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The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry.

Sustainable nitrogen (N) management in agriculture is one of the most important issues affecting the environmental performance of modern agriculture. It is actually well perceived that coordinated efforts and holistic approaches are required to regulate N use by farmers. The purpose of this study was to provide an initial examination of stakeholders’ views in Japan regarding N use in agriculture and challenges to increase its sustainability. The analysis was based on a questionnaire study of five types of stakeholders (farmers, advisors, researchers, suppliers, policy makers). By means of multivariate analysis techniques it was revealed that consensus was lacking either in the acknowledgment of the causes and effects of unsustainable N management or in the challenges that need to be addressed. N losses from farms and the effects of N use were perceived but not conceived equally by all stakeholders. Organic farming and mandatory measures were the most controversial challenges, while those involving awareness, training and advisory were the most popular. This study cannot provide safe conclusions that can be generalized in the Japanese context, but it indicates domains where further research is required and orientations for future policy design towards more sustainable N use.

This study deals with the flood-hazard assessment and mapping in the catchment of Megalo Rema (East Attica, Greece). Flood-hazard zones were identified utilizing Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information System (GIS). Five factors were considered as the most influential parameters for the water course when high storm-water runoff exceeds drainage system capacity and were taken into account. These factors include slope, elevation, distance from stream channels, geological formations in terms of their hydro-lithological behavior and land cover. To obtain the final weights for each factor, rules of the Analytic Hierarchy Process (AHP) were applied. The final flood-hazard assessment and mapping of the study area were produced through Weighted Linear Combination (WLC) procedures. The final map showed that approximately 26.3 km2, which corresponds to 22.7% of the total area of the catchment, belongs to the high flood risk zone, while approximately 25 km2, corresponding to ~15% of the catchment, is of very high flood risk. The highly and very highly prone to flooding areas are located mostly at the southern and western parts of the catchment. Furthermore, the areas on both sides of the channel along the lower reaches of the main stream are of high and very high risk. The highly and very highly prone to flooding areas are relatively low-lying, gently sloping and extensively urbanized, and host the densely populated settlements of Rafina-Pikermi, Penteli, Pallini, Peania, Spata, Glika Nera, Gerakas and Anthousa. The accuracy of the flood-hazard map was verified by correlating flood events of the last 30 years, the Hydrologic Engineering Center’s River Analysis System (HEC–RAS) simulation and quantitative geomorphological analysis with the flood-hazard level. The results of our approach provide decision makers with important information for land-use planning at a regional scale, determining safe and unsafe areas for urban development.

The seeds of wild Crambe species have potential to be used as a source of industrial oil and animal feed. In this study, 48 genotypes of three Crambe species collected from the flora of Turkey were grown under field conditions in Ankara/Turkey in 2014–2016. The seed protein ratio, plant height, number of branches per plant, number of seeds per plant, seed yield per plant, thousand seed weight and hulless/hulled seed ratio (H/H) were determined. The highest protein ratio was determined as 26.02% in the t18 accession of Crambe tataria species. Variations in the characteristics were analyzed using principal component analysis. In the factor analysis of Crambe maritima, Crambe orientalis, Crambe tataria and the mean of these three species, the first two principal components accounted for 100%, 58.06%, 59.93% and 100% of the total variations, respectively. There were positive correlations between the plant height and number of seeds per plant, seed yield per plant for C. orientalis, and number of branches per plant for C. tataria. Although seed yield per plant was high in C. tataria and C. orientalis, they are not suitable for conventional agriculture due to shell thickness, inhomogeneous plant emergence and shooting. Conventional cultivation of wild Crambe species can be made possible by eliminating these negative features with breeding and agronomic studies.

The land transformation process in the last decades produced the urbanization growth in flat and coastal areas all over the world. The combination of natural phenomena and human pressure is likely one of the main factors that enhance coastal dynamics. These factors lead to an increase in coastal risk (considered as the product of hazard, exposure, and vulnerability) also in view of future climate change scenarios. Although each of these factors has been intensively studied separately, a comprehensive analysis of the mutual relationship of these elements is an open task. Therefore, this work aims to assess the possible mutual interaction of land transformation and coastal management zones, studying the possible impact on local coastal communities. The idea is to merge the techniques coming from urban planning with data and methodology coming from the coastal engineering within the frame of a holistic approach. The main idea is to relate urban and land changes to coastal management. Then, the study aims to identify if stakeholders’ pressure motivated the deployment of rigid structures instead of shoreline variations related to energetic and sedimentary balances. The influence of coastal protection (described by an indicator taking into account the linear density of the rigid protection extension alongshore) measures have been considered. Finally, the economical performances in the period just after the land transformation have been studied by means of a dimensionless index based on the concept of the local unit. The method has been applied to the case study of the Abruzzo Region. Results reveal a large urbanization growth and a generalized over-protection of the coast with a resulting spatial alternation of shoreline retreat and advance. On the other hand, the analysis of the local economy reveals that the presence of tourism activities does not necessarily lead to an increase in the local economy. Indeed, the most important improvement in local economies in the region can be associated with coastal stretches characterized by a high environmental value.

The rapid increase in urbanization has brought about a great deal of ecological problems, and thus the systematic protection of the environment is vital. Ecological security patterns are important for maintaining regional ecological stability and sustainable urban development. Human disturbance is a key factor affecting the stability and sustainable development of ecosystems. This paper constructs an ecological security pattern and evaluates the degree of human disturbance in Fuzhou City. Through a comprehensive analysis of both of these factors, the ecological priority restoration areas in Fuzhou were identified. The study shows that (1) there are 40 ecological source areas in Fuzhou, with a total area of 4556.48 km2; 83 ecological corridors, with a total distance of 179.33 km; and 30 ecological nodes. (2) The human disturbance degree score in the study area is between 0 and 0.8. The degree of human disturbance forms two larger major cores in Cangshan District, Gulou District, and Fuqing City. (3) The scores for the degree of human disturbance with ecological sources range from 0 to 0.42. The high-priority areas in the study area are distributed at the edges of ecological sources and form two high-scoring aggregation areas in Fuqing City and Jinan District. These corridors have a high degree of human disturbance with scores between 0 and 0.56. The I and II priority areas are mostly found in longer corridors in Fuqing City and Cangshan District near coastal or urban centers, and the III priority areas are mainly distributed in ecological corridors near the inland. The human disturbance degree scores of the nodes range from 0.01 to 0.27, and the nodes with higher grades were mainly distributed in the northeast, southeast, northwest and southwest of the study area.

With the emergence of machine learning methods during the past decade, alternatives to conventional geostatistical methods for soil mapping are becoming increasingly more sophisticated. To provide a complete overview of their performance, this study performed cost–benefit analysis of four soil mapping methods based on five criteria: accuracy, processing time, robustness, scalability and applicability. The evaluated methods were ordinary kriging (OK), regression kriging (RK), random forest (RF) and ensemble machine learning (EML) for the prediction of total soil carbon and nitrogen. The results of these mechanisms were objectively standardized using the linear scaling method, and their relative importance was quantified using the analytic hierarchy process (AHP). EML resulted in the highest cost–benefit score of the tested methods, with maximum values of accuracy, robustness and scalability, achieving a 55.6% higher score than the second-ranked RF method. The two geostatistical methods ranked last in the cost–benefit analysis. Despite that, OK could retain its place as the most frequent method for soil mapping in recent studies due to its widespread, user-friendly implementation in GIS software and its univariate character. Further improvement of machine learning methods with regards to computational efficiency could additionally improve their cost–benefit advantage and establish them as the universal standard for soil mapping.

Although climate-smart agriculture can simultaneously decline greenhouse gas emissions, increase the adaptive capacity of farmers and improve food security under climate change, constraints and drivers of scaling up are not entirely addressed in developing countries. This qualitative case study was conducted on both strawberry growers and agricultural experts to explore the perceived causes, evidence and impacts of climate change, adaptation strategies used by farmers, and constraints and drivers of climate-smart agriculture development on the strawberry farms in Kurdistan province, Western Iran. Findings indicated that the causes of climate change could be divided into anthropogenic and natural forces. Decreased precipitation, increased temperature, dust storms, greenhouse gases, forest fires, spring frosts, severe hail, floods and droughts comprised the most notable climate change evidence in the region. Both groups confirmed the impacts of climate change on the reduction in strawberry yield, increasing the perishability of the fruits, poverty, migration and other social problems. Adaptation strategies used by farmers are classified into technical–agricultural, water conservation, farm smartening, and institutional adaptation practices. However, poverty, the shortage of strawberry-processing industries, insufficient financial support, the presence of intermediaries and brokers, traditional cultivation, difficulties in shipping strawberry crops to the market, the lack of storage facilities and equipment and the export terminal along with the mistrust of strawberry growers in the agricultural organization hinder climate-smart agriculture development in the study area. Finally, several drivers were proposed, which were considered the basis for providing practical suggestions for planning and policy making for climate-smart agriculture development in strawberry farms.