Persistence of genetic diversity and phylogeographic structure of three New Zealand forest beetles under climate change

Climate change will lead to range shifts and genetic diversity losses of dung beetles in the Gobi Desert and Mongolian Steppe

Desertification is known to be a major threat to biodiversity, yet our understanding of the consequent decline in biodiversity remains insufficient. Here, we predicted climate change-induced range shifts and genetic diversity losses in three model dung beetles: Colobopterus erraticus, Cheironitis eumenes, and Gymnopleurus mopsus, distributed across the Gobi Desert and Mongolian Steppe, areas known for desertification. Phylogeographic analyses of mitochondrial COI sequences and species distribution modeling, based on extensive field investigations spanning 14 years, were performed. Species confined to a single biome were predicted to contract and shift their distribution in response to climate change, whereas widespread species was predicted to expand even if affected by range shifts. We indicated that all species are expected to experience significant haplotype losses, yet the presence of high singleton frequencies and low genetic divergence across geographic configurations and lineages mitigate loss of genetic diversity. Notably, Cheironitis eumenes, a desert species with low genetic diversity, appears to be the most vulnerable to climate change due to the extensive degradation in the Gobi Desert. This is the first study to predict the response of insects to desertification in the Gobi Desert. Our findings highlight that dung beetles in the Gobi Desert and Mongolian Steppe might experience high rates of occupancy turnover and genetic loss, which could reshuffle the species composition.

Impacts of climate change on herpetofauna diversity in the Qinghai-Tibetan Plateau

Although numerous studies on the impacts of climate change on biodiversity have been published, only a handful are focused on the intraspecific level or consider population-level models (separate models per population). We endeavored to fill this knowledge gap relative to the Qinghai-Tibetan plateau (QTP) by combining species distribution modeling (SDMs) with population genetics (i.e., population-level models) and phylogenetic methods (i.e., phylogenetic tree reconstruction and phylogenetic diversity analyses). We applied our models to 11 endemic and widely distributed herpetofauna species inhabiting high elevations in the QTP. We aimed to determine the influence of environmental heterogeneity on species' responses to climate change, the magnitude of climate-change impacts on intraspecific diversity, and the relationship between species range loss and intraspecific diversity losses under 2 shared socioeconomic pathways (SSP245 and SSP585) and 3 future periods (2050s, 2070s, and 2090s). The effects of global climatic change were more pronounced at the intraspecific level (22% of haplotypes lost and 36% of populations lost) than the morphospecies level in the SSP585 climate change scenario. Maintenance of genetic diversity was in general determined by a combination of factors including range changes, species genetic structure, and the part of the range predicted to be lost. This is owing to the fact that the loss and survival of populations were observed in species irrespective of the predicted range changes (contraction or expansion). In the southeast (mountainous regions), climate change had less of an effect on range size (>100% in 3 species) than in central and northern QTP plateau regions (range size <100% in all species). This may be attributed to environmental heterogeneity, which provided pockets of suitable climate in the southeast, whereas ecosystems in the north and central regions were homogeneous. Generally, our results imply that mountainous regions with high environmental heterogeneity and high genetic diversity may buffer the adverse impacts of climate change on species distribution and intraspecific diversity. Therefore, genetic structure and characteristics of the ecosystem may be crucial for conservation under climate change.

Contrasting adaptive genetic consequences of stream insects under changing climate

Freshwater biodiversity undergoes degradation due to climate change. Researchers have inferred the effects of climate change on neutral genetic diversity, assuming the fixed spatial distributions of alleles. However, the adaptive genetic evolution of populations that may change the spatial distribution of allele frequencies along environmental gradients (i.e., evolutionary rescue) have largely been overlooked. We developed a modeling approach that projects the comparatively adaptive and neutral genetic diversities of four stream insects, using empirical neutral/ putative adaptive loci, ecological niche models (ENMs), and a distributed hydrological-thermal simulation at a temperate catchment under climate change. The hydrothermal model was used to generate hydraulic and thermal variables (e.g., annual current velocity and water temperature) at the present and the climatic change conditions, projected based on the eight general circulation models and the three representative concentration pathways scenarios for the two future periods (2031-2050, near future; 2081-2100, far future). The hydraulic and thermal variables were used for predictor variables of the ENMs and adaptive genetic modeling based on machine learning approaches. The increases in annual water temperature in the near- (+0.3-0.7 °C) and far-future (+0.4-3.2 °C) were projected. Of the studied species, with different ecologies and habitat ranges, Ephemera japonica (Ephemeroptera) was projected to lose rear-edge habitats (i.e., downstream) but retain the adaptive genetic diversity owing to evolutionary rescue. In contrast, the habitat range of the upstream-dwelling Hydropsyche albicephala (Trichoptera) was found to remarkably decline, resulting in decreases in the watershed genetic diversity. While the other two Trichoptera species expanded their habitat ranges, the genetic structures were homogenized over the watershed and experienced moderate decreases in gamma diversity. The findings emphasize the evolutionary rescue potential, depending on the extent of species-specific local adaptation.

The change in biocomfort zones in the area of Muğla province in near future due to the global climate change scenarios

It is inevitable that the global climate change, which has important effects on the climate throughout the world, would have significant effects on the biocomfort zones. Hence, how global climate change will change the biocomfort zones should be determined and the data to be obtained should be used in urban planning projects. In the current study, SSPs 245 and SSPs 585 scenarios were taken as a basis, and the potential effects of global climate change on the biocomfort zones in Muğla province, Türkiye were investigated. Within the scope of the present study, the current status of biocomfort zones in Muğla and their possible conditions in years 2040, 2060, 2080, and 2100 were compared using DI and ETv methods. At the end of the study, it was estimated that, according DI method, 14.13% of Muğla province are in cold zone, 31.96% in cool zone, and 53.71% in comfortable zone. According to the SSPs 585 scenario, together with the increase in temperature, the cold and cool zones will totally disappear in year 2100, comfortable zones will decrease to 31.22%, and approx. 68.78% of the province will be in hot zone. According to the calculations made using ETv method, Muğla province currently consists of moderately cold zones by 2%, quite cold zones by 13.16%, slightly cold zones by 57.06%, and mild zones by 27.79%. Based on the SSPs 585 scenario for the year 2100, it is projected that Muğla will consist of slightly cool zones by 1.41%, mild zones by 14.42%, and comfortable zones by 68.06%, besides warm zones by 16.11% which are not present at this moment. This finding suggests that especially the cooling costs will increase and the air-conditioning systems to be used will negatively affect the global climate change through the energy consumption and the gases used.

Genetic Variation and Population Structure of the Old World Bollworm Helicoverpa armigera (Hübner, 1808) (Lepidoptera: Noctuidae) in Ethiopia

Helicoverpa armigera is one of the most destructive insect pests of economically valuable crops in the world. Despite its economic importance, the population genetic structure of this insect remains unexplored in Ethiopia. To investigate the genetic diversity and population structure of H. armigera, we sampled 170 individuals from 15 populations throughout Ethiopia. We sequenced a fragment of the mitochondrial cytochrome b (cyt b) gene and five exon-primed intron-crossing (EPIC) markers. Twenty cyt b haplotypes with low-to-moderate haplotype diversity (mean Hd = 0.537) and high nucleotide diversity (mean Pi = 0.00339) were identified. The most frequently observed and widely distributed cyt b haplotype was designated as Hap_1 (67.058%), which is identical to sequences found across the globe. Tajima's D and Fu's F for the cyt b data were negative, supporting a model of population expansion. Within populations, a mean of 2.493 alleles/locus was recorded across the five EPIC loci, ranging from 1.200 to 3.600 alleles/locus. The highest mean effective number of alleles/population was 2.369 and the lowest was 1.178. The mean observed heterozygosity (HO) of the five loci (0-0.289; mean 0.104 ± 0.020) was lower than the expected heterozygosity (HE) (0.095-0.523; mean 0.258 ± 0.028). AMOVA detected significant genetic structure with 61% of the total molecular genetic variation of EPIC genotypes occurring between populations, suggesting a considerable degree of differentiation among populations. STRUCTURE analyses clustered the H. armigera populations into three distinct population groups but very low isolation by distance (R2 = 0.0132, P < 0.05).

Dramatic impact of future climate change on the genetic diversity and distribution of ecologically relevant Western Mediterranean Carex (Cyperaceae)

Anticipating the evolutionary responses of species to ongoing climate change is essential to propose effective management and conservation measures. The Western Mediterranean Basin constitutes one of the hotspots of biodiversity where the effects of climate change are expected to be more dramatic. Plant species with ecological relevance constitute ideal models to evaluate and predict the impact of climate change on ecosystems. Here we investigate these impacts through the spatio-temporal comparison of genetic diversity/structure (AFLPs), potential distribution under different future scenarios of climate change, and ecological space in two Western Mediterranean sister species of genus Carex. Both species are ecologically key in their riparian habitats, but display contrasting distribution patterns, with one widespread in the Iberian Peninsula and North Africa (C. reuteriana), while the other (C. panormitana) is a restricted, probably endangered, Central Mediterranean endemic. At present, we found a strong genetic structure driven by geography in both species, and lower values of genetic diversity and a narrower ecological space in C. panormitana than in C. reuteriana, while the allelic rarity was higher in the former than in C. reuteriana subspecies. Future projections predict an overall dramatic reduction of suitable areas for both species under all climate change scenarios, which could be almost total for C. panormitana. In addition, gene diversity was inferred to decrease in all taxa, with genetic structure reinforcing in C. reuteriana by the loss of admixture among populations. Our findings stress the need for a reassessment of C. panormitana conservation status under IUCN Red List criteria and the implementation of conservation measures.

Improving prediction of rare species' distribution from community data

Species distribution models (SDMs) have been increasingly used to predict the geographic distribution of a wide range of organisms; however, relatively fewer research efforts have concentrated on rare species despite their critical roles in biological conservation. The present study tested whether community data may improve modelling rare species by sharing information among common and rare ones. We chose six SDMs that treat community data in different ways, including two traditional single-species models (random forest and artificial neural network) and four joint species distribution models that incorporate species associations implicitly (multivariate random forest and multi-response artificial neural network) or explicitly (hierarchical modelling of species communities and generalized joint attribute model). In addition, we evaluated two approaches of data arrangement, species filtering and conditional prediction, to enhance the selected models. The model predictions were tested using cross validation based on empirical data collected from marine fisheries surveys, and the effects of community data were evaluated by comparing models for six selected rare species. The results demonstrated that the community data improved the predictions of rare species' distributions to certain extent but might also be unhelpful in some cases. The rare species could be appropriately predicted in terms of occurrence, whereas their abundance tended to be underestimated by most models. Species filtering and conditional predictions substantially benefited the predictive performances of multiple- and single-species models, respectively. We conclude that both the modelling algorithms and community data need to be carefully selected in order to deliver improvement in modelling rare species. The study highlights the opportunity and challenges to improve prediction of rare species' distribution by making the most of community data.