Publications by authors named "Saskia Keesstra"

It is crucial for understanding the variations of carbon and nutrient pools within the ecosystems during long-term vegetation restoration to accurately assess the effects of different ecological restoration patterns. However, the long-term spatio-temporal variations of carbon and nutrient pools under different vegetation types remain unclear. The sites for long-term natural and planted forests (i.

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Climate-smart sustainable management of agricultural soil is critical to improve soil health, enhance food and water security, contribute to climate change mitigation and adaptation, biodiversity preservation, and improve human health and wellbeing. The European Joint Programme for Soil (EJP SOIL) started in 2020 with the aim to significantly improve soil management knowledge and create a sustainable and integrated European soil research system. EJP SOIL involves more than 350 scientists across 24 Countries and has been addressing multiple aspects associated with soil management across different European agroecosystems.

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This study explores how a vegetation cover (VC) index can be employed as a pollution warning tool in gold mining areas in the Northwest of Iran. The analysis included the following: (a) the extraction of normalized difference vegetation index (NDVI) maps from Landsat images in three zones, i.e.

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The major event that hit Europe in summer 2021 reminds society that floods are recurrent and among the costliest and deadliest natural hazards. The long-term flood risk management (FRM) efforts preferring sole technical measures to prevent and mitigate floods have shown to be not sufficiently effective and sensitive to the environment. Nature-Based Solutions (NBS) mark a recent paradigm shift of FRM towards solutions that use nature-derived features, processes and management options to improve water retention and mitigate floods.

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Forest fires impact on soil, water, and biota resources. The current forest fires in the West Coast of the United States (US) profoundly impacted the atmosphere and air quality across the ecosystems and have caused severe environmental and public health burdens. Forest fire led emissions could significantly exacerbate the air pollution level and, therefore, would play a critical role if the same occurs together with any epidemic and pandemic health crisis.

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The United Nations Sustainable Development Goal 6 aims for clean water and sanitation for all by 2030, through eight subgoals dealing with four themes: (i) water quantity and availability, (ii) water quality, (iii) finding sustainable solutions and (iv) policy and governance. In this opinion paper, we assess how soils and associated land and water management can help achieve this goal, considering soils at two scales: local soil health and healthy landscapes. The merging of these two viewpoints shows the interlinked importance of the two scales.

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This special issue provides an assessment of the contribution of soils to Nature's Contributions to People (NCP). Here, we combine this assessment and previously published relationships between NCP and delivery on the UN Sustainable Development Goals (SDGs) to infer contributions of soils to the SDGs. We show that in addition to contributing positively to the delivery of all NCP, soils also have a role in underpinning all SDGs.

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This theme issue provides an assessment of the contribution of soils to Nature's Contributions to People (NCP). The papers in this issue show that soils can contribute positively to the delivery of all NCP. These contributions can be maximized through careful soil management to provide healthy soils, but poorly managed, degraded or polluted soils may contribute negatively to the delivery of NCP.

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Flooding is a destructive natural phenomenon that causes many casualties and property losses in different parts of the world every year. Efficient flood susceptibility mapping (FSM) can reduce the risk of this hazard, and has become the main approach in flood risk management. In this study, we evaluated the prediction ability of artificial neural network (ANN) algorithms for hard and soft supervised machine learning classification in FSM by using three ANN algorithms (multi-layer perceptron (MLP), fuzzy adaptive resonance theory (FART), self-organizing map (SOM)) with different activation functions (sigmoidal (-S), linear (-L), commitment (-C), typicality (-T)).

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Forest fires and post-fire management practices (PFMP) cause changes in the hydrological response of a hillslope. This study evaluates the effect of log erosion barriers (LB) and Easy-Barriers® (EB) on the spatial patterns and values of structural sediment connectivity (SC) in a Mediterranean mountainous pine forest affected by an arson fire in August 2017. A drone flight was done in July 2019 (23 months after the fire and 11 months after the PFMP) to obtain a high-resolution orthomosaic and DEM (at 0.

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Ecosystem Services (ESs) are bundles of natural processes and functions that are essential for human well-being, subsistence, and livelihoods. The 'Green Revolution' (GR) has substantial impact on the agricultural landscape and ESs in India. However, the effects of GR on ESs have not been adequately documented and analyzed.

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Demarcation of conservation priority zones (CPZs) using spatially explicit models is the new challenge in ecosystem services (ESs) research. This study identifies the CPZs of the Indian Sundarbans by integrating 2 different approaches, that is, ESs and ecosystem health (EH). Five successive steps were followed to conduct the analysis: First, the ESs were estimated using biophysical and economic methods and a hybrid method (that combines biophysical and economic methods); second, the vigor-organization-resilience (VOR) model was used for estimating EH; third, the risk characterization value (RCV) of ESs was measured using the function of EH and ESs; fourth, Pearson correlation test was performed to analyze the interaction between ESs and EH components; and fifth, the CPZs were defined by considering 7 relevant components: ecosystem vigor, ecosystem organization, ecosystem resilience, RCV, EH, ESs, and the correlation between EH and ESs.

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Remote sensing techniques are effectively used for measuring the overall loss of terrestrial ecosystem productivity and biodiversity due to forest fires. The current research focuses on assessing the impacts of forest fires on terrestrial ecosystem productivity in India during 2003-2017. Spatiotemporal changes of satellite remote sensing derived burn indices were estimated for both fire and normal years to analyze the association between forest fires and ecosystem productivity.

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Most of the Earth's Ecosystem Services (ESs) have experienced a decreasing trend in the last few decades, primarily due to increasing human dominance in the natural environment. Identification and categorization of factors that affect the provision of ESs from global to local scales are challenging. This study makes an effort to identify the key driving factors and examine their effects on different ESs in the Sundarbans region, India.

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Our Planet suffers from human activities. As scientists, we know more and more about our environment, about processes, rates of change, new threats, and risks. However, the challenges we face seem to grow quicker than the solutions we can create.

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In November 2016, the urban dry streams (wadis) of the city of Haifa in Northern Israel were on fire. However, it was not just the fire that was threatening urban areas. Post-fire precipitation could turn into urban floods, further aggravating the fire damages.

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Grassland degradation resulting from desertification often alters the carbon (C), nitrogen (N) and phosphorus (P) cycles within grassland ecosystems. To estimate the effects of desertification on the C, N, and P concentrations and C:N:P stoichiometry of plants and soil, we examined C, N, and P concentrations in plant tissues (leaves, roots and litter) and soil across five degrees of desertification in the desert grassland of Ningxia, China (control, light, moderate, severe and very severe desertification stages). The C, N, and P concentrations and C:N:P stoichiometry of the leaves, roots and litter differed among the different desertification stages.

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Ecosystem Services (ESs) refer to the direct and indirect contributions of ecosystems to human well-being and subsistence. Ecosystem valuation is an approach to assign monetary values to an ecosystem and its key ecosystem goods and services, generally referred to as Ecosystem Service Value (ESV). We have measured spatiotemporal ESV of 17 key ESs of Sundarbans Biosphere Reserve (SBR) in India using temporal remote sensing (RS) data (for years 1973, 1988, 2003, 2013, and 2018).

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Gully erosion is one of the most effective drivers of sediment removal and runoff from highland areas to valley floors and stable channels, where continued off-site effects of water erosion occur. Gully initiation and development is a natural process that greatly impacts natural resources, agricultural activities, and environmental quality as it promotes land and water degradation, ecosystem disruption, and intensification of hazards. In this research, an attempt is made to produce gully erosion susceptibility maps for the management of hazard-prone areas in the Pathro River Basin of India using four well-known machine learning models, namely, multivariate additive regression splines (MARS), flexible discriminant analysis (FDA), random forest (RF), and support vector machine (SVM).

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Land subsidence caused by land use change and overexploitation of groundwater is an example of mismanagement of natural resources, yet subsidence remains difficult to predict. In this study, the relationship between land subsidence features and geo-environmental factors is investigated by comparing two machine learning algorithms (MLA): maximum entropy (MaxEnt) and genetic algorithm rule-set production (GARP) algorithms in the Kashmar Region, Iran. Land subsidence features (N = 79) were mapped using field surveys.

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For many years, scientists have tried to understand, describe and quantify water and sediment fluxes, with associated substances like pollutants, at multiple scales. In the past two decades, a new concept called connectivity has been used by Earth Scientists as a means to describe and quantify the influences on the fluxes of water and sediment on different scales: aggregate, pedon, location on the slope, slope, watershed, and basin. A better understanding of connectivity can enhance our comprehension of landscape processes and provide a basis for the development of better measurement and modelling approaches, further leading to a better potential for implementing this concept as a management tool.

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Assessment of watershed health and prioritization of sub-watersheds are needed to allocate natural resources and efficiently manage watersheds. Characterization of health and spatial prioritization of sub-watersheds in data scarce regions helps better comprehend real watershed conditions and design and implement management strategies. Previous studies on the assessment of health and prioritization of sub-watersheds in ungauged regions have not considered environmental factors and their inter-relationship.

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Throughout the history of Romania, political decisions, socio-economic measures, and cultural (traditional) characters have affected the implementation of environment friendly techniques (EFTs) policies. In the context of this paper, EFTs can be defined as solutions for the use of land resources aiming the increasing of goods for meeting the changing human needs and with neutral or positive environmental impact. Changes in the political regime have always had a visible impact on the EFTs issue in Romania.

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It is of fundamental importance to model the relationship between geo-environmental factors and piping erosion because of the environmental degradation attributed to soil loss. Methods that identify areas prone to piping erosion at the regional scale are limited. The main objective of this research is to develop a novel modeling approach by using three machine learning algorithms-mixture discriminant analysis (MDA), flexible discriminant analysis (FDA), and support vector machine (SVM) in addition to an unmanned aerial vehicle (UAV) images to map susceptibility to piping erosion in the loess-covered hilly region of Golestan Province, Northeast Iran.

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