Search for: All records

The Asian tiger mosquito ( Aedes albopictus ) arrived in the USA in the 1980’s and rapidly spread throughout eastern USA within a decade. The predicted northern edge of its overwintering distribution on the East Coast of the USA roughly falls across New York, Connecticut, and Massachusetts, where the species has been recorded as early as 2000. It is unclear whether Ae. albopictus populations have become established and survive the cold winters in these areas or are recolonized every year. We genotyped and analyzed populations of Ae. albopictus from the northeast USA using 15 microsatellite markers and compared them with other populations across the country and to representatives of the major global genetic clades to investigate their connectivity and stability. Founder effects or bottlenecks were rare at the northern range of the Ae. albopictus distribution in the northeastern USA, with populations displaying high levels of genetic diversity and connectivity along the East Coast. There is no evidence of population turnover in Connecticut during the course of three consecutive years, with consistent genetic structure throughout this period. Overall, these results support the presence of established populations of Ae. albopictus in New York, Connecticut, and Massachusetts, successfully overwintering and migrating in large numbers. Given the stability and interconnectedness of these populations, Ae. albopictus has the potential to continue to proliferate and expand its range northward under mean warming conditions of climate change. Efforts to control Ae. albopictus in these areas should thus focus on vector suppression rather than eradication strategies, as local populations have become firmly established and are expected to reemerge every summer. 

Urbanization is a persistent and widespread driver of global environmental change, potentially shaping evolutionary processes due to genetic drift and reduced gene flow in cities induced by habitat fragmentation and small population sizes. We tested this prediction for the eastern grey squirrel (Sciurus carolinensis), a common and conspicuous forest‐dwelling rodent, by obtaining 44K SNPs using reduced representation sequencing (ddRAD) for 403 individuals sampled across the species' native range in eastern North America. We observed moderate levels of genetic diversity, low levels of inbreeding, and only a modest signal of isolation‐by‐distance. Clustering and migration analyses show that estimated levels of migration and genetic connectivity were higher than expected across cities and forested areas, specifically within the eastern portion of the species' range dominated by urbanization, and genetic connectivity was less than expected within the western range where the landscape is fragmented by agriculture. Landscape genetic methods revealed greater gene flow among individual squirrels in forested regions, which likely provide abundant food and shelter for squirrels. Although gene flow appears to be higher in areas with more tree cover, only slight discontinuities in gene flow suggest eastern grey squirrels have maintained connected populations across urban areas in all but the most heavily fragmented agricultural landscapes. Our results suggest urbanization shapes biological evolution in wildlife species depending strongly on the composition and habitability of the landscape matrix surrounding urban areas.

 

TheAdelges(Dreyfusia)piceae(Ratzeburg) species complex is a taxonomically unstable group of six species. Three of the species are cyclically parthenogenetic [Ad.nordmannianae(Eckstein),Ad.prelli(Grossmann), andAd.merkeri(Eichhorn)] and three are obligately asexual [Ad.piceae,Ad.schneideri(Börner), andAd.nebrodensis(Binazzi & Covassi)]. Some species are high‐impact pests of fir (Abies) trees, so stable species names are needed to communicate effectively about management. Therefore, to refine species delimitation, guided by a reconstruction of their biogeographic history, we genotyped adelgids from Europe, North America, and the Caucasus Mountains region with 19 microsatellite loci, sequenced the COI DNA barcoding region, and compared morphology. Discriminant analysis of principal components of microsatellite genotypes revealed four distinct genetic clusters. Two clusters were morphologically consistent withAd.nordmannianae. One of these clusters consisted of samples from the Caucasus Mountains and northern Turkey, and the other included samples from this region as well as from Europe and North America, whereAd.nordmannianaeis invasive. A third cluster was morphologically consistent withAd.piceae, and included individuals from Europe, where it is native, and North America, where it is invasive. In North America, the majority ofAd.piceaeindividuals were assigned to two geographically widespread clones, suggesting multiple introductions. The fourth cluster included individuals morphologically consistent withAd.prelliorAd.merkeri. However, based on genetic assignments, hybrid simulations, and approximate Bayesian computation, we find it likely that these are contemporary hybrids betweenAd.nordmannianaeandAd.piceaethat arose independently in Europe and North America, so we propose thatAd.prelliandAd.merkeriare invalid. Finally, we synonymiseAd.schneideri(syn.n.)withAd.nordmannianaeand designateAd.nebrodensisas subspeciesAd.piceae nebrodensis(stat.n.). Our revised taxonomy therefore recognises two species:Ad.nordmannianaeandAd.piceae, which we estimate to have diverged recently, during one of the last two interglacial periods. Finally, we comment on this species complex being in the midst of transition between sexual and asexual reproduction, a pattern that is probably common in Adelgidae.

 

Conservation translocation projects must carefully balance multiple, potentially competing objectives (e.g. population viability, retention of genetic diversity, delivery of key ecological services) against conflicting stakeholder values and severe time and cost constraints. Advanced decision support tools would facilitate identifying practical solutions.

We examined how to achieve compromise across competing objectives in conservation translocations via an examination of giant tortoises in the Galapagos Islands with ancestry from the extinct Floreana Island species (Chelonoidis niger). Efforts have begun to populate Floreana Island with tortoises genetically similar to its historical inhabitants while balancing three potentially competing objectives – restoring ecosystem services (sustaining a high tortoise population size), maximizing genome representation of the extinctC. nigerspecies and maintaining a genetically diverse population – under realistic cost constraints.

We developed a novel approach to this conservation decision problem by coupling an individual‐based simulation model with generalized additive models and global optimization. We identified several incompatibilities among programme objectives, with quasi‐optimal single‐objective solutions (sets of management actions) differing substantially in programme duration, translocation age, incubation temperature (determinant of sex ratio) and the number of individuals directly translocated from the source population.

Quasi‐optimal single‐objective solutions were able to produce outcomes (i.e. population size and measures of genetic diversity andC. nigergenome representation) to within 75% of their highest simulated outcomes (e.g. highest population size achieved across all simulations) within a cost constraint ofc. $2m USD, but these solutions resulted in severe declines (up to 74% reduction) in outcomes for non‐focal objectives. However, when all programme objectives were equally weighted to produce a multi‐objective solution, all objectives were met to within 90% of the highest achievable mean values across all cost constraints.

Synthesis and applications. Multi‐objective conservation translocations are likely to encounter complex trade‐offs and conflicts among programme objectives. Here, we developed a novel combination of modelling approaches to identify optimal management strategies. We found that solutions that simultaneously addressed multiple, competing objectives performed better than single‐objective solutions. Our model‐based decision support tool demonstrates that timely, cost‐effective solutions can be identified in cases where management objectives appear to be incompatible.