Search

Driving effectively soil research towards practice and towards policy solutions requires that the involved stakeholders, i.e researchers, practitioners and both national and regional policy makers interact and share information and views. However, these communities rather function in isolation. The European Joint Co-fund programme, EJP SOIL (Towards climate-smart and sustainable agricultural soil management) developed an innovative instrument to this end in each of its 24 participating countries.EJP SOIL National Hubs are committees of soil stakeholders (farmers, farmers advisors and farmers organisations, industry and agrobusiness, NGOs, local or national governance and policy implementing representatives, scientists), that were set either de-novo for the EJP SOIL or based on existing committees. Their mission is to (i) provide feedback to the EJP SOIL activities and outputs, (ii) voice national position and needs, (iii) contribute to and learn from the work done in research and iv) support in the dissemination of EJP SOIL outcomesThese entities appeared as precious assets for developing a science-policy-practice interface. As an example, the EJP SOIL National Hubs contributed to elaborating the roadmap of the programme and more recently were informed and provided feedback on the programme outputs on soil data harmonization and sharing and on soil monitoring in the perspective of the future European soil health law.We performed an analysis of their composition and functioning gives insights on how to effectively create and use these entities, which is forecasted by the EU Mission “A Soil Deal for Europe” for all land uses.

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. This study summarizes the key findings of stakeholder consultations conducted at the national level across 20 countries with the aim to identify important barriers and challenges currently affecting soil knowledge but also assess opportunities to overcome these obstacles. Our findings demonstrate that there is significant room for improvement in terms of knowledge production, dissemination and adoption. Among the most important barriers identified by consulted stakeholders are technical, political, social and economic obstacles, which strongly limit the development and full exploitation of the outcomes of soil research. The main soil challenge across consulted member states remains to improve soil organic matter and peat soil conservation while soil water storage capacity is a key challenge in Southern Europe. Findings from this study clearly suggest that going forward climate-smart sustainable soil management will benefit from (1) increases in research funding, (2) the maintenance and valorisation of long-term (field) experiments, (3) the creation of knowledge sharing networks and interlinked national and European infrastructures, and (4) the development of regionally-tailored soil management strategies. All the above-mentioned interventions can contribute to the creation of healthy, resilient and sustainable soil ecosystems across Europe.

In the northwest Ethiopian highlands, Fagita Lekoma district, farmers’ are practicing different land use systems such as crop land use, fodder land use, tree based land use and a combination these land use systems. Acacia decurrens based small-scale agroforestry (SSA) land use system is commonly practiced. However, the economic advantage of the A. decurrens based SSA land use system is not yet investigated. Therefore, this study was conducted to investigate the productivity and economic benefit of the A. decurrens based SSA land use system. Within the district, five investigation sites were selected where A. decurrens based SSA land use system (LUS) widely applied. The study was designed in five treatments with five replications and the test crop was Teff (Eragrostis teff, E. abyssinica) and the test agroforestry tree was A. decurrens. The treatments were; (1) Sole crop (Teff) LUS, (2) Sole fodder LUS, (3) Crop—A. decurrens intercropped LUS, (4) Fodder—A. decurrens intercropped LUS, and (5) Sole A. decurrens LUS. The result shows that the Teff—A. decurrens intercropped, fodder—A. decurrens intercropped, and sole A. decurrens LUSs, respectively, were found to provide better income for small-holder farmers. The Teff—A. decurrens intercropped LUS provided 1.3 and 1.2 times more income than the sole Teff and sole Acacia LUSs, respectively. The fodder—A. decurrens intercropped LUS provided 11 times more income than the sole fodder LUS. These are the main reasons motivating farmers to change the sole Teff and sole fodder LUSs to mixed/intercropped LUS. In general, A. decurrens intercropped based SSA land use system was found to provide better income for small-holder farmers. Hence, the mixed land use system is recommended to be practiced by farmers and could be up-scaled to other areas having similar agro-ecological situations.

This paper is the output of a project of the Knowledge-based Programme of the Wageningen University called ‘Nature-Based Solutions for Climate Resilient and Circular Food Systems’. The authors would like to acknowledge funding from the Wageningen University & Research ‘Food Secu- rity and Valuing Water programme’ (KB-35-007-002) and Circular and Climate Neutral’ programme’ (KB-34-007-010), which is supported by the Dutch Ministry of Agriculture, Nature and Food Security., Food systems—encompassing food production, transportation, processing and consump- tion, including food losses and waste—are currently not delivering what is expected or needed to ensure their full contribution to societal well-being and ecological sustainability. In this paper, we hypothesize that nature-based solutions (NBS; solutions that are inspired by, supported by, or copied from nature) can overcome system challenges related to the functioning of the biosphere, society, or economy (including governance arrangements), and support a transition to sustainable climate-resilient food systems. We develop a conceptual framework to assess NBS contributions to such transitions. Three types of NBS are evaluated: intrinsic NBS which make use of existing ecosystems; hybrid NBS which manage and adapt ecosystems; and inspired NBS which consist of newly constructed ecosystems. We show that inspired NBS in particular will increase opportunities to achieve sustainable development in food systems. NBS can facilitate the much-needed transi- tion to a different way of using our natural resources to reach the SDGs by 2030. We identify the knowledge gaps that impede the development of NBS to support a transition towards sustainable, climate-resilient food systems., Wageningen University & Research 'Food Security and Valuing Water programme' KB-35-007-002, Wageningen University & Research Circular and Climate Neutral' programme' - Dutch Ministry of Agriculture, Nature and Food Security KB-34-007-010

In a context of a rapidly changing livability of towns and countryside, climate change and biodiversity decrease, this paper introduces a landscape-based planning approach to regional spatial policy challenges allowing a regime shift towards a future land system resilient to external pressures. The concept of nature-based solutions and transition theory are combined in this approach, in which co-created normative future visions serve as boundary concepts. Rather than as an object in itself, the landscape is considered as a comprehensive principle, to which all spatial processes are inherently related. We illustrate this approach with three projects in the Netherlands in which landscape-based visions were used to guide the land transition, going beyond the traditional nature-based solutions. The projects studied show that a shared long-term future landscape vision is a powerful boundary concept and a crucial source of inspiration for a coherent design approach to solve today&rsquo, s spatial planning problems. Further, they show that cherishing abiotic differences in the landscape enhances sustainable and resilient landscapes, that co-creation in the social network is a prerequisite for shared solutions, and that a landscape-based approach enhances future-proof land-use transitions to adaptive, circular, and biodiverse landscapes.

Soil erosion is a serious ecological problem in Mediterranean areas. The IntErO model based on the erosion potential method (EPM) and the modified universal soil loss equation (MUSLE) have been used to assess soil erosion in several basins. This study aimed to assess and evaluate the effectiveness of these methods for evaluating sediment production and deposition rates in the Arbaa Ayacha basin, Morocco, in order to estimate sediment fluxes on a catchment scale. Our findings suggest that the basin is strongly exposed to erosion owing to geological formations, slope and land use, with average losses of about 28.4 t ha−1 year−1. Erosion processes were evaluated at the erosion production (Eocene marly formations) and sedimentation zones (Quaternary terraces). The results of these models may be useful to address soil and water management in this region and to assess the impact of a river dam that will be built in the basin.

Field studies that investigate sediment transport between debris‐flow‐producing headwaters and rivers are uncommon, particularly in forested settings, where debris flows are infrequent and opportunities for collecting data are limited. This study quantifies the volume and composition of sediment deposited in the arterial channel network of a 14‐km2 catchment (Washington Creek) that connects small, burned and debris‐flow‐producing headwaters (

Soil erosion, rapid geomorphological change and vegetation degradation are major threats to the human and natural environment. Unmanned Aerial Systems (UAS) can be used as tools to provide detailed and accurate estimations of landscape change. The effect of flight strategy on the accuracy of UAS image data products, typically a digital surface model (DSM) and orthophoto, is unknown. Herein different flying altitudes (126-235 m) and area coverage orientations (N-S and SW-NE) are assessed in a semi-arid and medium-relief area where terraced and abandoned agricultural fields are heavily damaged by piping and gully erosion. The assessment was with respect to cell size, vertical and horizontal accuracy, absolute difference of DSM, and registration of recognizable landscape features. The results show increasing cell size (5-9 cm) with increasing altitude, and differences between elevation values (10-20 cm) for different flight directions. Vertical accuracy ranged 4-7 cm but showed no clear relationship with flight strategy, whilst horizontal error was stable (2-4 cm) for the different orthophotos. In all data sets, geomorphological features such as piping channels, rills and gullies and vegetation patches could be labeled by a technician. Finally, the datasets have been released in a public repository.

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. Limited research is done so far to examine its impact in connection to the current pandemic. As of October 21, nearly 8.2 million acres of forest area were burned, with more than 25 casualties reported so far. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID-19) casualties. The spatial-temporal concentrations of particulate matter (PM2.5 and PM10) and Nitrogen Dioxide (NO2) were collected from August 1 to October 30 for 2020 (the fire year) and 2019 (the reference year). Both spatial (Multiscale Geographically Weighted Regression) and non-spatial (Negative Binomial Regression) analyses were performed to assess the adverse effects of fire emission on human health. The in-situ data-led measurements showed that the maximum increases in PM2.5, PM10, and NO2 concentrations (μg/m3) were clustered in the West Coastal fire-prone states during August 1 – October 30, 2020. The average concentration (μg/m3) of particulate matter (PM2.5 and PM10) and NO2 was increased in all the fire states severely affected by forest fires. The average PM2.5 concentrations (μg/m3) over the period were recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, increasing up to 24.9, 13.4, 25.0, and 17.0 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID-19 incidents. Such association has been demonstrated robust and stable by a total of 30 models developed for analyzing the spatial non-stationary and local association. More in-depth research is needed to better understand the complex relationship between forest fire emission and human health.

International audience; 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. Yet, the empirical evidence on the effects of NBS across various settings remains fragmented and their implementation faces a series of institutional barriers. In this paper, we adopt a community expert perspective drawing upon LAND4FLOOD Natural flood retention on private land network (https://www.land4flood.eu) in order to identify a set of barriers and their cascading and compound interactions relevant to individual NBS. The experts identified a comprehensive set of 17 barriers affecting the implementation of 12 groups of NBS in both urban and rural settings in five European regional environmental domains (i.e., Boreal, Atlantic, Continental, Alpine-Carpathian, and Mediterranean). Based on the results, we define avenues for further research, connecting hydrology and soil science, on the one hand, and land use planning, social geography and economics, on the other. Our suggestions ultimately call for a transdisciplinary turn in the research of NBS in FRM.

Forest land has a vital role in our planet ecosystem health. Forest areas are under natural and human pressure worldwide. Pests may have irreparable damages to vegetation cover; Tortrix viridana is one of the most important pests in the western forests of Iran and is mainly hosted by oak trees. In this study the performance of Sentinel-2 images to detect infected oaks by T. viridana in the Zagros forest habitat was considered. Vegetation indices (VIs) were extracted from affected and non-affected areas by T. viridana. The indices indices included normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), infrared percentage vegetation index (IPVI) and inverted red-edge chlorophyll index (IRECI) which were extracted from Sentinel-2 satellite images. The results of the present study show that VIs in affected and non-affected areas of the study site have significant differences at 99% of confidence level. In addition, the Spearman’s correlation coefficients between the VIs values in the affected and non-affected were 0.213, 0.213, 0.168 and 0.121 for IPVI, NDVI, IRECI and SAVI, respectively. This shows that Sentinel-2 images can be used to detect pests in forest areas.

The importance of soils to society has gained increasing recognition over the past decade, with the potential to contribute to most of the United Nations’ Sustainable Development Goals (SDGs). With unprecedented and growing demands for food, water and energy, there is an urgent need for a global effort to address the challenges of climate change and land degradation, whilst protecting soil as a natural resource. In this paper, we identify the contribution of soil science over the past decade to addressing gaps in our knowledge regarding major environmental challenges: climate change, food security, water security, urban development, and ecosystem functioning and biodiversity. Continuing to address knowledge gaps in soil science is essential for the achievement of the SDGs. However, with limited time and budget, it is also pertinent to identify effective methods of working that ensure the research carried out leads to real-world impact. Here, we suggest three strategies for the next decade of soil science, comprising a greater implementation of research into policy, interdisciplinary partnerships to evaluate function trade-offs and synergies between soils and other environmental domains, and integrating monitoring and modelling methods to ensure soil-based policies can withstand the uncertainties of the future. Highlights: We highlight the contributions of soil science to five major environmental challenges since 2010. Researchers have contributed to recommendation reports, but work is rarely translated into policy. Interdisciplinary work should assess trade-offs and synergies between soils and other domains. Integrating monitoring and modelling is key for robust and sustainable soils-based policymaking.

In the last years, the environmental impacts of cosmetics production have received growing interest from consumers, industries and the scientific community. Therefore, the selection and evaluation of more sustainable ingredients for cosmetic preparations need greater attention. The purpose of this work was to evaluate the environmental impact of snail secretion filtrate (LX360®), which could be used as an alternative cosmetic ingredient. The Carbon Footprint (CF) was used to quantify the kgCO2eq per liter of the LX360® produced in a rearing system farm that follows circularity economy and regenerative agriculture principles. The study computes the soil organic carbon (SOC) stock change due to the implementation of regenerative agricultural practices. The CF of the production system was up to 1.76 kg CO2eq L−1, where the extraction stage contributed most. Findings on SOC stock showed a significant increase compared to the previous land-use. The net sequestered CO2 into the soil amounts to 2.07 kg CO2eq L−1; therefore, the production of LX360® showed a positive carbon balance (0.31 kg CO2eq L−1). The application of regenerative agriculture in snail rearing systems positively affects SOC sequestration, and it should be considered as a best management practice for the restoration of degraded land.

Dam removal can generate geomorphic disturbances, including channel bed and bank erosion and associated abrupt/pulsed release and downstream transfer of reservoir sediment, but the type and rate of geomorphic response often are hard to predict. The situation gets even more complex in systems which have been impacted by multiple dams and a long and complex engineering history. In previous studies one-dimensional (1-D) models were used to predict aspects of post-removal channel change. However, these models do not consider two-dimensional (2-D) effects of dam removal such as bank erosion processes and lateral migration. In the current study the impacts of multiple dams and their removal on channel evolution and sediment delivery were modeled by using a 2-D landscape evolution model (CAESAR-Lisflood) focusing on the following aspects: patterns, rates, and processes of geomorphic change and associated sediment delivery on annual to decadal timescales. The current modeling study revealed that geomorphic response to dam removal (i.e., channel evolution and associated rates of sediment delivery) in multiple dam settings is variable and complex in space and time. Complexity in geomorphic system response is related to differences in dam size, the proximity of upstream dams, related buffering effects and associated rates of upstream sediment supply, and emerging feedback processes as well as to the presence of channel stabilization measures. Modeled types and rates of geomorphic adjustment, using the 2-D landscape evolution model CAESAR-Lisflood, are similar to those reported in previous studies. Moreover, the use of a 2-D method showed some advantages compared to 1-D models, generating spatially varying patterns of erosion and deposition before and after dam removal that provide morphologies that are more readily comparable to field data as well as features like the lateral re-working of past reservoir deposits which further enables the maintenance of sediment delivery downstream.

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., mining operations, upstream areas without any exploration, and the downstream area of the mining activities, (b) calculation of the zones’ VC, (c) investigation of transformation trends in each pixel of VC time series using the Mann–Kendall trend test, (d) determination of the pixels with significant VC reduction and the significant starting points of the trend using the sequential Mann–Kendall test, (e) assessment of the correlation between the zones with significantly reduced VC, and (f) a correlation test between average monthly and annual climate parameters and VC. Our results indicate that although 51 ha of VC has been demolished around the mining activities areas (i.e., zone 1), an overall upward trend in vegetation with no chemical leakage is observed into the downstream area of the basin (i.e., zone 3). This upward trend can be mostly attributed to the increasing precipitation and decreasing temperature in the study period. The fact that the area downstream of the mine shows that the heap leaching method for gold mining in Andaryan mine is currently not damaging the vegetation, this likely means that there is no leakage to the surrounding environment from the mine. Our results further show that using NDVI in a pixel-based scale and statistical methods has a high potential to quantify the effects of human activities on surface biophysical characteristics.

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. While highlighting the great potential of soils to contribute to sustainable development, it is recognized that poorly managed, degraded or polluted soils may contribute negatively to both NCP and SDGs. The positive contribution, however, cannot be taken for granted, and soils must be managed carefully to keep them healthy and capable of playing this vital role. A priority for soil management must include: (i) for healthy soils in natural ecosystems, protect them from conversion and degradation; (ii) for managed soils, manage in a way to protect and enhance soil biodiversity, health and sustainability and to prevent degradation; and (iii) for degraded soils, restore to full soil health. We have enough knowledge now to move forward with the implementation of best management practices to maintain and improve soil health. This analysis shows that this is not just desirable, it is essential if we are to meet the SDG targets by 2030 and achieve sustainable development more broadly in the decades to come. This article is part of the theme issue ‘The role of soils in delivering Nature's Contributions to People’.

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. Soil health reflects the capacity of a soil to provide ecosystem services at a specific location, taking into account local climate and soil conditions. Soil is also an important component of a healthy and sustainable landscape, and they are connected by the water that flows through the soil and the transported sediments. Soils are linked to water in two ways: through plant-available water in the soil (green water) and through water in surface bodies or available as groundwater (blue water). In addition, water connects the soil scale and the landscape scale by flowing through both. Nature-based solutions at both soil health and landscape-scale can help achieve sustainable future development but need to be embedded in good governance, social acceptance and economic viability. This article is part of the theme issue ‘The role of soils in delivering Nature's Contributions to People’.

The main goal of this study was to optimize an adaptive neuro-fuzzy inference system (ANFIS) using three meta-heuristic optimization algorithms—genetic algorithm (GA), biogeography-based optimization (BBO) and simulated annealing (SA)—to prepare groundwater potential maps. The methodology was applied to the Booshehr plain, Iran. The results of optimized models were compared with ANFIS individually and three bivariate models: frequency ratio (FR), evidential belief function (EBF), and the entropy model. First, 339 wells with groundwater yield higher than 11 m3/h were selected and randomly divided into two groups. In all, 238 wells (70%) were used for training the models and 101 wells (30%) were used for testing and validating the models. Fifteen conditioning factors were selected as input parameters for the modeling. The accuracy of the groundwater potential maps for the study area was determined using root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and standard deviation of error (SD), as well as the area under the receiver operating characteristic (ROC) curve (AUC). Overall, the results demonstrated that ANFIS-GA had the highest prediction capability (AUC = 0.915) for groundwater potential mapping followed by ANFIS-BBO (0.903), entropy (0.862), FR (0.86), ANFIS-SA (0.83), ANFIS (0.82) and EBF (0.80). According to the entropy model, land-use, soil order and rainfall factors had the highest impact on groundwater potential in the study area. The results of this research show that the ANFIS models combined with meta-heuristic optimization algorithms can be a useful decision-making tool for assessment and management of groundwater resources.

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). These mangrove ecosystems are crucial for providing valuable supporting, regulatory, provisioning, and cultural ecosystem services. We have adopted supervised machine learning algorithms for classifying the region into different ecosystem units. Among the used machine learning models, Support Vector Machine (SVM) and Random Forest (RF) algorithms performed the most accurate and produced the best classification estimates with maximum kappa and an overall accuracy value. The maximum ESV (derived from both adjusted and non-adjusted units, million US$ year −1 ) is produced by mangrove forest, followed by the coastal estuary, cropland, inland wetland, mixed vegetation, and finally urban land. Out of all the ESs, the waste treatment (WT) service is the dominant ecosystem service of SBR. Additionally, the mangrove ecosystem was found to be the most sensitive to land use and land cover changes. The synergy and trade-offs between the ESs are closely associated with the spatial extent. Therefore, accurate estimates of ES valuation and mapping can be a robust tool for assessing the effects of poor decision making and overexploitation of natural resources on ESs.

Understanding landslide characteristics such as their locations, dimensions, and spatial distribution is of highly importance in landslide modeling and prediction. The main objective of this study was to assess the effect of different sample sizes and raster resolutions in landslide susceptibility modeling and prediction accuracy of shallow landslides. In this regard, the Bijar region of the Kurdistan province (Iran) was selected as a case study. Accordingly, a total of 20 landslide conditioning factors were considered with six different raster resolutions (10 m, 15 m, 20 m, 30 m, 50 m, and 100 m) and four different sample sizes (60/40%, 70/30%, 80/20%, and 90/10%) were investigated. The merit of each conditioning factors was assessed using the Information Gain Ratio (IGR) technique, whereas Alternating decision tree (ADTree), which has been rarely explored for landslide modeling, was used for building models. Performance of the models was assessed using the area under the ROC curve (AUROC), sensitivity, specificity, accuracy, kappa and RMSE criteria. The results show that with increasing the number of training pixels in the modeling process, the accuracy is increased. Findings also indicate that for the sample sizes of 60/40% (AUROC = 0.800) and 70/30% (AUROC = 0.899), the highest prediction accuracy is derived with the raster resolution of 10 m. With the raster resolution of 20 m, the highest prediction accuracy for the sample size of 80/20% (AUROC = 0.871) and 90/10% (AUROC = 0.864). These outcomes provide a guideline for future research enabling researchers to select an optimal data resolution for landslide hazard modeling.

Climate-smart agriculture (CSA) conceptually has the potential to contribute to the sustainable development goals of achieving zero hunger, reducing land degradation, eliminating poverty, tackling climate change, and promoting gender equality. The scaling-up needed to achieve goals of CSA represents a challenge, as it entails understanding synergies between often opposing socioeconomic and environmental priorities and trade-offs over temporal and spatial scales. In this paper, we tested new approaches to support scaling-up of sustainable food production through investigating the contribution of systems thinking as a conceptual approach and complex adaptive system (CAS) attributes as a framework for analysis of CSA. This was done through examining (i) to what extent CSA represents a CAS and (ii) what contribution systems thinking and CAS attributes can make to understanding and scaling-up sustainable food production systems through CSA. The CSA situation was conceptualized through systems thinking sessions with women farmers in the climate-smart village (CSV) of Doggoh-Jirapa, northern Ghana, and was guided by the Distinctions, Systems, Relationships and Perspectives (DSRP) framework. Systems thinking, and CAS attributes provide system-wide understanding of elements, dynamics and trade-offs over temporal and spatial scale in selected agri-food systems. As such it could aid horizontal and vertical scaling-up by informing policy developoment and selection of a context-specific portfolio of technologies and practices at landscape and farm levels to achieve synergies between goals. In this study, systems thinking enabled women farmers in the CSV to identify income-generating and tree planting activities, with desirable simultaneous system-wide impact. The paper calls for further testing of tools, approaches, and methods that enable dynamic systems thinking to inform scaling-up efforts, while embracing the transdisciplinary nature and complexity of CSA as a constituent of the food production system.

[EN] In many Mediterranean areas, citrus orchards exhibit high soil loss rates because of the expansion of drip irrigation that allows cultivation on sloping terrain and the widespread use of glyphosate. To mitigate these non-sustainable soil losses, straw mulch could be applied as an efficient solution but this has been poorly studied. Therefore, the main goal of this paper was to assess the use of straw mulch as a tool to reduce soil losses in clementine plantations, which can be considered representative of a typical Mediterranean citrus orchard. A total of 40 rainfall simulation experiments were carried out on 20 pairs of neighbouring bare and mulched plots. Each experiment involved applying 38.8 mm of rain at a constant rate over 1 h to a circular plot of 0.28 m(2) circular plots. The results showed that a cover of 50% of straw (60 g m(-2)) was able to delay the time to ponding from 32 to 52 s and the time to runoff initiation from 57 to 129 s. Also, the mulching reduced the runoff coefficient from 65.6 to 50.5%. The effect on sediment transport was even more pronounced, as the straw mulch reduced the sediment concentration from 16.7 g l(-1) to 3.6 g l(-1) and the soil erosion rates from 439 g to 73 g. Our results indicated that mulching can be used as a useful management practice to control soil erosion rates due to the immediate effect on high soil detachment rate and runoff initiation reduction in conventional clementine orchards on sloping land, by slowing down runoff initiation and by reducing runoff generation and, especially, sediment losses. We indirectly concluded that straw mulch is also a sustainable solution in glyphosate-treated citrus plantations., This paper is part of the results of research projects GL2008-02879/BTE, LEDDRA 243857 and RECARE-FP7 (ENV.2013.6.2-4).

© 2018 Elsevier Ltd 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. In this regard, fuzzy logic theory can be employed to improve the assessment of watershed health. The present study considered a combination of climate vulnerability (Climate Water Balance), relative erosion rate of surficial rocks, slope weighted K-factor, topographic indices, thirteen morphometric characteristics (linear, areal, and relief aspects), and potential non-point source pollution to assess watershed health, using a new framework which considers the complex linkage between human activities and natural resources. The new framework, focusing on watershed health score (WHS), was employed for the spatial prioritization of 31 sub-watersheds in the Khoy watershed, West Azerbaijan Province, Iran. In this framework, an analytical network process (ANP) and fuzzy theory were used to investigate the inter-relationships between the above mentioned geo-environmental factors and to classify and rank the health of each sub-watershed in four classes. Results demonstrated that only one sub-watershed (C15) fell into the class that was defined as ‘a potentially critical zone’. This article provides a new framework and practical recommendations for watershed management agencies with a high level of assurance when there is a lack of reliable hydrometric gauge data.

Land-management options for greenhouse gas removal (GGR) include afforestation or reforestation (AR), wetland restoration, soil carbon sequestration (SCS), biochar, terrestrial enhanced weathering (TEW), and bioenergy with carbon capture and storage (BECCS). We assess the opportunities and risks associated with these options through the lens of their potential impacts on ecosystem services (Nature's Contributions to People; NCPs) and the United Nations Sustainable Development Goals (SDGs). We find that all land-based GGR options contribute positively to at least some NCPs and SDGs. Wetland restoration and SCS almost exclusively deliver positive impacts. A few GGR options, such as afforestation, BECCS, and biochar potentially impact negatively some NCPs and SDGs, particularly when implemented at scale, largely through competition for land. For those that present risks or are least understood, more research is required, and demonstration projects need to proceed with caution. For options that present low risks and provide cobenefits, implementation can proceed more rapidly following no-regrets principles.

Soil respiration is a biological process in microbes that convert organic carbon to atmospheric CO2. This process is considered to be one of the largest global carbon fluxes and is affected by different physicochemical and biological properties of soil, land use, vegetation types and climate patterns. Soil respiration recently received much attention, and it could be measured in two states basal respiration (BR) and substrate induced respiration (SIR) which together gives a good representation of the general soil microbial activity. The aim of this study was to estimate the BR and SIR of 150 data points obtained from soil samples collected from the surface to 20 cm of depth under different land use categories using the Artificial Neural Network (ANN) and Linear Regression Methodology (LRM). This study is bringing data from an arid area, and there is little information on this issue. Soil samples were chosen from three provinces of Iran, with humid subtropical and semi-arid climate patterns. In each soil sample a variety of characteristics were measured: soil texture, pH, electrical conductivity (EC), calcium carbonate equivalent (CCE), organic carbon (OC), OC fractionation data e.g. light fraction OC (LOC), heavy fraction OC (HOC), cold water extractable OC (COC) and warm water extractable OC (WOC), population of fungi, bacteria, actinomycete, BR and SIR. Our goal was to use the most efficient ANN-model to predict soil respiration with simple soil data and annual precipitation (AP) and mean annual temperature (MAT) and compare it with LRM. Our results indicated that for an ANN model containing all the measured soil parameters (14 variables), the R2 and RMSE values for BR prediction were 0.64 and 0.05 while these statistical indicators for SIR obtained 0.58 and 0.15, respectively; whereas the addition of AP and MAT data to this model (16 variables) caused a decrease in statistical indicators. When the R2 and RMSE values of the BR-ANN and SIR-ANN predicted using an ANN model with only 7 variables (including OC, pH, EC, CCE and soil texture) they were estimated to be 0.66, 0.043 and 0.52, 0.16, respectively. Overall, LRM in comparison to ANN had a lower R2. Therefore, the results show that ANN modeling is a reliable method for predicting soil respiration, even when based on easy to measure data. Our results revealed that highest and lowest BR and SIR were recorded in rice paddy soils and saline lands, respectively. In total, soil respiration (BR: 0.09 vs 0.06 and SIR: 0.46 vs 0.32 mg CO2 g−1 day−1) was higher in agricultural land compared to natural covered land.

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. EFTs has gone through several major phases. The political impact on EFTs implementation mainly affected sustainable land management (SLM) and to a small extent, at the end of the communist era and partly during the capitalist period, climate change mitigation. Throughout history, the political factor has dominated and influenced the capacity of the EFTs implementation process in responding to socio-economic stimuli. In addition, quality of life, rural-urban and urban-rural migrations, poverty, education level, and climate change adaptation have had impacts on the status of EFTs according to governance and political reflections. The agrarian reforms from the last two centuries, based on socio-economic demands, have strongly influenced the capacity to implement EFTs both positively and negatively. However, the cultural factor was least affected by political and socio-economic changes as a stability factor in ensuring continued implementation of the EFTs. Currently, there is a strong need to reconsider EFTs as sustainability tools for Romanian agriculture that can cope with climate change and sustainable land management (SLM) demands. This paper presents a brief history of EFTs in Romania and their benefits in achieving SLM equilibrium, describing the impacts of political decisions, socio-economic measures, and cultural features on implementing ETFs policies.

In the past two decades, connectivity has emerged as a relevant conceptual framework for understanding the transfer of water and sediment through landscapes. In geomorphology, the concept has had particular success in the fields of fluvial geomorphology and soil erosion to better explain rates and patterns of geomorphic change in catchment systems. Sediment (dis)connectivity in geomorphic systems is generally governed by the spatial arrangement of sediment sources, transfer pathways and sinks (i.e. the structural component) as well as the interactions between landscape compartments and the frequency-magnitude relationships that dictate the relative effectiveness of geomorphic processes (i.e. the structural component; Poeppl et al., 2020). This presentation will provide a short general overview on existing concepts of connectivity in geomorphology, further highlighting and discussing recent developments in geomorphological connectivity research.ReferencesRonald E. Poeppl, Kirstie A. Fryirs, Jon Tunnicliffe, Gary J. Brierley (2020). Managing sediment (dis)connectivity in fluvial systems, Science of The Total Environment, Volume 736, 139627

Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment.