Meiotic drivers are genetic variants that selfishly manipulate the production of gametes to increase their own rate of transmission, often to the detriment of the rest of the genome and the individual that carries them. This genomic conflict potentially occurs whenever a diploid organism produces a haploid stage, and can have profound evolutionary impacts on gametogenesis, fertility, individual behaviour, mating system, population survival, and reproductive isolation. Multiple research teams are developing artificial drive systems for pest control, utilising the transmission advantage of drive to alter or exterminate target species. Here, we review current knowledge of how natural drive systems function, how drivers spread through natural populations, and the factors that limit their invasion.

Among vertebrates, true parthenogenesis is known only in reptiles. Parthenogenetic lizards of the genus Darevskia emerged as a result of the hybridization of bisexual parental species. However, uncertainty remains about the mechanisms of the co-existence of these forms. The geographical parthenogenesis hypothesis suggests that unisexual forms can co-exist with their parental species in the “marginal” habitats. Our goal is to investigate the influence of environmental factors on the formation of ecological niches and the distribution of lizards. For this reason, we created models of species distribution and ecological niches to predict the potential geographical distribution of the parthenogenetic and its parental species. We also estimated the realized niches breadth, their overlap, similarities, and shifts in the entire space of predictor variables. We found that the centroids of the niches of the three studied lizards were located in the mountain forests. The “maternal” species D. mixta prefers forest habitats located at high elevations, “paternal” species D. portschinskii commonly occurs in arid and shrub habitats of the lower belt of mountain forests, and D. dahli occupies substantially an intermediate or “marginal” position along environmental gradients relative to that of its parental species. Our results evidence that geographical parthenogenesis partially explains the co-existence of the lizards.

Northern Eurasia is extensive and includes terrestrial and aquatic ecosystems that cover several natural zones and access to the seas of three oceans. As a result, it has been invaded by numerous invasive alien species (IAS) over large temporal and spatial scales. The purpose of this research was to assess invasion trends and construct species distribution models for the Russian TOP-100 most dangerous IAS. Environmentally suitable regions for IAS were established based on alien species attribute databases, datasets of 169,709 species occurrence records (SOR) and raster layers of environmental variables using species distribution modelling (MaxEnt). The objectives of this research were to (1) create databases of SOR for the TOP-100 IAS in Russia; 2) determine pathways, residence time, donor regions and trends of invasions; (3) determine the main types of spatial distributions of invasive species and their relation to residence time; and (4) distinguish regions with the highest richness of IAS that have a strong impact on the terrestrial and aquatic ecosystems of Russia. We found that although species invasions date back over 400 years, the number of naturalized IAS has increased non-linearly over the past 76 years. The TOP-100 list is mainly represented by unintentionally introduced species (62%) which are characterized by different introduction pathways. Species occurrence records revealed that 56 IAS are distributed locally, 26 are distributed regionally and 18 are widespread in Russia. Species with local, regional or widespread distributions were characterized by residence times of 55, 126 or 190 years, respectively. We found that IAS with local distribution can expand their range into suitable regions more extensively (expected increase by 32%) than widespread species (expected increase by only 7%). The procedure of identifying hot/cold spots locations based on SOR allowed us to identify the Russian regions with the highest richness of IAS. Our results and the integrated database that we created provide a framework for studying IAS over large temporal and spatial scales that can be used in the development of management plans for dangerous IAS.

The striped field mouse (Apodemus agrarius Pallas, 1771) is a widespread species in Northern Eurasia. It damages crops and carries zoonotic pathogens. Its current and future range expansion under climate change may negatively affect public health and the economy, warranting further research to understand the ecological and invasive characteristics of the species. In our study, we used seven algorithms (GLM, GAM, GBS, FDA, RF, ANN, and MaxEnt) to develop robust ensemble species distribution models (eSDMs) under current (1970–2000) and future climate conditions derived from global circulation models (GCMs) for 2021–2040, 2041–2060, 2061–2080, and 2081–2100. Simulation of climate change included high-, medium-, and low-sensitivity GCMs under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We analyzed the habitat suitability across GCMs and scenarios by constructing geographical ranges and calculating their centroids. The results showed that the range changes depended on both the sensitivity of GCMs and scenario. The main trends were range expansion to the northeast and partial loss of habitat in the steppe area. The striped field mouse may form a continuous range from Central Europe to East Asia, closing the range gap that has existed for 12 thousand years. We present 49 eSDMs for the current and future distribution of A. agrarius (for 2000–2100) with quantitative metrics (gain, loss, change) of the range dynamics under global climate change. The most important predictor variables determining eSDMs are mean annual temperature, mean diurnal range of temperatures, the highest temperature of the warmest month, annual precipitation, and precipitation in the coldest month. These findings could help limit the population of the striped field mouse and predict distribution of the species under global climate change.