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Land cover change (LCC) is both a consequence and a cause of global environmental change. This paper attempts to construct a framework to reveal the driving mechanism and ecological effects of different ecological factors under LCC and to explore the ecological characteristics of future LCC. A rule-mining framework based on a land expansion analysis strategy (LEAS) in the patch-generating land use simulation (PLUS) model was used to analyze the drivers of LCC. Neighborhood analysis and ecological effect index were used to investigate multiple ecological effects of LCC. Remote sensing-based ecological indices (RSEI) and the PLUS and stepwise regression model were introduced to explore and predict the integrated ecological effect of LCC. Focusing on the Weihe River basin, study's main drivers of LCC were precipitation, temperature, elevation, population, water table depth, proximity to governments and motorways, GDP, and topsoil organic carbon were the main drivers of LCC. Change directionality were similar for the effects of greenness and biomass formation but opposite for summertime and wintertime temperature. In addition, the conversion of land cover types to cropland had the most significant integrated ecological effect, followed by forest, grassland-shrubland, and other types. The RSEI is predicted to rise to 0.77 in 2030, and the areas where the ecological quality grade will improve and decrease are concentrated on the east and west sides of Ziwuling Mountain, respectively. The findings of this study have practical significance for land management and ecological protection. • The PLUS Model is used to explore driving mechanism of land cover change (LCC). • Ecological effects of LCC are analyzed from multiple and integrated perspectives. • The integrated ecological effect of land cover types converted to cropland is the most significant. • The PLUS model with stepwise regression predicts a decreasing trend of RSEI in 2030. [ABSTRACT FROM AUTHOR]

Over the last two decades, forest cover has experienced significant impacts from fires and deforestation worldwide due to direct human activities and climate change. This paper assesses trends in forest cover loss and land use and land cover changes in northern Algeria between 2000 and 2020 using datasets extracted from Google Earth Engine (GEE), such as the Hanssen Global Forest Change and MODIS Land Cover Type products (MCD12Q1). Classification was performed using the pixel-based supervised machine-learning algorithm called Random Forest (RF). Trends were analyzed using methods such as Mann–Kendall and Sen. The study area comprises 17 basins with high rainfall variability. The results indicated that the forest area decreased by 64.96%, from 3718 to 1266 km2, during the 2000–2020 period, while the barren area increased by 40%, from 134,777 to 188,748 km2. The findings revealed that the Constantinois-Seybousse-Mellegue hydrographic basin was the most affected by deforestation and cover loss, exceeding 50% (with an area of 1018 km2), while the Seybouse River basin experienced the highest percentage of cover loss at 40%. Nonparametric tests showed that seven river basins (41%) had significantly increasing trends of forest cover loss. According to the obtained results, the forest loss situation in Algeria, especially in the northeastern part, is very alarming and requires an exceptional and urgent plan to protect forests and the ecological system against wildfires and climate change. The study provides a diagnosis that should encourage better protection and management of forest cover in Algeria. [Display omitted] • Trends of forest cover loss over northern Algeria were assessed (2000–2020). • Hanssen global forest change and MODIS database in the GEE were used. • Forest area decreased from 3718–1266 km2 (65%) and 6 basins had positive loss trends. • Seybouse River basin was the most affected in terms of percentage (40%). • The forest loss situation in Algeria is alarming and needs an urgent protection plan. [ABSTRACT FROM AUTHOR]

Forested catchments are generally assumed to provide higher quality water in opposition to agricultural and urban catchments. However, this should be tested in various ecological contexts and through the study of multiple variables describing water quality. Indeed, interactions between ecological variables, multiple land use and land cover (LULC) types, and water quality variables render the relationship between forest cover and water quality highly complex. Furthermore, the question of the scale at which land use within stream catchments most influences stream water quality and ecosystem health remains only partially answered. This paper quantifies, at the regional scale and across five natural ecoregions of Wallonia (Belgium), the forest cover effect on biological water quality indices (based on diatoms and macroinvertebrates) at the riparian and catchment scales. Main results show that forest cover – considered alone – explains around one third of the biological water quality at the regional scale and from 15 to 70% depending on the ecoregion studied. Forest cover is systematically positively correlated with higher biological water quality. When removing spatial, local morphological variations, or population density effect, forest cover still accounts for over 10% of the total biological water quality variation. Partitioning variance shows that physico-chemical water quality is one of the main drivers of biological water quality and that anthropogenic pressures often explain an important part of it (shared or not with forest cover). The proportion of forest cover in each catchment at the regional scale and across all ecoregions but the Loam region is more positively correlated with high water quality than when considering the proportion of forest cover in the riparian zones only. This suggests that catchment-wide impacts and a fortiori catchment-wide protection measures are the main drivers of river ecological water quality. However, distinctive results from the agricultural and highly human impacted Loam region show that riparian forests are positively linked to water quality and should therefore be preserved. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • We simulated land use and cover from a pristine period (Year 1500), 1960, and 1985. • We evaluated the effects of precipitation change on discharge from 1961 to 1990. • Natural vegetation fell by more than half of the original area up to 1985. • Precipitation increased by more than 20% after the 1970s global climate shift. • Results suggest that climate shift is the main driver in increasing annual discharge. [ABSTRACT FROM AUTHOR]

Integration of mining brownfields into green infrastructure(GI) planning has been widely recognized as a sustainable developmentstrategy. The key is to locate the spatial priority areas for brownfieldrestoration that would provide the greatest enhancement of themultifunctionality of the GI network. At the regional scale, a wellconnectedGI network can help maximize the benefits that it generates andachieve greater multifunctionality. In this paper, an approach forassessing the restoration priority of brownfields is proposed from the perspective of enhancing the structural connectivity of GI network. Itcan also be used as an assistance tool for planning GI networks at theregional level. The Least Cost Path (LCP) model is adopted for mapping corridors among GI patches on the basis of a resistance map composed by considering the naturalness of land covers, the riparian corridor, and disturbance of roads. Taking Fenhe River Basin (in China) as an example, three factors are jointly considered in the priority assessment of brownfields restoration: their potential contribution as corridors, their importance as stepping stones, and their resistance values. Then, we divided the brownfields into groups indicating the level of priority for restoration. The results show that 67% of the brownfields are of high or very high priority for restoration (mainly located in the north), and less than 10% area is recognized as very low or low priority. Our proposed approach could be a valuable tool for providing a macro-scale assessment of restoration priorities of brownfields for enhancing the GI network connectivity, and giving instructions for on-site redevelopment. Image 1 • Brownfields can be restored as potential elements of Green Infrastructure (GI). • The lease cost path model is adopted for simulating the corridors of GI networks. • The restoration priority of brownfields is related to their contribution to GI connectivity. • Post-mining brownfields are evaluated acting as potential stepping stones and corridors. • The proposed method can help planners to develop GI networks at a regional level. [ABSTRACT FROM AUTHOR]