Inference of selection pressures that drive insecticide resistance in Anopheles and Culex mosquitoes in Korea.

Pyrethroids are primarily used for mosquito control in Korea. However, high frequencies of mutations conferring resistance to not only pyrethroids but also to other insecticides have been found in mosquito populations. This study aimed to examine the hypothesis that insecticides used outside of public health may play a role in selection. Briefly, the resistance mutation frequencies to three insecticide groups (pyrethroids, organophosphates, and cyclodienes) were estimated in two representative groups of mosquito species (Anopheles Hyrcanus Group and Culex pipiens complex). The relationship between these frequencies and the land-use status of the collection sites was investigated through multiple regression analysis. In the Anopheles Hyrcanus Group, the frequencies of both ace1 (organophosphate resistance) and rdl (cyclodiene resistance) mutations were positively correlated with 'proximity to golf course', possibly be due to the insecticides used for turf maintenance. They also showed positive correlations with field area and rice paddy area, respectively, suggesting the role of agricultural insecticides in the selection of these resistance traits. For the Cx. pipiens complex, the kdr (pyrethroid resistance), ace1, and rdl mutations were positively correlated with the residential area, field, and rice paddy, respectively. Therefore, pyrethroids used for public health could serve as a direct source of resistance selection pressure against kdr, whereas non-public health insecticides may pose primary selection pressure against the ace1 and rdl traits. The current findings suggest that the insecticides used in agriculture and the golf industry play a significant role in mosquito selection, despite variations in the extent of indirect selection pressure according to the mosquito groups and insecticide classes.

The high climate vulnerability of western Mediterranean forests.

Understanding the effects of climate change is one of the most challenging goals for biodiversity conservation. The forests of Andalusia, in Southern Spain, are part of an important Mediterranean Basin biodiversity hotspot. However, great changes in climate are expected to occur in this region, and there is an increasing need to assess the vulnerability of its vegetation. We assess the vulnerability of twelve forest types in the region that are included in the European Directive 92/43/EEC as Habitats of Community Interest (HCI). HCI are natural habitat types which are in danger, have a small natural range, or present an outstanding example of a biogeographical regions in the European Union. We assessed vulnerability by analyzing the climate exposure level of each forest type under two global climate models (MRI-CGCM3, which predicts warmer and wetter conditions, and MIROC-ESM which predicts hotter and drier conditions), two emission scenarios (RCP4.5, a representative concentration pathway that predicts stable emissions of CO2, and RCP8.5, that predicts the highest CO2 emissions) by the mid- and end-century time periods. The vulnerability analysis also includes the sensitivity and adaptive capacity of the dominant tree species which compose each forest type. An overall vulnerability score was calculated for each forest type, model, scenario and time period. High-elevation forest types and those with high moisture requirements were more vulnerable to climate change, while forest types dominated by more thermophilic species were less vulnerable and more resilient. The worst climate impacts were predicted in the MIROC-ESM model and RCP8.5 scenario by the end of the century (2070-2100), while the least climatic stress was obtained in the MRI-CGCM3 model and RCP4.5 scenario by the mid-century (2040-2070), which still shows high potential stress for most forest types. By the end of the century, the climate exposure of the entire forest domain will range between 32 % in the least stressful situation (MRI-CGCM3 and RCP4.5), and 98 % in the most climatically stressful situation (MIROC-ESM and RCP8.5). However, the effects of climate change will be perceptible by the mid-century, with most of the HCI forest types suffering climate stress. The "Andalusian oak forest" and the "Corylus wet forest" types were the most vulnerable to climate change, while the "Mediterranean pine forest", the "Olea and Ceratonia forests" and the "oak forests" were the least vulnerable. This assessment identifies the vulnerable forest types to climate change in the south of the Iberian Peninsula, and provides context for natural resource managers in making decisions about how to adapt forests to the impacts of climate change.

Integrating the Rabinowitz rarity framework with a National Plant Inventory in South Korea.

Increasingly large presence-only survey datasets are becoming available for use in conservation assessments. Potentially, these records could be used to determine spatial patterns of plant species rarity and endemism. We test the integration of a large South Korean species record database with Rabinowitz rarity classes. Rabinowitz proposed seven classes of species rarity using three variables: geographic range, habitat specificity, and local population size. We estimated the range size and local abundance of 2,215 plant species from species occurrence records and habitat specificity as the number of landcover types each species' records were found in. We classified each species into a rarity class or as common, compared species composition by class to national lists, and mapped the spatial pattern of species richness for each rarity class. Species were classed to narrow or wide geographic ranges using 315 km, the average from a range size index of all species (D max), based on maximum distance between observations. There were four classes each within the narrow and wide range groups, sorted using cutoffs of local abundance and habitat specificity. Nationally listed endangered species only appeared in the narrow-range classes, while nationally listed endemic species appeared in almost all classes. Species richness in most rarity classes was high in northeastern South Korea especially for species with narrow ranges. Policy implications. Large presence-only surveys may be able to estimate some classes of rarity better than others, but modification to include estimates of local abundance and habitat types, could greatly increase their utility. Application of the Rabinowitz rarity framework to such surveys can extend their utility beyond species distribution models and can identify areas that need further surveys and for conservation priority. Future studies should be aware of the subjectivity of the rarity classification and that regional scale implementations of the framework may differ.

Assessing shortfalls and complementary conservation areas for national plant biodiversity in South Korea.

Protected areas (PAs) are often considered the most important biodiversity conservation areas in national plans, but PAs often do not represent national-scale biodiversity. We evaluate the current conservation status of plant biodiversity within current existing PAs, and identify potential additional PAs for South Korea. We modeled species ranges for 2,297 plant species using Multivariate Adaptive Regression Splines and compared the level of mean range representation in South Korea's existing PAs, which comprise 5.7% of the country's mainland area, with an equal-area alternative PA strategy selected with the reserve algorithm Marxan. We also used Marxan to model two additional conservation scenarios that add lands to approach the Aichi Biodiversity Target objectives (17% of the country). Existing PAs in South Korea contain an average of 6.3% of each plant species' range, compared to 5.9% in the modeled equal-area alternative. However, existing PAs primarily represent a high percentage of the ranges for high-elevation and small range size species. The additional PAs scenario that adds lands to the existing PAs covers 14,587.55 km2, and would improve overall plant range representation to a mean of 16.8% of every species' range. The other additional PAs scenario, which selects new PAs from all lands and covers 13,197.35 km2, would improve overall plant range representation to a mean of 13.5%. Even though the additional PAs that includes existing PAs represents higher percentages of species' ranges, it is missing many biodiversity hotspots in non-mountainous areas and the additional PAs without locking in the existing PAs represent almost all species' ranges evenly, including low-elevation ones with larger ranges. Some priority conservation areas we identified are expansions of, or near, existing PAs, especially in northeastern and southern South Korea. However, lowland coastal areas and areas surrounding the capital city, Seoul, are also critical for biodiversity conservation in South Korea.

Mapping National Plant Biodiversity Patterns in South Korea with the MARS Species Distribution Model.

Accurate information on the distribution of existing species is crucial to assess regional biodiversity. However, data inventories are insufficient in many areas. We examine the ability of Multivariate Adaptive Regression Splines (MARS) multi-response species distribution model to overcome species' data limitations and portray plant species distribution patterns for 199 South Korean plant species. The study models species with two or more observations, examines their contribution to national patterns of species richness, provides a sensitivity analysis of different range threshold cutoff approaches for modeling species' ranges, and presents considerations for species modeling at fine spatial resolution. We ran MARS models for each species and tested four threshold methods to transform occurrence probabilities into presence or absence range maps. Modeled occurrence probabilities were extracted at each species' presence points, and the mean, median, and one standard deviation (SD) calculated to define data-driven thresholds. A maximum sum of sensitivity and specificity threshold was also calculated, and the range maps from the four cutoffs were tested using independent plant survey data. The single SD values were the best threshold tested for minimizing omission errors and limiting species ranges to areas where the associated occurrence data were correctly classed. Eight individual species range maps for rare plant species were identified that are potentially affected by resampling predictor variables to fine spatial scales. We portray spatial patterns of high species richness by assessing the combined range maps from three classes of species: all species, endangered and endemic species, and range-size rarity of all species, which could be used in conservation planning for South Korea. The MARS model is promising for addressing the common problem of few species occurrence records. However, projected species ranges are highly dependent on the threshold and scale criteria, which should be assessed on a per-project basis.