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

Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling

Zelkova carpinifolia is a Tertiary relict tree distributed in Hyrcanian and Colchic forests. Most of its habitat has been destroyed in the last century. This study aimed to model potentially suitable habitat areas for Zelkova carpinifolia from the past to the future. The Last Glacial Maximum (LGM) and Future (2061-2080) models include 19 bioclimatic variables from the CCSM4 global circulation model Pearson correlation coefficient was used to assess collinearity between variables and ten variables were selected for distribution modelling. Habitat suitability was estimated using the Biodiversity Modelling (BIOMOD) ensemble modelling method by combining the results of ten algorithm models using the R package "biomod2". The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and true skills statistics (TSS) were calculated to evaluate the performance of the models. The contributions of the environmental variables were calculated separately for each algorithm model. According to the results obtained, the most effective bioclimatic variable in the distribution of the species is temperature seasonality (Bio4). The modelling results revealed that Zelkova carpinifolia survived in suitable refuge areas in western Asia during the LGM. These distribution areas have remained largely unchanged and even expanded. The future model results predict that the suitable habitats of the species will narrow in the Hyrcanian forests south of Caspian Sea and that more suitable conditions will be found around the Caucasus. Given the increasing destruction of these valuable plant species due to human activities and the expected negative impacts of climate change in the future, it is important to develop policies and strategies for the protection of Zelkova carpinifolia's habitat, the creation of nature reserves, and sustainability.

The potential range of west Asian apple species Malus orientalis Uglitzk. under climate change

The wild relatives of cultivated apples would be an ideal source of diversity for breeding new varieties, which could potentially grow in diverse habitats shaped by climate change. However, there is still a lack of knowledge about the potential distribution of these species. The aim of the presented work was the understand the impacts of climate change on the potential distribution and habitat fragmentation of Caucasian crab apple (Malus orientalis Uglitzk.) and the designation of areas of high interest according to climatic conditions. We used the MaxEnt models and Morphological-Spatial Analysis (MSPA) to evaluate the potential distribution, suitability changes, habitat fragmentation, and connectivity throughout the species range in Turkey, Armenia, Georgia, Russia, and Iran. The results revealed that the potentially suitable range of M. orientalis encompasses 858,877 km², 635,279 km² and 456,795 km² under the present, RCP4.5 and RCP8.5 scenario, respectively. The range fragmentation analysis demonstrated a notable shift in the edge/core ratio, which increased from 50.95% in the current scenario to even 67.70% in the future. The northern part of the range (Armenia, northern Georgia, southern Russia), as well as the central and western parts of Hyrcania will be a core of the species range with suitable habitats and a high connectivity between M. orientalis populations and could work as major refugia for the studied species. However, in the Zagros and central Turkey, the potential range will shrink due to the lack of suitable climatic conditions, and the edge/core ratio will grow. In the southern part of the range, a decline of M. orientalis habitats is expected due to changing climatic conditions. The future outlook suggests that the Hyrcanian forest and the Caucasus region could serve as important refuges for M. orientalis. This study helps to understand spatial changes in species' range in response to climate change and can help develop conservation strategies. This is all the more important given the species' potential use in future breeding programs aimed at enriching the gene pool of cultivated apple varieties.

Potential distribution of Biscogniauxia mediterranea and Obolarina persica causal agents of oak charcoal disease in Iran's Zagros forests

In Iran, native oak species are under threat from episodes of Charcoal Disease, a decline syndrome driven by abiotic stressors (e.g. drought, elevated temperature) and biotic components, Biscogniauxia mediterranea (De Not.) Kuntze and Obolarina persica (M. Mirabolfathy). The outbreak is still ongoing and the country's largest ever recorded. Still, the factors driving its' epidemiology in time and space are poorly known and such knowledge is urgently needed to develop strategies to counteract the adverse effects. In this study, we developed a generic framework based on experimental, machine-learning algorithms and spatial analyses for landscape-level prediction of oak charcoal disease outbreaks. Extensive field surveys were conducted during 2013-2015 in eight provinces (more than 50 unique counties) in the Zagros ecoregion. Pathogenic fungi were isolated and characterized through morphological and molecular approaches, and their pathogenicity was assessed under controlled water stress regimes in the greenhouse. Further, we evaluated a set of 29 bioclimatic, environmental, and host layers in modeling for disease incidence data using four well-known machine learning algorithms including the Generalized Linear Model, Gradient Boosting Model, Random Forest model (RF), and Multivariate Adaptive Regression Splines implemented in MaxEnt software. Model validation statistics [Area Under the Curve (AUC), True Skill Statistics (TSS)], and Kappa index were used to evaluate the accuracy of each model. Models with a TSS above 0.65 were used to prepare an ensemble model. The results showed that among the different climate variables, precipitation and temperature (Bio18, Bio7, Bio8, and bio9) in the case of O. persica and similarly, gsl (growing season length TREELIM, highlighting the warming climate and the endophytic/pathogenic nature of the fungus) and precipitation in case of B. mediterranea are the most important influencing variables in disease modeling, while near-surface wind speed (sfcwind) is the least important variant. The RF algorithm generates the most robust predictions (ROC of 0.95; TSS of 0.77 and 0.79 for MP and OP, respectively). Theoretical analysis shows that the ensemble model (ROC of 0.95 and 0.96; TSS = 0.79 and 0.81 for MP and OP, respectively), can efficiently be used in the prediction of the charcoal disease spatiotemporal distribution. The oak mortality varied ranging from 2 to 14%. Wood-boring beetles association with diseased trees was determined at 20%. Results showed that water deficiency is a crucial component of the oak decline phenomenon in Iran. The Northern Zagros forests (Ilam, Lorestan, and Kermanshah provinces) along with the southern Zagros forests (Fars and Kohgilouyeh va-Boyer Ahmad provinces) among others are the most endangered areas of potential future pandemics of charcoal disease. Our findings will significantly improve our understanding of the current situation of the disease to pave the way against pathogenic agents in Iran.

The influence of climate and population density on Buxus hyrcana potential distribution and habitat connectivity

Changes in environmental factors, human impact, and interactions between them accelerate the extinction of woody species. Therefore, conservation programs are needed to protect endangered taxa. However, the relationship between climate, habitat fragmentation, and anthropogenic activities and their consequences are still not well understood. In this work, we aimed to evaluate the impact of climate change and human population density on the Buxus hyrcana Pojark distribution range, as well as the phenomenon of habitat fragmentation. Based on species occurrence data throughout the Hyrcanian Forests (north of Iran), the MAXENT model was employed to estimate the potential distribution and suitability changes. Morphological-spatial analysis (MSPA) and CIRCUITSCAPE were used to assess habitat fragmentation and its connectivity. According to the main results obtained from future scenarios, the potential range will significantly decrease due to the lack of suitable climatic conditions. Meanwhile, B. hyrcana may not be able to shift in potentially suitable areas because of human influence and geographic barriers. Under RCP scenarios the extent of the core area would be reduced and the edge/core ratio significantly increased. Altogether, we found negative effects of the environmental change and the human population density on the continuity of habitats of B. hyrcana. The results of the presented work may improve our knowledge connected with in situ and ex situ protection strategies.

The influence of climate change on the suitable habitats of Allium species endemic to Iran

Identifying the consequences of global warming on the potential distribution of plant taxa with high species diversity or a high proportion of endemic species is one of the critical steps in conservation biology. Here, present and future spatial distribution patterns of 20 Allium endemic species were predicted in Iran. In this regard, the maximum entropy model (MaxEnt) and seven environmental factors were applied. In addition, optimistic (RCP2.6) and pessimistic (RCP8.5) scenarios of 2050 and 2080 were also considered to predict the future spatial distributions. The results showed that annual mean temperature (BIO1), temperature annual range (P5-P6) (BIO7), soil organic carbon content, annual precipitation (BIO12), and depth of soil were the most important environmental variables affecting the distributions of the studied taxa. In total, the model predictions under the future scenarios represented that the suitable habitats for all Allium species endemic to Zagros except for A. saralicum and A. esfahanicum are most probably increased. In contrast, the suitable habitats for all species in Azerbaijan Plateau, Kopet Dagh-Khorassan region, and Alborz except for A. derderianum are most likely decreased under the future climate conditions. The present study indicates that the habitats of Alborz, Azarbaijan, and Kopet Dagh-Khorassan will be probably very fragile and vulnerable to climate change and most species will respond strongly negatively under applied scenarios, while Zagros species occupy new habitats by expanding their distributions. Therefore, determining conservation strategies for the species in these regions seems to be very important and high priority for decision makers.

Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future

The predicts current and future flood risk in the Kalvan watershed of northwestern Markazi Province, Iran. To do this, 512 flood and non-flood locations were identified and mapped. Twenty flood-risk factors were selected to model flood risk using several machine learning techniques: conditional inference random forest (CIRF), the gradient boosting model (GBM), extreme gradient boosting (XGB) and their ensembles. To investigate the future (year 2050) effects of changing climates and changing land use on future flood risk, a general circulation model (GCM) with representative concentration pathways (RCPs) of the 2.6 and 8.5 scenarios by 2050 was tested for impacts on 8 precipitation variables. In addition, future land uses in 2050 was prepared using a CA-Markov model. The performances of the flood risk models were validated with Receiver Operating Characteristic-Area Under Curve (ROC-AUC) and other statistical analyses. The AUC value of the ROC curve indicates that the ensemble model had the highest predictive power (AUC = 0.83) and was followed by GBM (AUC = 0.80), XGB (AUC = 0.79), and CIRF (AUC = 0.78). The results of climate and land use changes on future flood-prone areas showed that the areas classified as having moderate to very high flood risk will increase by 2050. Due to the changes occurring with land uses and in climates, the area classified as moderate to very high risk increased in the predictions from all four models. The areal proportion classes of the risk zones in 2050 under the RCP 2.6 scenario using the ensemble model have changed of the following proportions from the current distribution Very Low = -12.04 %, Low = -8.56 %, Moderate = +1.56 %, High = +11.55 %, and Very High = +7.49 %. The RCP 8.5 scenario has caused the following changes from the present percentages: Very Low = -14.48 %, Low = -6.35 %, Moderate = +4.54 %, High = +10.61 %, and Very High = +5.67 %. The results of current and future flood risk mapping can aid planners and flood hazard managers in their efforts to mitigate impacts.