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This study was conducted to determine indices and components of economic sustainability assessment in the pastoral units of Sahand summer rangelands. The method was based on descriptive-analytical survey (experts and researchers) with questionnaires. Analysis of variance showed that the mean values of economic components are significantly different from each other and the efficiency component has the highest mean value (0.57). The analysis of rangeland pastoral units with the technique for order-preference by similarity to ideal solution (TOPSIS) indicated that from an economic sustainability standpoint, Garehgol (Ci = 0.519) and Badir Khan (Ci = 0.129), pastoral units ranked first and last, respectively. This study provides a clear understanding of existing resources and opportunities for policy makers that is crucial to approach economic sustainable development. Accordingly, this study can help better define sustainable development goals and monitor the progress of achieving them.

Sustainable development by forest managing need to identify forest ecosystem elements. Forest soil is the most important element of forest ecosystem that has key roles in forest managing. Therefore, studying of soil properties and evolution under different environmental conditions is necessary for sustainable management of forest ecosystems. Spatial variation of soil properties is significantly influenced by some environmental factors that slope position is one of them. The aim of this study was evaluating effects of slope position on forest soil change which was carried out in Arasbaran forest, NorthWest of Iran. Nine soil profiles were dug, described and sampled in three different parts of an altitudinal transect with same environmental conditions and different slope positions. Then soil samples were analysed physicaly and chemicaly and so classified based on Soil Taxonomy 2014. Also according to obtained results One-way analysis of variance was used to test relations of soil properties and slope positions. This results revealed significant effect of slope positions on thickness of the soil profile and solum, clay, organic carbon and total nitrogen percentages and cation exchange capacity at 5% level of confidence which lead to change of type, depth and sequence of soil horizons along altitudinal transect. Finally, it has found that slope position not only has important role in soil properties changes and soil evolution but also it can't be refused the various role and influence of same forest stand in different slope positions. Therefore various soils such as Inceptisols, Alfisols and Molisols were observed under different slope positions. Then it can be achieved that, because of special forest vegetation, soil evolution along altitudinal transect of forest ecosystems are differing from other ecosystems. Thus, for forest soil management program it is necessary to consider both of topography and vegetation effect over the area, even if one of them is constant.

Hackberry (Celtisaustralis L.) is native to the Mediterranean region and is distributed in Europe, Turkey, North Africa, and Iran. To the best of our knowledge, no study has been conducted on C.australis L. in the Arasbaran region, Iran. In the present study, total phenol (TP), flavonoid (TF), antioxidant capacity based on DPPH and FRAP assays and phenolic compounds and sugars profiles were investigated. According to the results, the range of antioxidant capacity based on DPPH and FRAP assays was 14.12–88.24% and 44.35–117.87 mg Fe2+/100 g, respectively. Also, the range of gallic acid, caffeic acid, chlorogenic acid, rutin, p-coumaric acid, rosmaric acid, cinnamic acid, and apigenin content was 2.59–26.32, 2.03–9.32, 0.94–11.35, 1.80–4.857, 2.32–9.52, 4.74–51.38, 0.18–2.10 and 0.27–1.37 mg/g, respectively. The results of factor analysis showed that the C12, C14, C15, C20, C8, C16, C3, and C20 genotypes are positively characterized by the first principal component (PCA1) that have a higher caffeic acid, chlorogenic acid, rutin, p-coumaric acid, rosmaric acid, quercetin, cinnamic acid, and apigenin phenolic compounds. Based on cluster analysis, the twenty genotypes were located in 2 main clusters. In general, the obtained results can be useful for breeding programs and the introduction of cultivars in Celtisaustralis L.

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Many countries have implemented policies to reduce the negative effects of deforestation. In Iran, the Zagros Forest Preservation Plan (ZFPP) began in 2003. This study evaluates the effectiveness of ZFPP on land cover changes in two periods, before (1993–2002) and after (2002–2017) implementation of the plan. Logistic regression (LR) analysis was used to examine the effectiveness of key socio-economic, environmental and demographic drivers associated with deforestation activities. The results showed that despite the implementation of ZFPP forest conversion to other land-use types increased during the second period compared to the first. Calculating the annual rate of deforestation showed that this rate increased from -0.4% to -0.5%. The results of LR showed that the occurrence of deforestation in different years was significantly related to distance from rivers, croplands, cities, roads, and slope such that areas with low slope and close to these features have a high probability of deforestation activities.

Questions Which clustering algorithms are most effective according to different cluster validity evaluators? Which distance or dissimilarity measure is most suitable for clustering algorithms? Location Hyrcanian forest, Iran (Asia), Virginia region forest, United States (North America), beech forests, Ukraine (Europe). Methods We tested 25 clustering algorithms with nine vegetation data sets comprised of three real data sets and six simulated data sets exhibiting different cluster separation values. The clustering algorithms included both hierarchical and non‐hierarchical partitioning. Five evaluators were employed on each cluster solution to evaluate different clustering algorithms. Algorithms were ranked from best to worst on each clustering evaluator for each data set. Results The comparison revealed that the OPTSIL initiated from a Flexible‐β (−0.25) solution achieved particularly good performance. We also found that Ward's method and Flexible‐β (−0.1) implementations were accurate. K‐means with Hellinger distance was superior to Partitioning Around Medoids (PAM) algorithms. Accordance between distance measures and clustering algorithms was also observed. Bray–Curtis dissimilarity combined with a range of clustering algorithms was successful in most cases. Bray–Curtis dissimilarity proved superior to other distance measures for heterogeneous data sets. Conclusions All in all, the results demonstrate that choosing the most suitable method before clustering is critical for achieving maximally interpretable clusters. The complexity of vegetation data sets makes this issue even more important. The choice of distance measure had more effect than the choice of clustering method on the quality of results. Our results illustrate that OPTSIL Flexible‐β (−0.1) and OPTPART could prove superior to alternative conventional clustering algorithms when internal evaluation criteria are used to optimize clustering.