Representation Of Land Use Research Articles

Pollution and the abundance of plankton in Rangkui River in Bangka Island

Land use and activity around the Rangkui Watershed affect water quality, and plankton have been studied to help manage the river's water quality. In the 2017 dry season, six station points representing land use functions from upstream to downstream were studied. Surface water sampling was carried out during the day with three replicates. Pollution around the Rangkui Watershed affected plankton abundance. Based on saprobity and physicochemical readings, the pollution level ranged from light upstream to heavy downstream. This study found 15 species from 15 families from six phytoplankton classes, that is, Bacillariophyceae, Chlorophyceae, Euglenophyceae, Cyanophyceae, Cryptophyceae, Dinophyceae, and 2 species of zooplankton Eurotatoria, and Branchiopoda. The highest total abundance of phytoplankton and zooplankton was observed upstream of Station 1 (721 ind/L) and gradually decreased downstream, with the exception of the absence of plankton at Station 3. Nitrate had a positive correlation with phytoplankton at different correlation levels, whereas other abiotic environments responded differently to phytoplankton and zooplankton. The water quality is highest upstream, where there are pepper plantations, and gradually decreases as it flows downstream. The station near tin mining activities was the most polluted.

Effects of land use patterns on soil properties and nitrous oxide flux on a semi-arid environmental conditions of Loess Plateau China

Ecosystems and agroecosystems strongly influences the global warming by nitrogen oxide (N2O) emission. In a recent climate change scenario, nitrogen and carbon sequestration is obligatory under different land-use patterns. However, soil nitrogen elements and carbon content in the recover process of degraded environmental conditions on the Dingxi Loess Plateau has not been clearly understood. Thus, in this current study, we selected four representative land use patterns, including picea asperata (PA), which is based on forest land; Medicago sativa (MS), which is based on grassland; abandoned bare land (AL), which is based on abandoned land; and wheat field (WF), which is based on farmland, to study soil quality indicators and N2O greenhouse gas and relationships amongst environmental factors and N2O flux. Our results depicted that PA and MS significantly increased organic carbon (SOC), total phosphorous (TP), gravimetric water content (SWC), soil bulk density (BD), total nitrogen (TN), ammonium nitrogen (NH4+-N), and microbial biomass nitrogen (MBN) whist decreased soil nitrate nitrogen (NO3--N) content and soil pH value over AL land-use pattern. However, WF land-use pattern showed reduced trend of above mention studied parameters than AL. Additionally, compared to AL, PA and MS significantly reduced the total soil N2O emissions, with reductions of 24.91% and 14.77% in 2021 and 29.08% and 17.53% in 2022, respectively. The WF significantly increased the total N2O emissions, increasing by 53.18% and 40.37% in 2021 and 2022, respectively. Moreover, environmental variables for instance aerial temperature, precipitation had significant correlation with soil N2O based on linear regression analysis, soil NO3--N and soil temperature had significant positive correlation with soil N2O flux while NH4+-N, BD, and SWC were negatively correlated with N2O flux. The Partial Least Squares Path Model (PLS-PM) indicates that soil temperature and soil moisture was the dominant factor for controlling soil N2O emissions followed by soil nutrients and land use patterns. Accordingly, in the context of vegetation restoration process of the study area, the proportion of forest land and grassland should be increase to cope with future climate change scenario. This research result can provide theoretical basis and technical support for scientific understanding and evaluation of soil N2O emission mechanisms and nitrogen sink functions under different land-use patterns in semi-arid region of China.

Land-Use Change Effects on Soil Erosion: The Case of Roman “Via Herculia” (Southern Italy)—Combining Historical Maps, Aerial Images and Soil Erosion Model

Land use and land cover (LULC) strongly influence soil erosion/sediment yield, and predicting changes in soil erosion is an important management strategy. Tracing the Earth’s past also helps us better understand the future evolution of the landscape, but research using modern mapping capabilities is hampered by the scarcity of historical landscape information. To fill the data gap and provide an example of how historical maps might be used in land-use change research, we combined an old paper map based on the IT Military Topographical Institute (ITM), aerial photos, and orthophotos to derive land-use history and landscape dynamics at fine scales for a segment of the Roman route “Via Herculia” located in the north-western sector of the Basilicata Region, Italy. Three LULC scenarios were then analysed to represent land use in 1870, 1974, and 2013. Starting from such scenarios, we applied a soil erosion model (Unit Stream Power Eosion and Deposition—USPED) to understand how land-use change over time has modified the areas subject to erosion and deposition. The results show an increase in erosion (from 17% to 20% of the total area) and sediment deposition (from 15% to 19%) over the period 1870–1974. In contrast, over the period of 1974–2013, the results show a decrease in gross erosion (from 20% to 14% of the total area) and sediment deposition (from 19% to 13%).

Estimating the runoff response from hillslopes treated with soil and water conservation structures in the semi-arid Ethiopian highlands: Is the curve number method applicable?

Planning and management of water resources is crucial to enhance agricultural productivity and ensure food security in drylands. For this, adaptable and reliable runoff prediction models are urgently needed to support water harvesting and irrigation development. In this study we explored the potential of the runoff Curve Number (CN) method to estimate daily surface runoff from representative land use types and management conditions in Tigray (north Ethiopia). For this, we use the National Engineering Handbook (NEH-Tables) to derive CN values for runoff plots treated with and without soil and water conservation (SWC) structures. Moreover, the rainfall-runoff data collected from 21 large (600–1000 m2) runoff plots during three years (2010 to 2012) were used to calculate CN-values. Results show that CN values derived from the NEH-Tables are larger by 21% compared to those values calculated from plot data. The calculated CN values vary widely (34 to 91) in response to land use type, slope gradient, and applied SWC structures. Our results show that land use and SWC structures strongly influence runoff production. Considering plots with otherwise similar characteristics, CN values are consistently larger for rangeland sites as compared to those values for cropland sites. Likewise, SWC structures greatly reduce runoff production and their presence also leads to a clearly lower performance of the CN model. The results of this study are relevant contributions towards addressing several goals of agenda 2063 of the African union either directly or indirectly and also international sustainable development goals (SDG). Based on our analysis and field observations, we propose calibrated CN values that may be used for runoff yield assessments in similar environments.

Microbial source tracking and land use associations for antibiotic resistance genes in private wells influenced by human and livestock fecal sources.

Antimicrobial resistance is a growing public health problem that requires an integrated approach among human, agricultural, and environmental sectors. However, few studies address all three components simultaneously. We investigated the occurrence of five antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in private wells drawing water from a vulnerable aquifer influenced by residential septic systems and land-applied dairy manure. Samples (n=138) were collected across four seasons from a randomized sample of private wells in Kewaunee County, Wisconsin. Measurements of ARGs and intI1 were related to microbial source tracking (MST) markers specific to human and bovine feces; they were also related to 54 risk factors for contamination representing land use, rainfall, hydrogeology, and well construction. ARGs and intI1 occurred in 5%-40% of samples depending on target. Detection frequencies for ARGs and intI1 were lowest in the absence of human and bovine MST markers (1%-30%), highest when co-occurring with human and bovine markers together (11%-78%), and intermediate when co-occurring with just one type of MST marker (4%-46%). Gene targets were associated with septic system density more often than agricultural land, potentially because of the variable presence of manure on the landscape. Determining ARG prevalence in a rural setting with mixed land use allowed an assessment of the relative contribution of human and bovine fecal sources. Because fecal sources co-occurred with ARGs at similar rates, interventions intended to reduce ARG occurrence may be most effective if both sources are considered.

Assessing amount of soil organic carbon and some soil properties under different land uses in a semi-arid region of northern Türkiye

The objective of this study is to investigate the effects of representative land use types and land cover (LUT/LC) of heavily deforested areas on soil properties in semi-arid region of Türkiye. Some of the soil properties have been measured on a grid with a 50 m sampling distance on the top-soil (0-15 cm depth). Data has been analyzed by using Ordinary Kriging/Spherical geostatistical model. Results indicated that the soil properties differed in terms of organic carbon (SOC), pH, bulk density, and the amount of sand, depending on the land uses in the study areas. The SOC concentration of top-soil layers has referred a significant difference (P<0.05) according to the land use type. Top-soil SOC concentrations in the four LUTLCs have been in the following order: cultivated areas < grasslands < Scotch pine stands = Uludağ fir stands. The impacts of LUTLC change on SOC and soil properties have not been restricted to the soil surface; however, relative changes have equally been high in the sub-soil, stressing the importance of sufficiently deep sampling. Furthermore, it has been determined that some physical and chemical characteristics of the natural forest soil have been significantly changed after long term and continuous cultivation. SOC loss is remarkable under the land use conversion while cropland has considerable potential to sequester SOC.

Mapping Secondary Vegetation of a Region of Deforestation Hotspot in the Brazilian Amazon: Performance Analysis of C- and L-Band SAR Data Acquired in the Rainy Season

The re-suppression of secondary vegetation (SV) in the Brazilian Amazon for agriculture or land speculation occurs mostly in the rainy season. The use of optical images to monitor such re-suppression during the rainy season is limited because of the persistent cloud cover. This study aimed to evaluate the potential of C- and L-band SAR data acquired in the rainy season to discriminate SV in an area of new hotspot of deforestation in the municipality of Colniza, northwestern of Mato Grosso State, Brazil. This is the first time that the potential of dual-frequency SAR data was analyzed to discriminate SV, with an emphasis on data acquired during the rainy season. The L-band ALOS/PALSAR-2 and the C-band Sentinel-1 data acquired in March 2018 were processed to obtain backscattering coefficients and nine textural attributes were derived from the gray level co-occurrence matrix method (GLCM). Then, we classified the images based on the non-parametric Random Forest (RF) and Support Vector Machine (SVM) algorithms. The use of SAR textural attributes improved the discrimination capability of different LULC classes found in the study area. The results showed the best performance of ALOS/PALSAR-2 data classified by the RF algorithm to discriminate the following representative land use and land cover classes of the study area: primary forest, secondary forest, shrubby pasture, clean pasture, and bare soil, with an overall accuracy and Kappa coefficient of 84% and 0.78, respectively. The RF outperformed the SVM classifier to discriminate these five LULC classes in 14% of overall accuracy for both ALOS-2 and Sentinel-1 data sets. This study also showed that the textural attributes derived from the GLCM method are highly sensitive to the moving window size to be applied to the GLCM method. The results of this study can assist the future development of an operation system based on dual-frequency SAR data to monitor re-suppression of SV in the Brazilian Amazon or in other tropical rainforests.

WHO SPEAKS FOR THE FOREST? LOCAL KNOWLEDGE, PARTICIPATORY MAPPING AND COLLABORATIVE EVALUATION FOR GIS ANALYSIS IN THE TROPICS OF CENTRAL BALI, INDONESIA

Abstract. This paper describes a land survey of the Bedugul area in Central Bali that was constructed using multi-temporal and multi-spectral data collected from a new class of commercially available satellites to produce detailed land cover mappings. The paper discusses the significance of the land area under investigation, including difficulties in reading land cover features in the tropics. It describes participatory field mapping efforts set in place in order to complement the reading of remote sensing assets and our attempts to represent land use features of particular interest to a local NGO. We further discuss the challenges and opportunities of representing land cover and use scenarios that satellite assets can only partially capture. We use band operations and object-based classification methods to represent change in settlement activity in the area under observation. We also describe a collaborative cloud-based analysis and evaluation pipeline that facilitates the processing of different sources of remote sensing data as well as the representation of various types of land use scenarios defined with the assistance of local knowledge.

Spatial Relationship between Land Use Patterns and Ecosystem Services Value—Case Study of Nanjing

The degree of land use reflects the progress of social and economic development; however, it also has a direct impact on land resources. Maximizing the ecosystem services of land resources in a limited space is a key issue in China’s rapid urbanization. Therefore, this study aims to analyze the spatial relationship between land use patterns and ecosystem services to enhance the benefits of urban ecology. First, we used the landscape pattern index to represent land use patterns and the equivalence factor method to quantify the ecosystem services value (ESV); second, spatial autocorrelation and spatial autoregression were used to explore the spatial relationship between the landscape pattern index and ESV. Our main conclusions were that (1) the landscape pattern index and ESV both showed obvious spatial aggregation, but that of ESV was more significant; (2) the largest patch index and contagion index had a greater degree of influence on ESV than other variables, with the largest patch index having a positive effect and the contagion index having a negative effect; (3) it was necessary to cultivate the landscape dominance of land patches in ecological spatial regulation and to form large-scale ecological agglomeration in key ecological source areas and nodes. The research results can ensure that land resources exert a higher level of ecological value by adjusting the spatial form of the landscape patch.

Distribution and population status of Adansonia digitata L. (baobab) and its contribution to livelihood in Makueni County, Kenya

Adansonia digitata L. commonly known as baobab is a globally known high valued multipurpose tree. The current study was designed to map the distribution and determine the effects of different land use systems (cropland, grazing land and settlement area) on the species population density, composition, health and productivity in Makueni County. Livelihood potential of baobab in the studied area was also assessed. Two sub counties; Kibwezi East and West in Makueni County where baobab populations occur were purposely selected for this study. A reconnaissance study was carried out followed by selection of three contrasting representative land use systems: Namely cropland, grazing land and settlement area/homesteads using Google Map through a desktop study. Plots of 0.5 km long and 0.25 km wide were used to assess the population and health status of baobab trees. Market centers and chiefs’ camps were randomly sampled for a household and market survey where a total of 423 informants were interviewed. Baobab growth characteristics across the three land use systems in the two sub counties as well as household and market data were analyzed using GraphPad Prism version 8.4.3. The waypoints were downloaded from the Garmin etrex 10 GPS handset into Arc Map 1.0 of Arc Geographic Information System (GIS) (ESRI, Redlands, CA) where the baobab distribution maps were generated. The findings revealed that the baobab populations occurred in clusters of high to low density. Density and fruit production of baobab trees were statistically different across the three land use systems in the two sub counties while height, DBH and crown diameter did not differ significantly. No saplings were found in the study area. The study revealed that there is a huge potential for baobab fruits in diet especially during food scarcity. Therefore, farmer training is advisable to augment local knowledge and skills for enhanced value addition of baobab products.

High-resolution land use and land cover dataset for regional climate modelling: a plant functional type map for Europe 2015

Abstract. The concept of plant functional types (PFTs) is shown to be beneficial in representing the complexity of plant characteristics in land use and climate change studies using regional climate models (RCMs). By representing land use and land cover (LULC) as functional traits, responses and effects of specific plant communities can be directly coupled to the lowest atmospheric layers. To meet the requirements of RCMs for realistic LULC distribution, we developed a PFT dataset for Europe (LANDMATE PFT Version 1.0; http://doi.org/10.26050/WDCC/LM_PFT_LandCov_EUR2015_v1.0, Reinhart et al., 2021b). The dataset is based on the high-resolution European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset and is further improved through the additional use of climate information. Within the LANDMATE – LAND surface Modifications and its feedbacks on local and regional cliMATE – PFT dataset, satellite-based LULC information and climate data are combined to create the representation of the diverse plant communities and their functions in the respective regional ecosystems while keeping the dataset most flexible for application in RCMs. Each LULC class of ESA-CCI is translated into PFT or PFT fractions including climate information by using the Holdridge life zone concept. Through consideration of regional climate data, the resulting PFT map for Europe is regionally customized. A thorough evaluation of the LANDMATE PFT dataset is done using a comprehensive ground truth database over the European continent. The assessment shows that the dominant LULC types, cropland and woodland, are well represented within the dataset, while uncertainties are found for some less represented LULC types. The LANDMATE PFT dataset provides a realistic, high-resolution LULC distribution for implementation in RCMs and is used as a basis for the Land Use and Climate Across Scales (LUCAS) Land Use Change (LUC) dataset which is available for use as LULC change input for RCM experiment set-ups focused on investigating LULC change impact.

Analysis of the Relationship between Climate Change and Land Use Change using the ESA CCI Land Cover Maps in Sungai Kelantan Basin, Malaysia

Climate and land use land cover (LULC) are two major key drives that affect the hydrological cycle pattern within a river basin. This study aims to evaluate the capability of the European Space Agency Climate Change Initiative land cover (ESA CCI LC) product in representing land use pattern in Sungai Kelantan Basin (KRB), Malaysia; to analyze the changes of rainfall, maximum and minimum temperatures of the KRB from 1979 to 2018; and to assess the relationships between climate and land use changes within KRB. The results show that the ESA CCI LC product is applicable to represent LULC of the KRB, with an overall accuracy of 74.72% and a Kappa coefficient of 0.66. Trend analysis indicates that maximum and minimum temperatures of the KRB increased significantly at 95% confident level by 0.01 to 0.03 °C/year and 0.01 to 0.05 °C/year, respectively. Whereas annual precipitation at the Pos Hau, Pos Bihai, Pos Gob, and Kuala Krai stations increased significantly with the rates of 17.5 to 29.74 mm/year. The correlation shows that urban expansion in Gua Musang had a strong correlation with annual rainfall with a correlation coefficient (CC) value of -0.78. Furthermore, the conversion of forest into croplands over the Tanah Merah increased the minimum temperature significantly, with a CC value of -0.73. The findings show that the changes of land use in the middle basin contributed to the variations in temperature.

Intense wet-dry cycles weakened the carbon sequestration of soil aggregates in the riparian zone

Increasing the frequency and magnitude of wet-dry cycles can fundamentally affect soil carbon (C) turnover. However, the response of soil respiration to intense wet-dry cycles in the riparian zone is unclear. Hence, this study aimed to identify whether soil respiration and soil aggregates in different land use types were affected by different flooding intensities in the riparian zone of the Three Gorges Reservoir, China, and determine the responses of soil organic carbon (SOC) sequestration by soil aggregates to wet-dry cycles in the riparian zone. At the Wuyangwan of the Pengxi River, a tributary of the Yangtze River in the Three Gorges Reservoir, soil respiration and soil aggregates were investigated at different elevations of the riparian zone with representative land use types, namely a cornfield (173C) and a paddy field (173P), both at an elevation of 173 m above sea level, and two paddy fields, 168 m and 163 m above sea level (168P and 163P). The results showed that soil aggregate stability increased (e.g., the mean weight diameter increased by 38% and 18% for 173C and 173P, respectively) in the low flooding intensity sites and decreased (e.g., the mean weight diameter decreased by 44% and 33% for 168P and 163P, respectively) in strong flooding intensity sites after four wet-dry cycles in the riparian zone of the Three Gorges Reservoir. Moreover, the wet-dry cycles increased soil respiration (i.e., the soil respiration increased by 36%, 218%, 129%, and 31% for 173C, 173P, 168P, and 163P, respectively). In addition, soil aggregate stability had a direct negative effect on soil respiration (namely, the mitigation of CO2 emissions), and the negative effect weakened after four intense wet-dry cycles (pathway coefficient was −0.76 in 2014 and −0.28 in 2018). Thus, the carbon sequestration of soil aggregates was weakened in the riparian zone. The size of the soil aggregate fractions and their organic carbon contents directly or indirectly affected soil respiration. Most notably, the proportion of microaggregates and their associated nitrogen and organic carbon contents strongly influenced soil respiration. Finally, from the perspective of maintaining soil aggregate stability and SOC sequestration, we suggest that agricultural activities should be prohibited in areas with high flooding intensity in the riparian zones.

Land Use and Cover Changes versus climate shift: Who is the main player in river discharge? A case study in the Upper Paraná River Basin

Assessing the relative contribution of Land Use and Cover Changes (LUCC) and climate changes on runoff still represents a great challenge for water resources management. This issue is particularly critical for the Upper Paraná River Basin (UPRB), one of the most important basins in South America and responsible for most of the production of food, ethanol, and electricity generation in Brazil. In this paper, we used the Soil and Water Assessment Tool (SWAT) to quantitatively assess the relative contribution of both forcings. The simulation period included a time of great importance for climate studies, known as the 1970s global climate shift, and of great impact on river discharge within the UPRB. Three land use and cover scenarios were assigned to the 1961–1990 period of simulations, representing land use and cover during a pristine period (around the Year 1500), 1960, and 1985. Thirteen years of precipitation before and after the climate shift (considered to be the period 1974–1977) were analyzed and compared. Results showed a precipitation increase for the basin in general after the climate shift. The increase in rainfall reached up to 15% in many northern areas and more than 20% in the southern parts of the basin. By comparing all simulations, results indicate that both LUCC and precipitation increase due to the climate shift had a significant effect on the changes in annual discharge of the largest rivers of the UPRB. However, the results suggest that the impact of the precipitation increase on the discharge exceeded that of the LUCC. Between 1960 and 1985 the LUCC accounts for about 16% of the increase of the median annual discharge, whereas climate shift accounts for an increase of about 32%. These findings, suggesting a more relevant role for the climate, are consistent with two recent water crisis experienced by the country in the last decades, caused by prolonged below-normal rainfall throughout 2001/2002 and again in 2014/2015.

A novel strategy to assimilate category variables in land-use models based on Dirichlet distribution

Data assimilation is an effective approach to reduce the propagation and cumulative errors of land use models. However, as the discrete categorical outputs of land use models, land use data assimilation requires a novel approach distinguished from the traditional assimilation for continuous variables. Here, Bayesian inference for categorical distribution is introduced into a land use cellular automata model to update multiple discrete state variables. The accuracies with data assimilation outperform those of simulation-only. By 2009, kappa coefficient and figure of merit in the entire area increase by 0.34% and 1.78%, respectively, and in fine-scale areas where drastic and representative land use changes occurred, increase by 23.88% and 38.39%, respectively. The assimilation performance is associated with the landscape patch size and the length of the assimilation cycle. This study innovatively introduces the conjugate prior features of Dirichlet distribution into land use assimilation, providing insights and references for discrete variable data assimilation.

Universal Digital Twin: Land use

AbstractThis article develops an ontological description of land use and applies it to incorporate geospatial information describing land coverage into a knowledge-graph-based Universal Digital Twin. Sources of data relating to land use in the UK have been surveyed. The Crop Map of England (CROME) is produced annually by the UK Government and was identified as a valuable source of open data. Formal ontologies to represent land use and the geospatial data arising from such surveys have been developed. The ontologies have been deployed using a high-performance graph database. A customized vocabulary was developed to extend the geospatial capabilities of the graph database to support the CROME data. The integration of the CROME data into the Universal Digital Twin is demonstrated in two use cases that show the potential of the Universal Digital Twin to share data across sectors. The first use case combines data about land use with a geospatial analysis of scenarios for energy provision. The second illustrates how the Universal Digital Twin could use the land use data to support the cross-domain analysis of flood risk. Opportunities for the extension and enrichment of the ontologies, and further development of the Universal Digital Twin are discussed.

River Flow Modelling for Sustainable Operation Of Hydroelectric Power Plant in the Taludaa-Gorontalo Watershed

River flow discharge is generally measured by multiplying the cross-sectional river area at the measurement point with the flow velocity. However, this approach cannot be used for planning needs which involves knowing the changes in discharge values at all times, which are directly affected by the variations in weather conditions and catchment area systems. This is necessary because planning errors usually lead to unsustainable and interrupted operations. It is possible to determine the changes in the river discharge values using the rainfall-runoff modelling technique through the hydrograph output of the model. Therefore, this study used hydrological modelling techniques to obtain a watershed's spatial and temporal river flow discharge. This involved using parameters such as watershed area, curve number representing land use and soil type, time lag as the delay between maximum rainfall and the occurrence of peak discharge, and the initial abstraction that considers all the losses before the runoff occurred. Moreover, rainfall data were obtained from an ARR station installed around the watershed area, while water level data were retrieved through an AWLR station installed in the river at the debit measurement point. The model was analyzed using HEC-HMS software, while the dependable discharge for power plants was analyzed using the flow duration curve method. The results showed that the rainfall-runoff hydrological modelling technique applied to the Taludaa-Gorontalo sub-watershed could ensure the continuous and sustainable operation of the hydroelectric power plant.

The Impacts of Urbanisation on Landscape and Environment: The Case of Slovakia

The development of urbanisation is linked to qualitative and quantitative changes in the landscape and its components aimed at strengthening economic, administrative and cultural-social functions, which are associated with ever-increasing pressures on ecosystems and their individual components. These pressures are subject to various factors—socio-economic, political, environ-mental, etc. In this paper, we present an evaluation of the environmental impacts of the development of urbanisation in Slovakia. Independent Slovakia belongs to the young European states. The communist period lasted from 1948 to 1989. The character of landscape, the quality of the environment and also the degree of anthropisation of territory were dependent on a centrally managed economy. Urbanisation changes began to manifest themselves rapidly after 2000, when the economy was transformed and Slovakia was preparing to join the European Union (Slovakia joined the European Union in 2004). The transformation from central planning into a market economy was the basis of the changes, which was conditioned following strong pressure of investors on the landscape, the construction of technological parks, shopping and logistics centres and transport infrastructure and the construction of residential complexes. According to the European Environment Agency’s study on urban sprawl between the mid-1950s and the end of the 1990s, industry, commercial and transport services have grown at a significant rate and the residential areas at a moderate rate in Slovakia. On the other hand, Slovakia has areas where urbanisation has the opposite trend. Rural settlements are abandoned as well as large areas of agricultural land. The character of land use has fundamentally changed over the past 20 years. These changes not only have a spatial dimension but are associated with the emergence of various environmental problems. The paper deals with the impacts of anthropisation and industrialisation of Slovakia after 2000. The anthropisation process in Slovakia was determined through data processed in GIS and also through the statistical data representing land use. Based on the ecological significance of land use elements, the degree of anthropisation in Slovakiawas calculated.

Working Together for Grizzly Bears: A Collaborative Approach to Estimate Population Abundance in Northwest Alberta, Canada

Grizzly bears are a threatened species in Alberta, Canada, and their conservation and management is guided by a provincial recovery plan. While empirical abundance and densities estimates have been completed for much of the province, empirical data are lacking for the northwest region of Alberta, a 2.8 million hectare area called Bear Management Area 1 (BMA 1). In part, this is due to limited staff capacity and funding to cover a vast geographic area, and a boreal landscape that is difficult to navigate. Using a collaborative approach, a multi-stakeholder working group called the Northwest Grizzly Bear Team (NGBT) was established to represent land use and grizzly bear interests across BMA 1. Collectively, we identified our project objectives using a Theory of Change approach, to articulate our interests and needs, and develop common ground to ultimately leverage human, social, financial and policy resources to implement the project. This included establishing 254 non-invasive genetic hair corral sampling sites across BMA 1, and using spatially explicit capture-recapture models to estimate grizzly bear density. Our results are two-fold: first we describe the process of developing and then operating within a collaborative, multi-stakeholder governance arrangement, and demonstrate how our approach was key to both improving relationships across stakeholders but also delivering on our grizzly bear project objectives; and, secondly we present the first-ever grizzly bear population estimate for BMA 1, including identifying 16 individual bears and estimating density at 0.70 grizzly bears/1,000 km2-the lowest recorded density of an established grizzly bear population in Alberta. Our results are not only necessary for taking action on one of Alberta's iconic species at risk, but also demonstrate the value and power of collaboration to achieve a conservation goal.

Pinpointing optimized air quality model performance over the Beijing-Tianjin-Hebei region: Mosaic approach

Mosaic approach, with certain number of tiles representing land use (LU) types in each grid cell, had been implemented into WRF-Noah model. Previous studies found mosaic approach had a better performance on meteorological parameters than only considering dominant LU in dominant approach. In this study, the impacts of mosaic approach on meteorological parameters and air quality were investigated in WRF-CMAQ over Beijing-Tianjin-Hebei (BTH) region in China in 2020. Results showed that mosaic approach improved the simulation results of WS10 (surface wind speed at 10 m), T2 (temperature at 2 m), and RH (relative humidity) especially in nighttime in winter and were available for all stations with different percent of urban area. “MOS_TOPO” scenario, which coupled with mosaic approach and “topo-wind” schemes, obtained best simulation results of WS10 and T2 in January among six scenarios, with the lower average Root Mean Square Error of WS10 (1.18 m/s) and Mean Bias of T2 (0.55 °C) for all stations. Meanwhile, mosaic approach obtained lower |NMB| of PM2.5 than dominant approach in more than 69% cities in BTH region. Cities in southern Hebei province, especially Xingtai city, were identified as the most sensitive area for PM2.5 simulation affected by mosaic approach. Although the mosaic approach has improved the simulation results of meteorological parameters, especially the nighttime simulation results of WS10, there is still some deviation in the simulation results of PM2.5. Accurate emission inventory, suitable physics option in numerical weather model and rational chemical mechanism in air quality model are the important factors for WRF-CMAQ.