that support diverse wildlife assemblages. Integrating fallow lands into conservation strategies through agroecological practices and biodiversity-sensitive land management can enhance habitat connectivity and resilience.

Performance Assessment of Advanced Daily Surface Soil Moisture Products in China for Sustainable Land and Water Management

This study evaluates the performance of nine satellite and model-based daily surface soil moisture products, encompassing sixteen algorithm versions across mainland China to support sustainable land and water management. The assessment utilizes 2018 in situ measurements from over 2400 stations in China’s Automatic Soil Moisture Monitoring Network. All products were standardized to a 0.25° × 0.25° grid in the WGS-84 coordinate system through reprojection and resampling for consistent comparison. Daily averaged station observations were matched to product pixels using a 10 km radius buffer, with the mean station value as the reference for each time series after rigorous quality control. Results reveal distinct performance rankings, with SMAP-based products, particularly the SMAP_IB descending orbit variant, achieving the lowest unbiased root mean square deviation (ubRMSD) and highest correlation with in situ data. Blended products like ESA CCI and NOAA SMOPS, alongside reanalysis datasets such as ERA5 and MERRA2, outperformed SMOS and China’s FY3 products. The SoMo.ml product showed the broadest spatial coverage and strong temporal consistency, while FY3-based products showed limitations in spatial reliability and seasonal dynamics capture. These findings provide critical insights for selecting appropriate soil moisture datasets to enhance sustainable agricultural practices, optimize water resource allocation, monitor ecosystem resilience, and support climate adaptation strategies, therefore advancing sustainable development across diverse geographical regions in China.

Appetite for forages? The adoption and multidimensional impacts of improved forage grasses in Uganda

IntroductionSmallholder dairy farming has the potential to contribute to multiple Sustainable Development Goals (SDGs), including income and employment generation, food security, nutrition, and health. A key constraint to enhancing dairy productivity is the limited availability of high-quality, nutritious feed. Improved forage grasses (IFGs) are considered a promising lever for sustainable intensification of livestock systems. However, limited evidence exists on the multidimensional impacts of IFGs at the farm household level.MethodsThis study addresses this knowledge gap by applying a mixed-methods approach to assess both the determinants of adoption and the impacts of feeding IFGs on productivity, income, food security, and land management practices. We focus on Uganda, where several IFGs were introduced and disseminated through two livestock development projects. Adoption barriers and impact pathways are analyzed, and inverse probability weighted regression adjustment (IPWRA) is used to address selection bias.ResultsKey barriers to adoption include limited experience with forage cultivation, use of local breeds, non-practice of zero-grazing, and lack of membership in producer organizations. Feeding IFGs to dairy cows significantly increases daily milk yield per cow by 13%, household income by 18%, and the number of food items consumed by 0.9.DiscussionThese findings highlight the potential of IFGs to improve productivity, incomes, and food security in smallholder dairy systems. They offer practical insights for the design and implementation of future dairy development programs aimed at scaling sustainable livestock intensification.

Pinelands: Impacts of Different Long-Term Land Uses on Soil Physical Properties in Red Ferrosols

Century-long land-use practices have a profound impact on soil physical and chemical properties, with direct implications for soil health and agricultural sustainability. This study aimed to assess the effects of four contrasting land uses—remnant vegetation, pasture, cultivated areas, and loafing areas—on the physical and chemical properties of Red Ferrosols in the Toowoomba region, Queensland, Australia. Soil samples were collected from upper and lower slope positions for each land use. Physical properties, including bulk density, porosity, water retention, and permeability, as well as chemical properties such as organic carbon, nitrogen, phosphorus, and potassium, were analysed. The results showed that remnant vegetation preserved the most favourable soil conditions, with lower bulk density, higher porosity, and greater water retention. Cultivated areas exhibited significant soil degradation, marked by compaction, reduced infiltration, and depleted organic matter. Loafing areas displayed localised nutrient enrichment but higher compaction due to livestock trampling. Pastures maintained intermediate conditions, retaining some beneficial soil characteristics. These findings emphasise the critical need for sustainable land management strategies to protect soil structure and function, supporting the long-term productivity and resilience of Red Ferrosols.

Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection

Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. Subsequently, PSO was deployed to optimize key hyperparameters of the Random Forest algorithm and compare its performance with the ResNet-Transformer model. Our results indicate that PSO effectively automates the search for optimal WP decomposition parameters, preserving essential spectral information while efficiently reducing high-frequency spectral noise. The Genetic Algorithm (GA) was also found to be effective in extracting feature bands relevant to land desertification, which enhances the classification accuracy of the model. Among all the models, integrating wavelet packet denoising, genetic algorithm feature selection, the first-order differential (FD), and the hybrid architecture of the ResNet-Transformer, the WP-GA-FD-ResNet-Transformer model achieved the highest accuracy in extracting soil sandification and salinization, with Kappa coefficients and validation set accuracies of 0.9746 and 97.82%, respectively. This study contributes to the field by advancing hyperspectral desertification monitoring techniques and suggests that the approach could be valuable for broader ecological conservation and land management efforts.

Effect of improved Establishment Technologies (ET) on growth, yield, economics and energy use in Italian millet

Minor millets are small, seeded grains with enriched minerals and nutrients over other grain crops. Besides its nutritional quality, low yielding potential and lack of available technologies restricted its cultivation area. During the last few decades, most of crop-producing activities turned to mechanization except minor millets due to less focus on minor millet research. In this experiment, various establishment technologies were evaluated through mechanization with the objective of increasing foxtail millet (Italian millet) productivity. The treatments were formulated with various land management [(Ridges & Furrow (RF); Compartmental Bunding (CB); Broad Bed Furrow (BBF); Flatbed (FB)], sowing [Line sowing (LS), Sowing by drone (SD) and Machine sowing (MS)] and irrigation methods (Modified surge irrigation (MSI), Rain gun (RG)). The Randomized Block Design (RBD) was used to lay the experiment with 3 replications during the Rabi seasons of 2023 and 2024. Among the Establishment Technologies (ET), higher plant height was measured in ET-7 at 40 DAS (74.87 cm), 60 DAS (109.33 cm) and harvest stage (114.67 cm). Higher dry matter production of foxtail millet was recorded in ET-8 at 40 DAS (3772.40 kg/ha) & CT at 60 DAS (6035.87 kg/ha) and harvest stage (7541.90 kg/ha). In yield and economics parameters, ET-6 produced higher productive tillers (4.44/plant), grain yield (2340 kg/ha) & straw yield (4516 kg/ha) and it reflected on economic indices as higher net return (Rs. 47959) and benefit-cost ratio (1.65). ET-2 recorded the lowest values across all parameters during both the studies.

Emerging trends in AI-based soil health assessment: A review

The application of artificial intelligence (AI) in soil health assessment presents significant advancements over conventional methods by enabling more efficient and precise measurements. This review examines and supports how AI monitors soil health and its significance for sustainable land management. AI technologies, including machine learning, remote sensing and big data analytics, enable researchers and practitioners to analyse diverse data sources, model soil-plant relations and predict soil health trends with greater accuracy. AI-integrated soil health monitoring enables tracking of key soil parameters, facilitating efficient nutrient management, soil erosion control and overall ecosystem sustainability. AI-driven precision agriculture helps stakeholders predict the long-term impacts of farming practices, optimize resource use, enhance crop yields and reduce environmental impacts. This review also demonstrates how updated highlights recent research, case studies and best practices that demonstrate how AI-based soil health monitoring contributes to agricultural sustainability, conservation and food security.

Evaluation forest educational boards based on eye tracking analysis in a pilot study

A thorough understanding of the visual behaviors of the audience interacting with the content on informational boards is crucial for developing training programs and facilitating communication between land managers, such as foresters, and the public. The aim of the study was to assess the extent of perception of information presented on educational boards in the forest by school-aged youth, thereby determining the usefulness of these panels in the environmental and forestry education of young people. We analyzed the variable eye movement of the respondent students using the Tobii Pro Glasses 2 eye tracker. We generated heat maps to identify the elements on the boards that most strongly attracted the participants’ attention. For the determined areas of interest (header, description, image, footer), we generated standard fixation metrics. The fixation time for the image was consistently significantly longer than that for the header. The number of fixations was higher on the descriptions than on the images. School youth experienced slightly more difficulty in assimilating information conveyed through images that required deeper analysis compared to reading text or following diagrams. An effective design for an educational board may involves placing diagrams in a sequential layout with accompanying descriptions underneath.

How size and resource traits control species' biomass in monoculture and mixture and drive biodiversity–ecosystem functioning relationships

Humans are driving unprecedented environmental change, causing the loss of species from local ecosystems. This local species loss is likely to result in declines in ecosystem functioning but understanding why these so‐called biodiversity‐ecosystem functioning relationships vary is crucial for conservation and sustainable land management. Previous studies have shown that variation among biodiversity–ecosystem functioning (BEF) relationships can be explained by a ‘function‐dominance correlation', i.e. the correlation of species' biomass in monoculture (‘functioning') versus mixtures (‘dominance'). One potential reason for the importance of the function–dominance correlation is its relationship to underlying plant traits. Here, we explore which traits control species' biomass in monoculture and mixture and thereby drive the function–dominance correlation, and hence BEF relationships. To do this, we perform a modeling experiment with six trait‐based models of plant community dynamics and classify model traits as either ‘size' or ‘resource' traits. This approach allows us to better generalize across systems that differ in terms of their key traits and/or how a given trait affects individual performance and ecosystem functioning. We found that size traits, but not resource traits, predicted species' monoculture biomass in five out of the six models. However, in mixture, resource traits became more important and – in addition to size traits – explained substantial variation in species' biomass in four models. In models where size traits were consistently important predictors of biomass variance in monoculture and mixture, the function–dominance correlation was high, and BEF relationships were strongly positive. Our analysis shows how generalizable categories of functional traits allow predicting BEF relationships across systems, and thereby the potential effects of losing species on ecosystem functioning.

Conflict and Compromise, Discourse and Action: Political Ecology in the Complexity of Land Management in Central Kalimantan, Indonesia

Peatlands in Mantangai District, Central Kalimantan, have emerged as a site of contention among many stakeholders with differing interests, illustrating the intricacies of natural resource management in Indonesia. This research seeks to examine the contestation process, identify main actors, and comprehend how various forms of knowledge and power influence the results of peatland management. This research employs a case study method with a qualitative approach, incorporating direct observation, in-depth interviews, and document analysis to achieve a thorough knowledge of the dynamics of contestation. The findings indicate three primary viewpoints in peatland management: eco-conservationism exemplified by Mawas Borneo Orangutan Survival Foundation (BOSF), eco-developmentalism illustrated by the government's food estate initiative and oil palm plantation expansion, and eco-populism promoted by Wahana Lingkungan Hidup (WALHI) Central Kalimantan and local communities. This contention leads to multiple underlying conflicts, including tensions between conservation initiatives and resource extraction activities by local communities, discrepancies between governmental development programs and the ecological and social realities, as well as unresolved land disputes and compensation challenges arising from the expansion of oil palm plantations. This study suggests that a more holistic and inclusive approach to peatland management is necessary, taking into account ecological, economic, and socio-cultural factors in a balanced manner. These findings significantly enhance the comprehension of the intricacies of natural resource management and can underpin the formulation of more inclusive and sustainable policies moving forward.

Climate Consideration in Environmental Effects Analyses on Federal Public Lands in the United States.

Effects of a changing climate, including drought, wildfire, and invasive species encroachment, are evident on public lands across the United States. Decision making on Federal public lands requires analyses under the National Environmental Policy Act (NEPA), and there are guidelines for considering climate in NEPA analyses. To better understand how climate most recently has been considered, we analyzed a stratified random sample of 130 environmental assessments (EAs) completed by the Bureau of Land Management (BLM) from 2021 to 2023 across the contiguous United States. We assessed whether EAs considered (1) potential effects of the proposed action on climate (2) potential climate effects on the proposed action, and (3) potential climate effects on resources of concern. We also identified whether EAs included data and science about climate or greenhouse gas emissions, and which datasets and documents were cited. We used two approaches: automated keyword searches and document analysis. Thirty-seven percent of EAs considered the potential effects of the proposed action on climate, 8% considered the potential effects of climate on the proposed action, and 4% of individual resource analyses considered the potential effects of climate on the resource. EAs in the 'oil and gas development,' 'renewable energy,' and 'forestry and timber management' proposed action categories most frequently considered the potential effects of climate and used climate data and science. Our findings suggest an opportunity for scientists to work more closely with public land managers to identify available data and science for considering climate in environmental effects analyses and to provide science delivery mechanisms that can facilitate the consideration and use of climate science in decision making.

Analyses of MODIS Land Cover/Use and Wildfires in Italian Regions Since 2001

Monitoring land cover/use dynamics and wildfire occurrences is very important for land management planning and risk mitigation practices. In this research, moderate-resolution imaging spectroradiometer (MODIS) annual land cover images for the period 2001–2023 are utilized for the twenty administrative regions of Italy. Monthly MODIS burned area images are utilized for the period 2001–2020 to study wildfire occurrences across these regions. In addition, monthly Global Precipitation Measurement images for the period 2001–2020 are employed to estimate correlations between precipitation and burned areas annually and seasonally. Boxplots are produced to show the distributions of each land cover/use type within the regions. The non-parametric Mann–Kendall trend test and Sen’s slope are applied to estimate a linear trend, with statistical significance being evaluated for each land cover/use time series of size 23. Pearson’s correlation method is applied for correlation analysis. It is found that grasslands and woodlands have been declining and increasing in most regions, respectively, most significantly in Abruzzo (−0.88%/year for grasslands and 0.71%/year for grassy woodlands). The most significant and frequent wildfires have been observed in southern Italy, particularly in Basilicata, Apulia, and Sicily, mainly in grasslands. The years 2007 and 2017 experienced severe wildfires in the southern regions, mainly during July and August, due to very hot and dry conditions. Negative Pearson’s correlations are estimated between precipitation and burnt areas, with the most significant one being for Basilicata during the fire season (r = −0.43). Most of the burned areas were mainly within the elevation range of 0–500 m and the lowlands of Apulia. In addition, for the 2001–2020 period, a high positive correlation (r > 0.7) is observed between vegetation and land surface temperature, while significant negative correlations between these variables are observed for Apulia (r ≈ −0.59), Sicily (r ≈ −0.69), and Sardinia (r ≈ −0.74), and positive correlations (r > 0.25) are observed between vegetation and precipitation in these three regions. This study’s findings can guide land managers and policymakers in developing or maintaining a sustainable environment.

Soil erosion vulnerability analysis of Damodar River Basin, India using Revised Universal Soil Loss Equation (RUSLE) in Google Earth Engine (GEE)

Soil erosion is an important environmental issue worldwide. Therefore, data on spatio-temporal patterns of soil erosion and successive soil loss would be of immense significance for the sustainable management of land and water resources. Despite being coal mining-intensive area, Damodar River Basin of India, suffers with the lack of adequate measurements of soil erosion over the entire basin, which hampers the holistic planning and conservation initiative. Therefore, present study employs the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS), massive databases and processing capabilities of Google Earth Engine (GEE) and attempts to estimate the soil loss in the entire basin. To estimate soil loss for the years 2017 and 2024 for the study area, RUSLE considers several factors, including the steepness factor (S), crop/cover management component (C), rainfall erosivity factor (R), soil erodibility factor (K), slope length (L), and conservation support practice factor (P). The mean soil loss in the Damodar River Basin is decreased from 12.86 t ha⁻1 yr⁻1 in 2017 to 12.06 t ha⁻1 yr⁻1 in 2024. The present study identifies areas affected by prominent soil loss (> 20 t ha⁻1 yr⁻1) covering 36.47% of the total area in 2017 mostly concentrated on northwestern and central region of the entire basin with extensive mining activities, which slightly declined to 35.07% in 2024. Among all the factors, R factor is the primary reason for such decline which is attributed to the decrease in rainfall in the study area. The findings underscore the urgent need for focused soil conservation measures in the Damodar River Basin, considering its ecological relevance and socioeconomic worth. Due to the limitations in obtaining comprehensive field observations, across such an immense river basin, might affect the accuracy of predictions using the RUSLE model. However, present study estimates soil loss and identify vulnerable zone over two time periods within the expansive and mining-scarred river basin to enhance the reliability of estimations and thus it may contribute to the development of viable strategies for the long-term management of the Damodar River Basin's natural resources.

Characterization of soil bacterial pathogens in peri-urban zones across population density gradients and land use patterns: insights into pathogen diversity, composition, interactions, and community assembly processes.

Characterization of soil bacterial pathogens in peri-urban zones across population density gradients and land use patterns: insights into pathogen diversity, composition, interactions, and community assembly processes.

Chasing pigs, chasing profits: (De)territorializing organic and free-range pig farming in Norway

Abstract Organic and free-range pig farming offers a potential solution to multiple agricultural challenges, including high pesticide and antimicrobial use, excess fertilization, biodiversity loss, and animal suffering. Organic pig production, which includes outdoor access and rearing, has been one solution promoted by the European Union. This study, based on ethnographic fieldwork and interviews with organic and non-organic free-range pig farmers in Norway, suggests that while promising, sustaining these production systems faces challenges related to animal welfare, land management, and market dynamics for pork. Specifically, we note how the weak symbolic value of organic labels and principles for pigs and pork results in fragile markets, whilst pigs’ rooting undermines not just soil and farm boundaries, but potentially their own welfare. Farmers have responded by forming new relational arrangements, including situating pigs as a working animal contributing to the broader productivity of the farm, and decommodifying pigs and pork in favour of using them to sustain broader social relations that produce other values and opportunities. We conclude that the flexibility and adaptability of pigs opens multiple trajectories of change, with regards to market organization, farmer collaboration and breeding pigs for rearing outdoors. If Europe is to reterritorialize the pig and pork industry around alternative production methods it requires a fundamental reimagining of the socio-material relations underpinning this industry, its moral frameworks and our relationship with pigs and pork.

China’s practice from coastline management towards sea-land integration

Integrated Sea-land management is an important feature of ecosystem-based management, and it is also the trend of marine spatial planning. China is one of the first countries worldwide to implement marine spatial planning which is mainly expressed as marine functional zoning (MFZ), and it has established a coastline management system for the connection between marine management and land management. In this paper, 18 national and local coastline management policies in China are analyzed. It is concluded that coastline management ensures the formulation, implementation, evaluation, and revision of MFZ, promotes the extension of MFZ to land, gradually evolves into coastal zone planning based on coordinated land and marine development, and promotes sea-land integration management in China. Taking Tangshan City in Hebei Province as an example, it is further proven that at the local level, coastline management accelerates the progress of sea-land integration.