RESUMO
This study explores how climate variables influenced the evolution and diversification of Neurergus newts within the Irano-Anatolian biodiversity hotspot. We use a dated phylogenetic tree and climatic niche models to analyze their evolutionary history and ecological preferences. Using genetic data from nuclear (KIAA) and mitochondrial (16s and 12s) genes, we estimate divergence times and identify four major Neurergus clades. The initial speciation event occurred approximately 11.3 million years ago, coinciding with the uplift of the Zagros and Anatolian mountains. This geological transformation isolated newt populations, likely triggering the first speciation event. By integrating potential geographic distribution with climate variables, we reconstruct ancestral niche occupancy profiles. This highlights the critical roles of temperature and precipitation in shaping Neurergus habitat preferences and distribution. We observe both phylogenetic niche conservatism and divergence, with niche divergence playing a dominant role in diversification. This research emphasizes the complex interplay of geography, climate, and ecology in speciation and the vulnerability of isolated mountain newt populations to environmental changes.
RESUMO
This study examines the impact of fire incidents on wildlife and habitats in the western oak forests of Iran (Zagros region). These forests are globally recognized for their exceptional biodiversity but are frequently threatened by wildfires. To achieve this, the study uses the space-time scan statistics permutation (STSSP) model to identify areas with a higher frequency of fires. The study also analyzes the effects of fires on the Zagros forests from 2000 to 2021 using remote-sensing MODIS data. Also, to understand the elements at risk of fire, burned areas were assessed based on the richness of vertebrate species, determined by the distribution of 88 vertebrate species. The results show that the annual fire rate in the Zagros forests is 76.2 (fire occurrences per year), calculated using the Poisson distribution. Findings show the highest fire rates are found in the northwest and a part of the south of the Zagros. The northwest of the Zagros also has the largest number of single fires and clusters, indicating a wide spatial distribution of fire in these regions. On the other side, it was unexpectedly found that these regions have the richest number of species and higher habitat value. The results demonstrate a significant correlation between the value of the habitat and the extent of burned areas (p < 0.05). The study also reveals that the greatest impact of fires is on small vertebrates. The overlap of frequent fire spots with the richest regions of Zagros oak forests in terms of vertebrate diversity emphasizes the need for strategic forest risk reduction planning, especially in these priority zones.
Assuntos
Biodiversidade , Conservação dos Recursos Naturais , Ecossistema , Florestas , Quercus , Vertebrados , Incêndios Florestais , Irã (Geográfico) , Animais , Conservação dos Recursos Naturais/métodos , Incêndios/prevenção & controleRESUMO
Oligochaetes are the most abundant benthic taxa in aquatic ecosystems that play an important role in food webs. The present study aims to assess the diversity and origin of Eiseniella tetraedra as a non-native species in the Lar National Park of Iran and also its response to current and future climate change. We obtained the specimen from rivers and sequenced the mitochondrial gene Cytochrome Oxidase subunit I (COI) and combined them with 117 sequences from the Jajroud and Karaj rivers in Iran and native regions from GenBank (NCBI). We also ran Species Distribution Modelings (SDMs) using an ensemble model approach that was estimated according to two shared socio-economic pathways (SSPs): 126 and 585 of the MRI-ESM2 based on CMIP6. According to the results, all the samples examined in the current study originated from Spanish rivers, and no unique haplotype was found in the Lar National Park. Moreover, the results also show high haplotype diversity that can positively affect the success of this non-native species in different freshwater. Also, the results of SDMs depict that climate change would remarkably affect the distribution of E. tetraedra and it verifies the invasion power of E. tetraedra in Iran's freshwater ecosystems over time.
Assuntos
Mudança Climática , Oligoquetos , Animais , Ecossistema , Irã (Geográfico) , Água DoceRESUMO
Climate change is one of the major challenges to the current conservation of biodiversity. Here, by using the brown bear, Ursus arctos, in the southernmost limit of its global distribution as a model species, we assessed the impact of climate change on the species distribution in western Iran. The mountainous forests of Iran are inhabited by small and isolated populations of brown bears that are prone to extinction in the near future. We modeled the potential impact of climate change on brown bear distribution and habitat connectivity by the years 2050 and 2070 under four representative concentration pathways (RCPs) of two general circulation models (GCMs): BCC-CSM1-1 and MRI-CGCM3. Our projections revealed that the current species' range, which encompasses 6749.8 km2 (40.8%) of the landscape, will decline by 10% (2050: RCP2.6, MRI-CGCM3) to 45% (2070: RCP8.5, BCC-CSM1-1). About 1850 km2 (27.4%) of the current range is covered by a network of conservation (CAs) and no-hunting (NHAs) areas which are predicted to decline by 0.64% (2050: RCP2.6, MRI-CGCM3) to 15.56% (2070: RCP8.5, BCC-CSM1-1) due to climate change. The loss of suitable habitats falling within the network of CAs and NHAs is a conservation challenge for brown bears because it may lead to bears moving outside the CAs and NHAs and result in subsequent increases in the levels of bear-human conflict. Thus, re-evaluation of the network of CAs and NHAs, establishing more protected areas in suitable landscapes, and conserving vital linkages between habitat patches under future climate change scenarios are crucial strategies to conserve and manage endangered populations of the brown bear.