Analyzing the Biological and Structural Diversity of Hyrcanian Forests Dominated by Taxus baccata L.

The Hyrcanian Forests, well-known for its World Heritage site in the South Caspian region of Northern Iran, are refugia for a special tree flora. Some areas in particular feature a concentration of large and numerous trees of Taxus baccata, a species that has attracted the interest of many researchers given its medicinal importance. The objective of this study was to analyze the biological and structural features of these unique ecosystems based on three large tree-mapped field plots using new methods. We developed a species abundance distribution and three species–area relations, and analyzed the small-scale structural patterns of each of the 15 tree species that occur in the plots. Species-specific details are presented for each of the three field plots, including the tree densities and average tree sizes, as well as the associated structural indices “species mingling”, “dominance”, and “size differentiation”. This includes non-linear relationships between tree density and neighborhood mingling, and between the average tree size and neighborhood dominance, and a linear relation between the neighborhood dominance and the mean neighborhood differentiation. Based on the findings, we recommend the use of these methods and indices for analyzing the structure of natural forests in other regions of the world

Water Resources Management Through Flood Spreading Project Suitability Mapping Using Frequency Ratio, k-nearest Neighbours, and Random Forest Algorithms

Lack of water resources is a common issue in many countries, especially in the Middle East. Flood spreading project (FSP) is an artificial recharge technique, which is generally suggested for arid and semi-arid areas with two major aims including (1) flood mitigation and (2) artificial recharge of groundwater. This study implemented three state-of-the-art popular models including frequency ratio (FR), k-nearest neighbours (KNN), and random forest (RF) for determining the suitability of land for FSP. At the first step, suitable areas for FSP were identified according to the national guidelines and the literature. The identified areas were then verified by multiple field surveys. To produce FSP land suitability maps, several FSP conditioning factors such as topographical (i.e. slope, plan curvature, and profile curvature), hydrogeological (i.e. transmissivity, aquifer thickness, and electrical conductivity), hydrological (i.e. rainfall, distance from rivers, river density, and permeability), lithology, and land use were considered as input to the models. For the FR modelling, classified layers of the aforementioned variables were used, while their continuous layers were implemented in the KNN and RF algorithms. At the last step, receiver operating characteristic (ROC) curve was used to assess the ability and accuracy of the applied algorithms. Based on the findings, the area under the curve of ROC for the RF, KNN, and FR models was 97.1, 94.6, and 89.2%, respectively. Furthermore, transmissivity, slope, aquifer thickness, distance from rivers, rainfall, and electrical conductivity were recognized as the most influencing factors in the modelling procedure. The findings of this study indicated that the application of RF, KNN, and FR can be suggested for identification of suitable areas for FSP establishment in other regions

Evaluation on the response of Bromus tomentellus Boiss and Festuca ovina L., to some environmental variables using the Generalized Additive Model(GAM) in the rangeland of Galandrood watershed in Mazandaran province, Iran

Investigation on the shape of the curve for responses of plant species to environmental gradients is one of the basic topics in the science of rangeland ecology. The objective of this study was investigation on the response of Bromus tomentellus and Festuca ovina species to some environmental variables using the generalized additive model (GAM) in the rangeland of Galandrood watershed in Mazandaran province. Towards this attempt, 153 quadrates of 1m2 along altitudinal gradient were taken. The sampling method was randomized-systematic. In the area sampled, presence of B. tomentellus and F.ovina, altitude, slope and aspect were recorded. Soil samples were taken from 0-20 cm in each quadrate. In each quadrate, soil properties including: pH, N, EC, organic carbon, the percentage of sand, silt and clay were measured. In order to study the shape of response curve in relation to the mentioned variables, GAM model was used with binomial distribution function. The data were analyzed by R ver.3.0.2 computer program. Results showed that altitude was the most important variable affecting the presence of B. tomentellus, While variables such as temperature and slope were the most important factors affecting the presence of F.ovina species. Clay and silt content in the soil were parameters that had significant negative impact on B. tomentellus and F.ovina species distribution. So, with an increase in clay and silt content of the soil, the possibility of the B. tomentellus and F.ovina presence were reduced

Non-linear height-diameter models for oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests, Iran

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R2), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small- and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance.status: publishe

The potential impact of future climate on the distribution of European yew (Taxus baccata L.) in the Hyrcanian Forest region (Iran)

International audienceThe Hyrcanian Forest region is rich in relict species, and endemic and endangered species. Although there are concerns about climate change, its influence on tree species in the Hyrcanian forests in the north of Iran is still unidentified.Taxus baccatais among the few conifer species found in the region, and the present study aims to evaluate the potential impact of climate change on the distribution ofT. baccata. For this purpose, we used ensemble species distribution modeling with ten algorithms and based on two geographic extents (global and regional) and climate data for different climate change scenarios. For the regional extent, we calibrated the models in Hyrcanian forests including the three provinces in the north of Iran. For the global extent, we calibrated the models on the whole range distribution ofT. baccata. In both cases, we applied the models to predict the distribution ofT. baccatain northern Iran under current, 2050, and 2070 climates. In regional extent modeling, precipitation of coldest quarter and in global extent modeling temperature seasonality emerged as the most important variables. Present environmental suitability estimates indicated that the suitable area forT. baccatain Hyrcanian forests is 5.89 x 10(3) km(2)(regional modeling) to 9.74 x 10(3) km(2)(global modeling). The modeling suggests that climate change under representative concentration pathways (RCP) 8.5 is likely to lead to strong suitability reductions in the region, with just between 0.63 x 10(3) km(2)(regional modeling) and 0.57 x 10(3) km(2)(global modeling) suitable area in 2070. Hence,T. baccatarisks losing most currently suitable areas in the Hyrcanian forests under climate change. The results of the present study suggest there should be focus on conservation of areas predicted to remain suitable through near-future climate change and provide an estimate of the availability of suitable areas for the regeneration ofT. baccataand its use in reforestation

B A S E Non-linear height-diameter models for oriental beech (Fagus orientalis Lipsky) in the Hyrcanian forests, Iran

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R 2 ), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small-and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance. Keywords. Forest trees, Fagus orientalis, simulation models, growth, Iran. Modèles non linéaires de diamètre de hauteur pour le hêtre oriental (Fagus orientalis Lipsky) dans les forêts Hyrcaniennes en Iran. La relation entre la hauteur des arbres et le diamètre est un élément important pour les modèles de croissance, de rendement, du budget de carbone et de volume du bois, et pour la description de la dynamique des peuplements. Six fonctions de croissance non linéaires (Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, fonctions logistiques et exponentielles modifiées) ont été ajustées aux données de diamètre de hauteur des arbres de hêtre oriental dans les forêts mélangées hyrcaniennes d'Iran. La performance prévue des modèles a été évaluée à l'aide du R² ajusté (adj R²), de l'erreur quadratique moyenne (RMSE), du critère d'information d'Akaike (AIC), de la différence moyenne (MD), de la différence absolue moyenne (MAD) et de l'erreur quadratique moyenne (MS). Les résultats ont montré que chacun de ces six modèles représente environ 75 % de la variation totale de hauteur, mais produit différentes estimations asymptotiques. La performance prévue a également été évaluée à l'aide des validations croisées et par séparation des données en classes de 5 cm de diamètre à hauteur de poitrine (DBH) afin de calculer le MD pour chaque classe. Les visualisations de MD pour toutes les classes DBH ont montré que les six fonctions de croissance, sauf la logistique modifiée, produisent des erreurs de prédiction moyennes similaires pour les arbres de tailles petites et moyennes. Cependant, pour les arbres de grande taille, l'erreur de prédiction moyenne est plus élevée. La fonction de logistique modifiée est la moins performante, en raison d'un large biais. Les modèles exponentiels et de Lundqvist/Korf ont été rejetés en raison, respectivement, de leur comportement biologique illogique et des estimations déraisonnables pour les coefficients asymptotiques. En envisageant tous les critères mentionnés ci-dessus, les fonctions Chapman-Richards, Weibull et Schnute fournissent les prédictions de hauteur les plus satisfaisantes, mais la fonction de Chapman-Richards pourrait être recommandée pour une analyse plus approfondie en raison de sa meilleure performance