Temporal and spatial variations in macrofouling of silicone fouling‐release coatings

This study examines landscape changes in the context of China's national Grain for Green (GFG) policy, one of the world's largest "payment for environmental/ecosystem services" (PES) programs. We explored landscape structures and dynamics between 2000 and 2010 in Shaanxi Province, the Chinese province with the greatest amount of cropland conversion and reforestation in recent decades. We used Landsat Thematic Mapper (TM)-derived data and landscape metrics for six land cover classes to determine (1) the major land cover changes during enforcement of the policy, (2) the spatial and temporal variations in these changes, and (3) the effects of land cover changes on landscape structure and dynamics. The results suggested that provincial-level land cover changes modestly reflected the goals of the GFG. Over the 10-year study period, the forest and grassland coverages expanded from 95,737.9 to 97,017.4km(2) and from 37,235.9 to 40,613.1km(2), respectively, while the cropland coverage decreased from 59,222.8 to 54,007.6km(2). The conversion direction differed regionally: the targeted croplands in Shanbei, namely, types III and IV, were mainly transformed into grassland while those in Shannan were mainly transformed into forestland. Reforestation was associated with increased inter-landscape aggregation and connection. Despite this large-scale reforestation trend, we found notable and significant differences in the land cover changes at the subprovincial level.

Multitemporal analysis (1940–1996) of land cover changes in the southwestern Bogotá highplain (Colombia)

Seasonal changes in the environment often strongly influence biological communities. In environmental transition zones, or ecotones, the environment fluctuates over time between two different types of environments and the seasonal change is more pronounced. Although emphasis has been placed on the spatial variation of biota along environmental gradients, seasonal change has not been well studied despite the seasonal nature of many ecotones. In this study, we investigated seasonal shifts in aquatic community structures of floodplain waterbodies characterised as transitions between lotic and lentic environments, and further investigated the biological processes behind the shift. We observed a clear seasonal shift of community structure in floodplain waterbodies. From the spring snowmelt season to the summer low flow season, the aquatic community structure was largely driven by the hydrological connectivity to the river, represented as the timing of the lotic-lentic transition during the seasonal flood recession. In contrast, after a few months of summer low flow period, the effect weakened over time, and the communities were structured based more on the basis of the local environment. The seasonal shift was largely explained by the change in amphibian and aquatic insect larvae, the main members of the floodplain aquatic assemblage, which metamorphose and emerge from the water during the summer period and then redistribute in different ways more strongly influenced by local environmental factors such as water body size, temperature and dissolved oxygen levels. Given that biota in ecotones occupy the habitat for a limited time due to the severe environmental fluctuations, such seasonal changes as we observed in this study may be widespread in ecotones. Landscape and local environmental conditions could alternately shape community structures in different seasons. Further attention to the temporal aspects of community structure is needed for community studies and for conservation.

Spatial and temporal variation of soil organic carbon stocks in a lake retreat area of the Ethiopian Rift Valley

According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.

Modeling the responses of grassland vegetation coverage to grazing disturbance in an alpine meadow

Comparison of spatial and temporal changes in riverine nitrate concentration from terrestrial basins to the sea between the 1980s and the 2000s in Japan: Impact of recent demographic shifts

Assemblage Organization of Stream Fishes: The Effect of Rivers on Adventitious Streams

Remote Sensing (RS) provides the best ways to monitor temporal changes and to understand land use dynamics. Remote sensing analysis can be further enhanced when community perception regarding major drivers of change is integrated. The present study was an attempt to assess the land use land cover changes in the Ishkoman watershed in the Ghizer district. The study explored Landsat-5 and Landsat-8 images to assess the LULC dynamics from 1998 to 2018, and also used questionnaires for community perception regarding LULC changes in the past two decades. Supervised classification was used to monitor changes between 1998 and 2018 and the maximum likelihood technique was used to categorize the pixels into six classes: vegetation/forest area, bare rocks, water bodies, glaciers/snow area, rivers, water, and agriculture. Regarding the questionnaires, the correlation matrix and regression models were developed between independent variables (population, land type cleared, and extra land required for new family members) and dependent variables (land use dynamics factors and socio-economic variables). The results showed that all six land cover classes have shown temporal changes between 1998-2018 and the most significant change was observed in forests and pastures (which decreased from 18.7% to 5.9 %). Similarly, glaciers, water, rivers, and agriculture have changed from 13.1, 6.5, 9.3, 1.5 to 15.8, 4.0, 11.32, 3.1, respectively between 1998-2018. The largest change was observed in bare rocks which increased from 50.2 % to 60.06%. Moreover, temporal NDVI analysis showed a decrease in vegetation cover (conversion to bare rocks) between 1998-2018. The questionnaire results revealed that the highest correlation was shown between population increase and decrease in crop production (R2 = -0.348), whereas the lowest correlation was found in population increase and population access to bus stops (R2 = -0.167). Similarly, the highest correlation was found between access to roads and markets (R2 = 0.349) and dependent variable (land type cleared), whereas the lowest correlobserved in access to water resources (R2 = -0.021). The study concluded that land use land cover has been significantly changed from 1998 to 2018 in the Ishkoman Watershed. The study suggested more in-depth research to examine land use land cover changes at finer scales by using high resolution satellite imagery, and conducting details surveys regarding the underlying anthropogenic causes of land use dynamics.

Assessing how the disturbances affect the physical structure and biodiversity of freshwater ecosystems has become a critical research priority. Bauxite mining is economically important in the Amazon, but associated infrastructure may influence freshwater biodiversity. We evaluated the effects of a bauxite ore pipeline on the community structure of semiaquatic bugs (Heteroptera: Gerromorpha) in 40 streams of the eastern Amazon, including 20 sites crossed by the pipeline and 20 control sites. We tested whether (i) species abundance and richness upstream and downstream of control sites would be higher than in pipeline sites, (ii) upstream sites would show greater abundance and richness due to species sensitivity and habitat alteration in sites crossed by the pipeline, (iii) community composition would differ between pipeline and control sites, with characteristic species for each treatment, and (iv) the pipeline would indirectly influence communities through changes in habitat quality, riparian cover, and abiotic variables. Multivariate analyses indicated clear differences in community composition, with indicator species characterizing each condition, including the species Rhagovelia jubata in pipeline streams and Stridulivelia alia and Stridulivelia strigosa in control streams. Abundance showed a tendency to be higher in control streams, whereas richness was associated with abundance but not with habitat integrity. These findings indicate that, although diversity metrics remained similar, pipeline installation is linked to changes in species composition, reflecting shifts in local environmental conditions.

This study applied time series analysis to examine land use/land cover (LULC) change and distribution in Usangu watershed and multinomial logistic regression in the GIS environment to model the influence of the related driving factors. Historical land use/cover data of the watershed were extracted from the 2000, 2006 and 2013 Landsat images using GIS and remote sensing data processing and analysis techniques. Data was analyzed using ArcMap 10.1, ERDAS Imagine, SPSS and IDRISI Selva software. Eight factors likely to influence LULC change and LULC distribution were assessed. These include elevation, slope, distance from roads, distance from rivers networks, population density, Normalized Vegetation Index (NDVI), annual rainfall and soil types. Results show that LULC changes are mainly influenced by variations in annual rainfall, population density and distance from road networks. LULC distribution is determined mainly by terrain and edaphic factors namely elevation, slope and soil types. NDVI does not influence LULC change nor determine the LULC distribution, but can be used to show concentration of LULC types on a landscape. Combination of GIS, remote sensing and statistical analysis capabilities are powerful tools for assessing and model processes of land use change and their underlying causes in terms of time and space. It is concluded that ingeniously integration of remote sensing, GIS application combined with multi-source spatial data analysis give great possibility of quantifying and explaining the temporal and spatial LULC changes and distribution in a given watershed.

Climate change is a global phenomenon which is mainly caused due to anthropogenic activities. Land use-land cover (LULC) changes occur in river basins due to human interventions and change in climate. The change in LULC causes change in evapotranspiration and contributes to further climatic change in the area. Hydrologic extremes occur in a river basin due to the combined effect of climatic extremes and LULC changes. Both climate and LULC change scenarios are usually used for estimating the variation in the hydrological response of a watershed. Hence LULC change detection and estimation is very essential for any watershed prior to the estimation of hydrologic response variation from it. The influence of LULC change on the rainfall variability of a region was studied taking the Bharathapuzha river basin which is spread over Tamil Nadu and Kerala. Bharathapuzha river is the second longest river in Kerala. Drastic changes have taken place in the river basin which caused the degradation of the river. Hence the study of the effect of LULC change in the study region on the rainfall trend is of great significance. The LULC change in the area was estimated both spatially and temporally using remote sensing-based techniques. The LANDSAT1 and LANDSAT8 satellite images for the years 1973 and 2018 were used for determining the land cover change in the study region. Necessary corrections were applied on the mosaicked images and these satellite images were classified using supervised classification. The land use change analysis was done on the classified images and the land use classes used were waterbodies, mixed vegetation, agricultural field, cultivable land, dense trees, barren land/rocky outcrop, built-up area and sandy area. It is seen that there has been severe reduction in dense trees and large increase in barren land and built-up areas over time. The rainfall trend in the study region was estimated using the data obtained from India Meteorological Department. The study indicates that LULC change is associated to the decrease in the rainfall over the area. It denotes the necessity of controlling the LULC changes in the basin for preventing further deterioration of the basin. The rainfall trend analysis also helps to devise proper management plans for the basin.KeywordsClimate changeLand use-land cover changeRainfall trendMann–kendall testSen’s slope estimator

The Arabian Sea is ecologically and environmentally significant due to its high biotic diversity and its potential role as a reservoir of emerging resistance determinants. However, molecular-level insights into the taxonomic composition, functional potential, and resistome of sediment associated communities from deep-sea seamount sediments remain limited. A metagenomic approach was employed to investigate the biotic composition, metabolic potential, resistome profiles, and physicochemical characteristics of two seamount sediment samples (SM1 and SM7) collected from the Arabian Sea. Distinct environmental conditions were observed, with SM1 enriched in inorganic nitrogen, whereas SM7 exhibited higher organic carbon content and pigment concentrations, indicating differences in substrate availability. These variations were consistent with differences in the community structure, with SM1 harbouring a less diverse assemblage dominated by Actinomycetota and fungi, while SM7 supported a broader community comprising Actinomycetota, diverse fungi, protists, metazoans, and a richer viral component. Functional annotation revealed enrichment of nitrogen metabolism pathways in SM1, whereas SM7 showed increased representation of carbohydrate metabolism and a higher proportion of novel gene content. Both sediment samples encoded antibiotic and heavy metal resistance genes; however, SM7 exhibited greater abundance and diversity of putative resistance-associated genes, including resistance to mupirocin, triclosan, and sulfonamides, along with broader metal resistance and stress response genes. The results based on two samples demonstrate pronounced sample specific variation in community structure, metabolic potential, and resistome profiles across Arabian Sea seamount sediments. These findings highlight Arabian Sea deep-sea sediments as important molecular reservoirs of microbial diversity and adaptive potential shaped by local environmental conditions.

Food webs from the Lerderderg River, an intermittent stream in Victoria, Australia, were compiled with the aim of examining changes in food web structure in a highly variable habitat. Emphasis was placed on a high degree of taxonomic precision. Spatial and temporal variation in the food webs was assessed by partitioning the study area into three sites, located ≈1.5 km apart along the river. Sites differed in overall stream width and the length of the low streamflow period during summer. Three separate webs for each site were compiled for four different times of the year. Relatively little spatial variation in community structure was observed. In contrast, temporal variation was considerable, with species composition and the number of species in the community changing considerably over the year. The number of species increased dramatically as the period of constant streamflow lengthened. Detritivores dominated the community, both in terms of species and individual numbers. The proportion of predators in the community increased slightly by the end of the year, suggesting that recolonization of the community by predators lags behind that of detritivores. The increase in the number of predator species also resulted in an increase in the mean food chain length through the year. Patterns observed in the food webs tended to fall within the range of values reported from several previous studies, suggesting that underlying constraints may structure certain aspects of food webs. However, the constancy of certain food web statistics was attributable either to methodological decisions made during compilation, or to an inherent property of the statistic itself. The potential sensitivity of several food web statistics to the methodology used to compile a food web render between—web comparisons difficult due to the confounding effects of methodology. This suggests that comparisons between food webs should be restricted to webs derived from similar habitats using a comparable methodology.

Changes in snow cover can influence root growth and distribution of herbaceous species in water limiting desert ecosystems. However, how the growth of root systems of herbaceous species responds to snow cover changes remains unclear. Thus, the present study was aimed to examine the influence of snow cover changes on root growth of herbaceous species in a temperate desert of central Asia. Plots with four snow cover depth treatments in winter were investigated in the Gurbantunggut Desert. The four treatments were snow removal (− S), ambient snow, double snow (+ S), and triple snow (+ 2S). We examined the root growth of two typical herbaceous species: one ephemeral species, Erodium oxyrhinchum, and one annual species, Ceratocarpus arenarius. The root length of the annual plant was significantly reduced by snow removal compared with the ambient treatment. The specific root length and specific surface area of the ephemeral plants increased with increasing snow depth, whereas the annual plants showed the opposite trends. Snow removal significantly increased the root–shoot ratio of the annual plants, with no effects found in the ephemeral plants. The individual root biomass and total underground biomass of the two species had similar responses to the snow depth treatments, with the highest values found with the ambient treatment. These results can contribute to explaining to changing winter snow cover depth can alter plant growth, community structure, and ecosystem function in the growing season in temperate desert ecosystems.