Landscape Parameters Research Articles

Nonlinear impacts of landscape and climatological interactions on urban thermal environment during a hot and rainy summer

Investigating the nonlinear impacts of urban landscape and climatic parameters on urban temperatures, a critical issue within urban climatology. Chengdu, characterized by its hot, rainy summers and rapid urban development, serves as an ideal model to illustrate these dynamics. Our investigation utilizes advanced analytical methods such as Random Forests (RF), SHapley additive explanation (SHAP), and Partial Dependence Plots (PDP) to analyze how landscape and climatic factors influence air temperature (AT) and land surface temperature (LST). Significant findings reveal profound thermal heterogeneity across Chengdu’s urban fabric, underscored by spatially distinct phenomena where some regions exhibit strong contrasts in temperature impacts due to varying climatic and landscape factors. The study identifies relative humidity and rainfall as key drivers of temperature variations during the summer months, reflecting Chengdu’s specific climatic idiosyncrasies. These insights are critical, as they highlight how urban planning and green infrastructure can be strategically used to mitigate adverse thermal effects. The research not only enhances understanding of the complex interplays within urban microclimates but also offers new perspectives on urban heat management. It contributes to the scientific community by providing evidence-based strategies for urban planners to counter the urban heat island effect and enhance urban resilience against climate change. This comprehensive analysis underscores the importance of incorporating multiple variables into urban climate models, lays the groundwork for more refined urban environmental policies and practices.

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study

Tumor–stroma ratio (TSR) has been recognized as a valuable prognostic indicator in various solid tumors. This study aimed to examine the clinicopathologic relevance of TSR in Merkel cell carcinoma (MCC) using artificial intelligence (AI)-based parameterization of the stromal landscape and validate TSR scores generated by our AI model against those assessed by humans. One hundred twelve MCC cases with whole-slide images were collected from 4 different institutions. Whole-slide images were first partitioned into 128 × 128-pixel “mini-patches,” then classified using a novel framework, termed pre-tumor and stroma (Pre-TOAST) and TOAST, whose output equaled the probability of the minipatch representing tumor cells rather than stroma. Hierarchical random samplings of 50 minipatches per region were performed throughout 50 regions per slide. TSR and tumor–stroma landscape (TSL) parameters were estimated using the maximum-likelihood algorithm. Receiver operating characteristic curves showed that the area under the curve value of Pre-TOAST in discriminating classes of interest including tumor cells, collagenous stroma, and lymphocytes from nonclasses of interest including hemorrhage, space, and necrosis was 1.00. The area under the curve value of TOAST in differentiating tumor cells from related stroma was 0.93. MCC stroma was categorized into TSR high (TSR ≥ 50%) and TSR low (TSR < 50%) using both AI- and human pathology–based methods. The AI-based TSR-high subgroup exhibited notably shorter metastasis-free survival (MFS) with a statistical significance of P = .029. Interestingly, pathologist-determined TSR subgroups lacked statistical significance in recurrence-free survival, MFS, and overall survival (P > .05). Density-based spatial clustering of applications with noise analysis identified the following 2 distinct TSL clusters: TSL1 and TSL2. TSL2 showed significantly shorter recurrence-free survival (P = .045) and markedly reduced MFS (P < .001) compared with TSL1. TSL classification appears to offer better prognostic discrimination than traditional TSR evaluation in MCC. TSL can be reliably calculated using an AI-based classification framework and predict various prognostic features of MCC.

Landscape, demographic, and dispersal parameters influence the spread and establishment of an aquatic biological invasion

AbstractHuman‐mediated species introductions are contributing to the biotic homogenization of global flora and fauna. Despite extensive research, we lack simple methods of predicting how and where an introduced species will spread and establish, particularly in species with complex life histories in aquatic ecosystems. We predict that spread can be modeled simply using the characteristics of the invading population, specifically species growth rate and dispersal capacity. In addition, we predict that the establishment of introduced species should be explained by the characteristics of the receiving ecosystem. Using the brown trout (Salmo trutta) invasion on the Island of Newfoundland as a case study, we fit and test a reaction–diffusion model with brown trout population data collected from the literature. Next, we use statistical models to assess the influence of a suite of abiotic (conductivity, pH, turbidity, calcium), biotic (Atlantic salmon occurrence), and landscape (watershed relief, watershed area, distance to original introduction) variables on brown trout establishment (i.e., presence–absence) patterns. We find that observed coastal spread in Newfoundland is slow (~4.4 km/year), and that it lies on the lower end of the range of predictions made by the reaction–diffusion model parameterized based on the estimates of growth rate and movement from the literature (predicted spread range 1.4 to 92 km/year). Also, we did not find evidence for a relationship between abiotic or biotic variables and brown trout establishment. However, we did observe that landscape variables of the distance to trout introduction point and estuary area may explain establishment patterns along the south coast of Newfoundland. Our results suggest the importance of using population‐specific parameterization and the need to integrate regional landscape factors that are generally applicable across biological invasions (e.g., distance to introduction), and those that are more specific to the ecology of the invader (e.g., estuary area). Our study contextualizes the mechanisms that contribute to a slow invasion by an aquatic species with a complex life history and reveals that future studies need to integrate a variety of methods to elucidate the processes governing invasions.

MechanoProDB: a web-based database for exploring the mechanical properties of proteins.

The mechanical stability of proteins is crucial for biological processes. To understand the mechanical functions of proteins, it is important to know the protein structure and mechanical properties. Protein mechanics is usually investigated through force spectroscopy experiments and simulations that probe the forces required to unfold the protein of interest. While there is a wealth of data in the literature on force spectroscopy experiments and steered molecular dynamics simulations of forced protein unfolding, this information is spread and difficult to access by non-experts. Here, we introduce MechanoProDB, a novel web-based database resource for collecting and mining data obtained from experimental and computational works. MechanoProDB provides a curated repository for a wide range of proteins, including muscle proteins, adhesion molecules and membrane proteins. The database incorporates relevant parameters that provide insights into the mechanical stability of proteins and their conformational stability such as the unfolding forces, energy landscape parameters and contour lengths of unfolding steps. Additionally, it provides intuitive annotations of the unfolding pathways of each protein, allowing users to explore the individual steps during mechanical unfolding. The user-friendly interface of MechanoProDB allows researchers to efficiently navigate, search and download data pertaining to specific protein folds or experimental conditions. Users can visualize protein structures using interactive tools integrated within the database, such as Mol*, and plot available data through integrated plotting tools. To ensure data quality and reliability, we have carefully manually verified and curated the data currently available on MechanoProDB. Furthermore, the database also features an interface that enables users to contribute new data and annotations, promoting community-driven comprehensiveness. The freely available MechanoProDB aims to streamline and accelerate research in the field of mechanobiology and biophysics by offering a unique platform for data sharing and analysis. MechanoProDB is freely available at https://mechanoprodb.ibdm.univ-amu.fr.

Dry grasslands in urban areas can harbour arthropod species of local conservation concern and should be prioritised for biodiversity‐friendly mowing regimes

Abstract Although urbanisation is one of the greatest threats to biodiversity, its effect on particular invertebrate groups remains ambiguous on local and landscape scales. We aimed to analyse the effect of urban grassland management on spiders (Araneae) and carabids (Coleoptera: Carabidae), as well as other local and landscape parameters. We investigated 27 grasslands of two different management intensities (‘extensive’: one to two late cuts with removal of biomass [n = 18]; ‘intensive’: three to five mulching cuts [n = 9]) in the city of Karlsruhe, Germany. Pitfall trapping and sweep netting were performed to sample carabids and spiders. Results indicate that urban grasslands in Karlsruhe are inhabited by species‐rich assemblages, including several species of conservation concern (cc). Latter remain mostly restricted to dry grassland. The number of total specimens and of those belonging to species of cc were negatively affected by intensive management. The number of specimens of species of cc further decreased with increasing humidity and in spiders, additionally, by vegetation height. Landscape factors had limited effects, and only isolation of meadows negatively influenced the species richness of carabids (total and of species of cc). Our results demonstrate that conservation of dry grasslands in urban areas is crucial for sustaining local arthropod communities. Dry urban grassland may also act as a refugium for species of cc and mitigate the global insect crisis on a local and regional scale. In conclusion, biodiversity‐friendly mowing regimes should be applied on a broader scale in urban areas and target especially dry grassland plots. In addition, increasing connectivity and permeability of the urban matrix assist the colonisation by species of cc.

A comparative analysis of the clinical and genetic profiles of blast phaseBCR::ABL1-negative myeloproliferative neoplasm and acute myeloid leukemia, myelodysplasia-related.

The classic Philadelphia chromosome-negative myeloproliferative neoplasms (Ph (-) MPNs), have variable potential for progression to the blast phase (MPN-BP) of the disease. Except initiated by distinct driver mutations, MPN-BP frequently carry similar genetic abnormalities defining acute myeloid leukemia myelodysplasia-related (AML-MR). Because of dissimilar initial pathogenesis, MPN-BP and AML-MR are retained under different disease categories. To determine if separately classifying these entities is justified, we compare MPN-BP with AML-MR patients based on mutational landscape and clinical parameters. 104 MPN-BP patients and 145 AML-MR patients were identified with available clinical, cytogenetic, and genetic data. AML-MR patients presented with a higher blast count (median, 51% vs. 30%) while MPN-BP patients had higher WBC counts, platelet counts and bone marrow cellularity (all p<0.0001). Patients with MPN-BP showed similar genetic mutations with similar mutation pattern (functional domain, hotspot and locus involved by the mutations) but a different mutation rate from AML-MR, with more frequent JAK2, CALR, MPL, ASXL1, IDH2, SETBP1 and SRSF2 mutations and less frequent TP53 and DNMT3A mutations. The overall survival (OS) of MPN-BP (OS post-BP-progression) is comparable to that of AML-MR (median OS, 9.5 months vs. 13.1 months, p=0.20). In addition, the subgroups of MPN-BP show similar OS as AML-MR. When harboring certain mutation such as TP53, ASXL1, DNMT3A, TET2, RUNX1, IDH1, IDH2, EZH2, U2AF1, BCOR and SRSF2, MPN-BP and AML-MR patients carrying the same somatic mutation show no difference in OS. MPN-BP and AML-MR harbor similar somatic mutations and clinical outcomes, suggesting a unified clinical disease entity.

Study on the Impact of Urban Morphologies on Urban Canopy Heat Islands Based on Relocated Meteorological Stations

This study addresses a crucial gap in understanding the impact of urban morphologies on the canopy urban heat islands (CUHI) effect. The selection of reference stations lacks a unified standard, and their surface air temperature (SAT) sequences are also inevitably influenced by urbanization. However, synchronous observational data from relocated meteorological stations could provide high-quality sample data for studying CUHI. Utilizing remote sensing techniques, the findings of this paper revealed that the observation environment of stations after relocation exhibited remarkable representativeness, with their observation sequences accurately reflecting the local climatic background. The differences in synchronized observation sequences could characterize the CUHI intensity (CUHII). Among the various factors, land use parameters and landscape parameters played particularly significant roles. Furthermore, the fitting performance of the random forest (RF) model for both training and testing data was significantly superior to that of the linear model and support vector regression (SVR) model. Additionally, the influence of local circulation on CUHI could not be overlooked. The mechanisms by which urban morphologies affect CUHII under different circulation backgrounds deserve further investigation.

Visual quality assesment in recreational and touristic landscape

AbstractAlthough the landscape quality parameter in rural areas, which is called landscape beauty, varies according to the way the individual perceives the landscape, being able to perceive and understand the landscape visually in rural and urban landscape areas, natural and cultural tourism and recreation areas is directly related to whether that recreational area is used actively or not. This study aims to examine the effect of perceptual landscape parameters in touristic and recreational landscape character. In this study, it was investigated how the recreational and touristic landscape character can be emphasized with visual quality value. For this purpose, Gölbaşı Pond and its surroundings in Bursa in Turkey, which has a rich landscape character selected as study area, by evaluating the area’s visual landscape quality. The method of the study visual quality analysis was performed and the data obtained by visual quality analysis were compared. As a result, Gölbaşı Pond and its surroundings with its natural beauty and nature, as well as its landscape qualities suitable for recreational activities, provide opportunities for many recreational activities, and the study concluded that all landscape quality parameters support each other and create a potential for more.

Diverse response of shallow lake water levels to decadal weather patterns in a heterogeneous glacial Boreal Plains landscape

AbstractTo examine the relative controls of landscape and climate on spatial variability, we measured water level dynamics of shallow lakes over two decades that represent both the heterogeneity of surficial geology classifications, and thus the potential range in surface and groundwater connectivity, and the long‐term weather patterns of the Boreal Plain hydrogeoclimatic setting. Large ranges in shallow lakes water levels (between 0.25 and 2 m) were observed corresponding to extremes in precipitation relative to the long‐term mean precipitation over the study period. We found low concurrence in water level dynamics among four detailed study lakes that received the same meteorological weather signal, but were located in different surficial geology texture classifications that incorporated important landscape parameters associated with lake water balance and storage. Surficial geology classification alone did not, however, distinguish between different ranges in lake water level measured in a broader synoptic survey of 26 lakes across the region. Thus, simple surficial geology classifications cannot alone be applied to classify Boreal Plain lake water level dynamics and other controls, notably landscape position, must also be considered. We further show that inter‐annual variability in lake water levels was significantly greater than seasonal variability in this hydrogeoclimatic setting. This emphasizes the need for studies of sufficient length to capture weather extremes that include periods of wetting and drying, and demonstrates how observed magnitudes of water level variability, and lake function, can be an artefact of study length and initiation date. These findings provide a foundation to test and calibrate conceptual understanding of the wider controls of lake water levels to form holistic frameworks to mitigate ecological and societal impacts due to hydrological changes under climate and anthropogenic disturbance within and between hydrogeoclimatic settings.

Potential energy landscape of a coarse grained model for water: ML-BOP.

We quantify the statistical properties of the potential energy landscape for a recently proposed machine learning coarse grained model for water, machine learning-bond-order potential [Chan et al., Nat. Commun. 10, 379 (2019)]. We find that the landscape can be accurately modeled as a Gaussian landscape at all densities. The resulting landscape-based free-energy expression accurately describes the model properties in a very wide range of temperatures and densities. The density dependence of the Gaussian landscape parameters [total number of inherent structures (ISs), characteristic IS energy scale, and variance of the IS energy distribution] predicts the presence of a liquid-liquid transition located close to P = 1750 ± 100 bars and T = 181.5 ± 1 K.

Deep learning models for monitoring landscape changes in a UNESCO Global Geopark

By identifying Earth heritage sites, UNESCO Global Geoparks (UGGps) have promoted geo-tourism and regional economic prosperity. However, commercial and tourism development has altered the natural contexts of these geoparks, diminishing their initial value. Before implementing land use policies, spatial landscape parameters should be monitored in multiple dimensions and in real time. This study aims to develop Bilateral Segmentation Network (BiSeNet) models employing an upgraded U-structured neural network in order to monitor land use/cover changes and landscape indicators in a Vietnamese UGGp. This network has proven effective at preserving input image data and restricting the loss of spatial information in decoding data. To demonstrate the utility of deep learning, eight trained BiSeNet models were evaluated against Maximum Likelihood, Support Vector Machine, and Random Forest. The trained BSN-Nadam model (128x128), with a precision of 94% and an information loss of 0.1, can become a valuable instrument for analyzing and monitoring monthly changes in land uses/covers once tourism activities have been rapidly expanded. Three tourist routes and 41 locations in the Dak Nong UGGp were monitored for 30 years using three landscape indices: Disjunct Core Area Density (DCAD), Total Edge Contrast Index (TECI), Shannon's Diversity Index (SHDI), based on the results of the model. As a result, 18 identified geo-sites in the Daknong Geopark have been influenced significantly by agricultural and tourist activities since 2010, making these sites less uniform and unsustainable management. It promptly alerts UNESCO management to the deterioration of geological sites caused by urbanization and tourist development.

Distance functions of carabids in crop fields depend on functional traits, crop type and adjacent habitat: a synthesis.

Natural pest and weed regulation are essential for agricultural production, but the spatial distribution of natural enemies within crop fields and its drivers are mostly unknown. Using 28 datasets comprising 1204 study sites across eight Western and Central European countries, we performed a quantitative synthesis of carabid richness, activity densities and functional traits in relation to field edges (i.e. distance functions). We show that distance functions of carabids strongly depend on carabid functional traits, crop type and, to a lesser extent, adjacent non-crop habitats. Richness of both carnivores and granivores, and activity densities of small and granivorous species decreased towards field interiors, whereas the densities of large species increased. We found strong distance decays in maize and vegetables whereas richness and densities remained more stable in cereals, oilseed crops and legumes. We conclude that carabid assemblages in agricultural landscapes are driven by the complex interplay of crop types, adjacent non-crop habitats and further landscape parameters with great potential for targeted agroecological management. In particular, our synthesis indicates that a higher edge-interior ratio can counter the distance decay of carabid richness per field and thus likely benefits natural pest and weed regulation, hence contributing to agricultural sustainability.

Spatial and temporal disturbances in the zone of mining of ferruginous quartzites of the Kostomuksha cluster, NW Russia

The research presents new methods for analyzing spatial and temporal disturbances, focusing on landscape ecology. The study covers the period from the beginning of the development of the field to the present stage. The Land Use and Land Сover (LULC) change analysis is based on processing of Landsat satellite imagery. The method uses landscape metrics, SDI calculation, and mapping to describe the mechanisms of transformation and self-regulation of the system. Landscape metrics include three groups: areas and edges, shape metrics, and diversity metrics. An increase in landscape fragmentation over time is shown. All LULC classes have been changed. The area of the “mining" class has been increased in 7.7% (from 0 to 55.5 thousand km2). The increase in the area of quarries occurs evenly at the expense of all other land use classes. The data obtained confirm several stages of anthropogenic impact. An approach has been developed for mapping disturbances and assessing the impact on geosystemsIt was revealed that in the cell size range from 1500 to 2500 m, the landscape parameters are the most stable. The calculation of the spatial disturbance index is based on principal component analysis data. Factors were identified that indicate external load and the adaptation and self-regulation of the geosystem. Three degrees of disturbance of the territory are defined: low, medium, and high. In 2006, the maximum level of spatial disturbance was found, with the area of heavily disturbed areas being 68%. The results of this study indicate the importance of taking the necessary measures to reduce environmental risks.

Use of geomatics and multi-criteria methods to assess water erosion in the Tigrigra watershed (Azrou region, Morocco)

In Morocco, the capacity of dam reservoirs has decreased in recent years due to water erosion. This study aims to identify the sub-watersheds most vulnerable to soil erosion in the Tigrigra watershed by utilizing morphometric analysis of linear, landscape, and shape parameters and various multi-criteria decision models. These approaches allow for the prioritization of areas or sub-watersheds at high erosion risk. In the study area, erosion assessment is conducted using multi-criteria decision support models (MCDM) such as MOORA, VIKOR, TOPSIS, COPRAS, WASPAS, and SAW within a GIS environment. This approach highlights the significant role of morphometric parameters and multi-criteria methods in identifying sub-watersheds susceptible to erosion. Overall, the results indicate that morphometric parameters are highly effective in identifying erosion-prone areas. The Tigrigra watershed generally exhibits low to medium sensitivity to erosion, except for certain sub-watersheds. Subcatchment 28 showed significant erosion in most methods used.

How can GIS support the evaluation and design of biodiverse agroecosystems and landscapes? Applying the Main Agroecological Structure to European agroecosystems

Agrobiodiversity plays a critical role in fostering the stability, resilience, and sustainability of European farming systems. Nonetheless, there is currently a lack of comprehensive methods to describe its spatial distribution within farms, its connectivity with the surrounding landscape, and, most crucially, how the perceptions and actions of human communities affect it. The Main Agroecological Structure (MAS) has recently been proposed as an environmental index aiming to tackle such challenges by promoting a dialogue between landscape ecology and agroecology, encompassing criteria that focus on both landscape parameters and cultural variables. Geographic information systems (GIS) can play a key role in the measurement of the index by leveraging public geodata and engaging with the direct participation of communities to map the territories they inhabit and cultivate. Nevertheless, their use in this context has not yet been studied. We propose here a new GIS-based approach for estimating the Main Agroecological Structure: landscape criteria are assessed through the hybrid use of free and open-source GIS tools, field samplings, and participative mapping methods; cultural parameters are evaluated through semi-structured interviews. Contextually to the definition of such methodological foundations, the present study tests the relevance of the index to European agroecological contexts by applying the proposed workflow to three Italian farms characterized by different territorial and organizational forms. Along with a few modifications to the original proposal, we highlight the relevance of GIS in making agrobiodiversity visible at a landscape level within the context of the index. We also suggest some potential future applications related to local empowerment and agroecosystem mapping.

Human Health Risks and Interference of Urban Landscape and Meteorological Parameters in the Distribution of Pollutant: A Case Study of Nakhon Si Thammarat Province, Thailand

Recently, the air quality in urban areas has declined because of increasing traffic emissions. This paper aimed to determine the toxicity from exposure to pollutants among three sensitive groups of residents in urban areas. Moreover, this study also estimated the impacts of landscape and meteorological conditions on the accumulation of air pollutants in these areas. The results showed that the annual average concentration in the town exceeded the WHO air quality guidelines. Other areas that had a high traffic density also presented unacceptable levels according to the hazard quotient (HQ value ≥ 1). It was found that the air quality in the town had declined. This study also found that people living in a tropical monsoon climate should avoid exposure to air pollution in both the summer and rainy seasons; even though the pollutant concentration is lower in the rainy season, the longer exposure time causes unacceptable health risks. Humidity showed a strong impact on gas pollutant reduction (rs = −0.943). The pollutants tended to increase in areas with a high density of main roads. Additionally, building density affected the accumulation of pollutants in near-source areas and blocked pollutants in receptor areas. Therefore, this study suggests that local authorities should provide vegetation infrastructure for a sustainable air quality improvement in urban areas.

Effects of landscape structure and patch characteristics on the density of central populations of the eastern green lizard Lacerta viridis.

A better understanding of the impact of habitat loss on population density can be achieved by evaluating effects of both parameters within remnant habitat patches and parameters of the landscape surrounding those patches. The integration of predictors at the patch and landscape level is scarce in animal ecological studies, especially for reptiles. In this study, a patch-landscape approach was applied to evaluate the combined effects of within-patch habitat quality, patch geometry and landscape configuration and composition on the density of remnant populations of the eastern green lizard, Lacerta viridis, in a highly modified landscape in Bulgaria. Landscape composition variables (proportion of different land covers) were measured at different spatial scales surrounding patches. Single-scale models were built to evaluate combined effects of all predictors on density, when including all landscape composition variables at a specific spatial scale. Multi-scale models were applied to analyze combined effects when including landscape composition variables at the scale of their strongest effect (scale of effect, SoE). Results showed that the SoE of proportion of cropland and urban areas was small (50 m), while for proportion of habitat was large (1.5 km). The overall effect of habitat loss was better explained by the multi-scale model. Population density increased with patch area and decreased with patch shape irregularity and with the proportion of three land cover types surrounding patches-cropland, urban areas, and habitat. Combining patch and landscape parameters is important to identify ecological processes that occur simultaneously at different spatial levels and landscape scales, which would imply the application of multi-scale approaches for the protection of wild animal populations. Results are contrasted with what is known about occupancy patterns of the species in the same region and approaches to integrate both occupancy and density, in the field design of animal ecological studies are suggested.

Contribution and behavioral assessment of physical and anthropogenic factors for soil erosion using integrated deep learning and game theory

Ensuring sustainable management of soil erosion is of utmost importance to prevent its adverse effects. Unfortunately, this issue has received limited attention in the past, therefore, a comprehensive study was undertaken to identify key indicators for soil erosion and develop an Ensemble Deep Neural Network (EDNN) model for predicting soil erosion probability (SEP) zones in the Guwahati urban watershed. To conduct this study, Revised Universal Soil Loss Equation (RUSLE) was employed to estimate potential soil loss (PSL). The study identified 17 physical and landscape parameters as priority factors for soil erosion initiation based on the PSL. These priority variables were analyzed using three hyper-tuned models i.e., Gradient Boosting Machine (GBM), Random Forest (RF), and Deep Neural Network (DNN) within the H2O framework. Furthermore, the study developed EDNN and hyper-tuned DNN models to predict SEP and analyzed the behavior of priority variables in high and low soil erosion probability zones using DNN-based game theory. The findings indicated that the study area experiences soil loss ranging from 140 to 181 tonnes/ha/year. Rainfall, Ff, Dd, slope, and elevation identified as the most critical factors influencing soil erosion. The EDNN model successfully predicted very high and high SEP zones, covering 172.13 km2 and 22.60 km2 respectively. Further, the result shows that high values of drainage density, cohesion, TWI, LULC, and rainfall contribute to significant soil erosion, while low values of slope, SHDI, ED, and Ff act as preventive factors. The study offers valuable insights into the construction of an EDNN model and the integration of deep learning with game theory for robust and scientific soil erosion modeling. The analysis of behavior of the priority parameters provides a novel approach for understanding the impact of individual parameter samples on soil erosion, facilitating the development of effective prevention strategies.

Owner attitudes and landscape parameters drive stand structure and valuable habitats in small-scale private forests of Lower Saxony (Germany)

Small-scale private forests cover large areas in Europe and often contain structures and habitats of high nature conservation value that are increasingly put under pressure due to a rising interest in fuelwood and wood products. We investigate the distribution of variables like living tree and deadwood volumes, management intensity, diversity and density of tree-related microhabitats recorded in 81 small-scale private forest parcels in the Lower Saxon Hills (northwest Germany). We provide an assessment of the influence of predictors like the individual forest owners’ goals and activities, as stated by them in a quantitative survey, as well as landscape parameters like parcel size, slope, landscape fragmentation and forest continuity. Our results indicate that there are two types of structures of conservation value in small-scale private forests: slowly evolving structures (type A) like large-diameter living trees and tree-related microhabitats which mostly depend on landscape parameters that act on longer time scales, and fast evolving structures (type B) like deadwood that are influenced by both owner attitudes and landscape parameters. The resulting implications for integrative forest and conservation management are discussed. When considering the conservation of the slowly evolving type A structures, long-term commitments to conservation legislation, financial incentives and generation-spanning education of forest owners are necessary. Efforts to promote the faster evolving type B structures might prove particularly advantageous in small-scale private forests given the structural diversity of the stands, but also the often strong identification of owners with their land.Graphical abstract

Pemetaan Daya Dukung Lingkungan Lahan Basah Desa Tanjung Buka Dalam Penyediaan Air dan Pangan

Changes in land cover caused by development activities carried out by humans have occurred a lot in Indonesia. It can cause a decrease in the carrying capacity of the environment. Therefore, this study aimed to assess the status of the environmental carrying capacity of the Tanjung Buka Village wetland, geographically located at 117°21'0" - 117°40'0" EL and 2°50'0" - 3°0'0" NL, where the land cover has changed many times due to development activities. The status assessment uses an ecosystem service approach with a simple, weighted approach to mathematical modeling, by using landscape, vegetation type, and land cover parameters. The results showed that: (1) The Tanjung Buka Village wetland ecosystem is dominated by the "very low" category (26,968.70 or 62.31%) of its ecosystem services as a provider of fresh water. It means its carrying capacity is "very low" in the fresh water supply, used continuously. At the same time, Food providers tend to be in the "high" category (20,917.47 ha or 48.33%), which means that in general, the carrying capacity of the Tanjung Buka Village wetland environment is "high" as a food provider that is used continuously. It indicated that the Tanjung Buka Village wetland had changed the land cover, becoming secondary mangroves, secondary swamp forests, ponds, open land, built-up land, mixed gardens and shrubs, so that its carrying capacity becomes “very low” as a provider of fresh water, but in providing food tends to be “high”