Two new Thripidae (Thysanoptera) records from India with first description of Astrothrips aureolus males

The distribution of species changes over time, and the current distribution of different species could result from distinct eco-evolutionary processes. Thus, investigating the spatiotemporal changes in the niche and geographic range of species is fundamental to understanding those processes and mechanisms shaping the current distributions of species. However, many studies only compared the current distribution and niche of the target species, ignoring the fact that the range shift of species is a dynamic process. Here, we reconstructed niche evolution and range dynamics of species to provide more information on related eco-evolutionary processes. We focused on a monophyletic species complex,Chrysanthemum zawadskiispecies complex, in which species occupy diverse habitats and exhibit different distribution patterns. Specifically, we investigated the niche breadth and overlap between lineages or species of the complex in geographic and environmental spaces. We then tested the phylogenetic signals for different climatic variables and estimated the niche of ancestral nodes on a time-calibrated phylogeny. Next, we used phyloclimatic modeling to reconstruct the dynamics of range shift for this complex. Our results show that this complex contains both specialist and generalist species, and niche diverges greatly among different species and intraspecific lineages of the complex. The moisture gradient may be the primary driver of the niche divergence of species in the complex. The reconstruction of ancestral distribution shows that this complex originated in the Qinling mountains and surrounding areas during the early Pliocene, and then diverged with the range expansion and niche evolution. Species of the complex have different range dynamics. Based on our findings, we propose that niche evolution, range dynamics, and their coupling shape the distribution of species, which provides insight into the eco-evolutionary processes that formed the current distribution of species in theC. zawadskiicomplex.

Climate change is leading to shifts in the distribution of species. Whether species range contract or expand, this will cause the reshuffling of assemblages, with potential negative consequences on the functioning of ecosystems. Within the marine realm, coral reefs are among the most threatened ecosystems due to climate change and other Anthropogenic activities. Thus, understanding how the distribution of key species of coral reefs may change in the future is of paramount necessity. Early prediction of range shifts can drive the management strategy and enable mitigation or conservation actions. In this work we used species distribution models to predict the potential shifts in the distribution of important species among four major groups: reef builders, herbivorous invertebrates, macroalgae and reef fish. In general, our results revealed that major changes are expected in the distribution of species on the Tropical Western Atlantic, with many species expanding poleward and losing suitable areas in their current distribution. However, patterns varied among species and groups, with some species expanding, others contracting and some keeping stable distributions. In the final part of the work, we aggregated the results of multiple distribution models to identify how climate change may impact the richness and composition of Atlantic reefs. Again, despite some consistent general trends (richness decrease in areas of high diversity), there is some variability among groups. Together, our results reinforce that Atlantic reefs may look very different in the future with less functional diversity and that there is an urgent need to attain with the goals of the Paris agreement in order to ensure an at least better scenario for the Western Atlantic coral reefs.

Levins (1969) and Hanski (1982a,b) presented dynamic models that describe the fraction of population sites occupied by species. Levins' model predicts a unimodal distribution of species at sites, whereas Hanski's model yields a bimodal distribution: a mode of widespread "core" species, and a mode of rare "satellite" species. The existence of this dichotomy is the core-satellite hypothesis. Hanski's model also predicts a positive correlation between the fraction of sites occupied by a species (distribution) and the average population size within occupied sites (abundance). Levins' model generates no such correlation between distribution and abundance. We find that a large set of quadrat data on tallgrass prairie plants matches some of the predictions of Hanski's model: for plants of seven different soil series, distribution and abundance are positively correlated, and the distribution of species at sites is bimodal. The bimodality is obscured if distributions from the seven soil series are aggregated. Two earlier hypotheses have been proposed to explain the core-satellite dichotomy. Williams (1964) showed that the degree of bimodality in species distributions depends on the number of quadrats examined: specifically, the smaller the sample, the larger the size of the core mode, and this is true even for randomly assembled communities of species. For our data, the size of the core mode correlates negatively with sample size, as Williams predicted. However, a computer simulation showed that the observed core modes were significantly larger than would be expected by chance. Thus, Williams' sampling hypothesis does not entirely account for the bimodal distribution of prairie plant species. Raunkiaer (1934, see "law of distribution of frequencies") argued that the core mode represented those species best adapted to a particular habitat. He also noted that when quadrats of dissimilar habitat were combined, the bimodality disappeared. The distributions of tallgrass prairie plants, however, do not conform to Raunkiaer's explanation: core species tend to be widespread across all soil series. If Raunkiaer's hypothesis were correct, each species would be widespread on only a few soil series, and each soil series would support a different assemblage of core species. Although our analyses confirm the existence of the core-satellite dichotomy, they do not provide an explicit test of Hanski's model. The essence of the models by Hanski and Levins is that the distribution of each species is dynamic and fluctuates owing to stochastic variation in immigration and local extinction. The strongest test of Hanski's model would be to demonstrate that the distribution of each species varied through time and that the composition of the core and satellite modes was not constant. Long-term data about the distribution of species in a community are needed for such comparisons.

India has different bioclimatic zones and supports diverse aquatic habitats rich in biodiversity. For effective conservation of the endangered species in its habitat, it is essential to know the distribution of fish species in the environmental range, and for this, species distribution models are the efficient and innovative tools. The present study used the MaxEnt modeling technique for developing probability distribution models highlighting the distribution of fish species by analyzing the known occurrence records of Denison barb under genus Sahyadria (Sahyadria denisonii Day 1865 and Sahyadria chalakkudiensis (Menon et al., Rec Zool Surv India 97:61-63, 1999)) in relation to environmental variables typically incorporating seasonal and temporal variability. AUC of the models for Sahyadria species depicted good fitness. Both species were found sensitive to "solar radiation," "temperature seasonality," and "temperature annual range" and assessed as significant predictors. The sensitivity and distribution of both species to these environmental variables were found correlated with their breading and spawning seasons. "Precipitation" was determined as one of the significant climatic envelopes influencing the distribution of the species associated with river flow. The models showed the distribution of S. denisonii in the higher precipitation areas compared to S. chalakkudiensis. The probability distribution model with respect to the distribution of both species indicates a lineage barrier at Palghat Gap supporting the earlier studies. At the latitudinal scale, prediction of the suitable ecological habitat provides a detailed insight into the distribution of all genetic lineages of the genus Sahyadria. Evidently, the findings of this study can assist in determining ecological niches for endangered species of other areas and may aid in field surveys as well as developing conservation plans.

Variations in planktonic foraminiferal assemblages along north-south transects in the Indian Ocean

Climate change has the potential to alter the size, shape, and location of species’ distributions. As a result, the interactions between species are also likely to be impacted as novel species encounter each other and historical community assemblages are broken apart. To quantify the impact of distributional changes as a result of climate change on interacting species, distribution maps were produced for three species of invasive plant and their associated biological control agent at three time periods: current, 2050, and 2080. For each of the future time periods, two distribution maps were created for each species, representing the minimum and maximum emission scenarios considered. The area of the projected future distributions for each species was compared to the current distributions. Percent change in area of distribution was calculated to determine the effect of climate change on the distributions of individual species. The total area of overlap in the distribution of plants and their biological controls for each of the time periods and emission scenarios also was calculated and percent change from the current distribution was used to quantify the effect of climate change on the species interactions. The distributions of the invasive plant species do not follow a consistent trend across models. The distribution of St. Johnswort (Hypericum perforatum Linnaeus, 1753) is expected to increase by 2050, then decrease to an area smaller than the current distribution by 2080. Leafy spurge (Euphorbia esula Linnaeus, 1753) is predicted to have larger distributions by 2080 under both emission scenarios, although only the minimum emission scenario predicts an initial decrease from the current distribution to that expected for 2050. The distribution of yellow toadflax [Linaria vulgaris (Miller, 1768)] is expected to decrease under both emission scenarios by 2080. The distributions of two of the biological control agents (BCAs), Klamath weed beetle [Chrysolina quadrigemina (Suffrian, 1851)] and toadflax moth [Calophasia lunula (Hufnagel, 1766)], are expected to increase by 2080. For both future time periods and emission scenarios, the distribution of leafy spurge hawk moth [Hyles euphorbiae (Linnaeus, 1758)] is expected to decrease from its current area. The area of overlap between two pairs of species (St. Johnswort and the Klamath weed beetle; yellow toadflax and the toadflax moth) is predicted to increase over time. This indicates that the distributions of the invasive species and their associated BCAs will overlap to a greater extent than currently and the BCAs have the potential to remain viable control mechanisms. The area of overlap between leafy spurge and the leafy spurge hawk moth is expected to decrease over time, indicating that the distributions of the species are not likely to respond similarly to climate change. As a result, the leafy spurge hawk moth might not be a suitable control mechanism for leafy spurge in the future. Because of data limitations, the results of this work are applicable to basic understanding of the systems and species involved. However, similar work has the potential to lead to a better understanding of the impact of biotic interactions on invasive and non-native species. In smaller geographic extents, similar research could help prioritize management of invasion by identifying those species that are expected to have increased distributions and escape from their BCA as a result of future climate change.

The geographic distribution of species depends on their relationships with climate and on the biotic interactions of the species. Ecological Niche Models (ENMs) mainly consider climatic variables only and may tend to overestimate these distributions, especially for species strongly restricted by biotic interactions. We identified the preference of Laelia speciosa for different host tree species and include this information in an ENM. The effect of habitat loss and climate change on the distribution of these species was also estimated. Although L. speciosa was recorded as epiphyte at six tree species, 96% of the individuals were registered at one single species (Quercus deserticola), which indicated a strong biotic interaction. We included the distribution of this host tree as a biotic variable in the ENM of L. speciosa. The contemporary distribution of L. speciosa is 52,892 km2, which represent 4% of Mexican territory and only 0.6% of the distribution falls within protected areas. Habitat loss rate for L. speciosa during the study period was 0.6% per year. Projections for 2050 and 2070 under optimistic and pessimistic climate change scenarios indicated a severe reduction in its distribution. Climaticaly suitable areas will also shift upwards (200–400 m higher). When estimating the distribution of a species, including its interactions can improve the performance of the ENMs, allowing for more accurate estimates of the actual distribution of the species, which in turn allows for better conservation strategies.

Tulips are bulbous geophytes that have considerable commercial value worldwide. This genus primarily originated in the Tien Shan and Pamir-Alai mountain ranges, which surround the Ferghana Valley. The Ferghana Valley is home to five sections of the genus Tulipa L, represented by 23 taxa (22 species). However, there is a lack of detailed information about the distribution of Tulipa species in the natural geographic area of the Ferghana Valley. Therefore, to address this knowledge gap, we comprehensively investigated the spatial distribution of all Tulipa species in the valley. To assess the spatial distribution, the entire area was divided into 32 squares consisting of four latitudinal and eight longitudinal zones. The results showed that latitudinal zones B and C with 15 and 13 taxa, respectively, along with five longitudinal zones (A5, B3, B4, C2, and C3) with 5 to 10 taxa were hotspots for this genus. Additionally, the spatial distributions of the species in terms of the corresponding state borders, mountain ranges, endemism, and conservation issues were assessed. The findings of this study provide comprehensive information about the distribution of Tulipa species to assist with conservation initiatives ultimately to ensure the survival of various species.

Tree species respond to climate change at multiple scales, such as species physiological response at fine scale and species distribution (quantified by percent area) at broader spatial scale. At a given spatial scale, species physiological response and distribution can be correlated positively or negatively. The consistency of such correlation relationships at different spatial scales determines whether species responses derived from local scales can be extrapolated to broader spatial scales. In this study, we used a coupled modeling approach that coupled a plot-level ecosystem process model (LINKAGES) with a spatially explicit landscape model (LANDIS). We investigated species physiological responses and distribution responses to climate warming at the local, zonal and landscape scales respectively, and examined how species physiological response and distribution correlated at each corresponding scale and whether the correlations were consistent among these scales. The results indicate that for zonal and warming-sensitive species, the correlations between species physiological response and distribution are consistent at these spatial scales, and therefore the research results of vegetation response to climate warming at the local scale can be extrapolated to the zonal and landscape scales. By contrast, for zonal and warming-insensitive species the correlations among different spatial scales are consistent at some spatial scales but at other scales. The results also suggest that the results of azonal species at the local scale near their distribution boundaries can not be extrapolated simply to broader scales due to stronger responses to climate warming in those boundary regions.

PDF HTML阅读 XML下载 导出引用 引用提醒 山西平陆黄河湿地植物分类学多样性 DOI: 10.5846/stxb201312032872 作者: 作者单位: 山西大学 生命科学学院 太原,山西大学 生命科学学院 太原,山西大学黄土高原研究所 太原;山西大学 生命科学学院 太原 作者简介: 通讯作者: 中图分类号: 基金项目: 山西省回国留学人员科研项目(20100012); 山西省自然科学基金项目(2013011037-1); 科技部科技基础性工作专项资助(2011FY110300) Plant taxonomic diversity in Yellow River Wetland in Pinglu, Shanxi Author: Affiliation: School of Life Science,Shanxi University,,Institute of Loss Plateau,School of Life Science,Shanxi University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:传统的物种多样性通常使用物种数量指标α和β等多样性指数进行测度,由于其对取样和样本大小有依赖关系且极其敏感,因此取样方法的不同会对多样性的结果产生显著影响。分类学多样性方法基于分类学系统关系测量物种多样性,弥补了传统方法的不足,同时面对各种变量和不受控制的取样具有稳健性,同时也考虑了集合的分类学均匀度。不仅能反映植物群落多样性,还能间接反映环境与扰动间的关系,用于识别生态系统或生境是否处于退化阶段。为了探究平陆黄河湿地的物种多样性,检验分类学多样性方法在植物生态学方面的应用,选取了16个样地进行植物调查,并结合历史资料整理了种子植物名录,结果表明平陆黄河湿地共有植物368种,隶属于36目67科213属。含种最多的科为菊科和禾本科,分别为54种和45种。应用平均分类学差异指数(Δ+)和分类学差异变异指数(Λ+)研究了各样地的植物物种多样性:Δ+和Λ+的理论平均值分别为74.24和480;位于三门峡大坝上游和下游的样地和不同群落类型的分类学多样性均没有显著差异(P>0.05)。受人类干扰较大的车村和鳖干平均分类学差异指数值显著较低, Δ+分别为62.28和67.41,位于95%的置信漏斗外;而水分条件较好且人为干扰较少的南沟渡口和三湾湖平均分类学差异指数值最高为分别81.30和79.94。车村的分类差异变异指数值最高为814.44,其物种在不同分类阶元分布最不均一,涧北的分类差异变异指数值最低为423.31,其物种分布相对较均一。传统的多样性方法难以全面的反映某个区域的物种组成、分布和多样性,此外分类学多样性的高低与物种数量的多少没有一定的相关关系, Δ+与S、Λ+与S的相关关系分别为-0.257和-0.187(P > 0.05)。耕作、生态旅游、日常活动等人为干扰因素可能是造成平陆黄河湿地分类学多样性降低及物种在不同分类等级间分布不均匀的主要原因。 Abstract:A study of traditional diversity study focuses on the number of species in a given ecosystem. Traditional indices are extremely sensitive to the sampling method and sample size; changes in sampling efforts often significantly impact on the level of diversity in an ecosystem, and it is difficult to compare data sets collected at different times and regions. Taxonomic diversity is used to measure species diversity, and not only species abundances and distribution but also taxonomic relatedness are considered. Furthermore, this method is robust and minimally influenced by variables or uncontrolled sampling efforts. On the other hand, taxonomic evenness of an assemblage should also be considered. It not only reflects community diversity; but also provides information on the relationship between environmental factors and indirect disturbance, which are often applied to identify whether the ecological system or environment is undergoing degradation. To explore the species diversity in Yellow River Wetlands, Pinglu,Shanxi, and to test the application of taxonomic diversity in plant ecology, 16 sites were chosen around the Sanmenxia Dam, Pinglu and a species list was established. In the present study, 368 species belonging to 213 genera, 67 families and 36 orders were recorded in this region. Most of the species belonged to the families Compositae (54 species) and Poaceae (45 species). Plant species diversity was studied using average taxonomic distinctness (Δ+) and variation in taxonomic distinctness (Λ+) and a confidence funnel was obtained. The expected value of Δ+ and Λ+ were 74.24 and 480, respectively. No significant difference were observed among the different stands both upstream and downstream of Sanmenxia Dam and various community types (P>0.05). The average taxonomic distinctness values of Checun (62.28) and Biegan (67.41), which severely disturbed by human activities, were lower and below the confidence limit. The average taxonomic distinctness values for Nangou Ferry and Sanwan Lake, which were sites with better water availability and less disturbance, were higher, (81.30 and 79.94,respectively). The value of Λ+in Checun (814.44) was the highest, suggesting that the species distribution in this site was less homogeneous. The value of Λ+ in Jianbei (423.31) was the lowest, with species distribution being homogeneous. Traditional diversity methods hardly reflect species composition, distribution and diversity; and there is no certain correlations between taxonomic diversity and species number. The correlation coefficient between Δ+ and S was 0.257(P > 0.05), and that between Λ+ and S was -0.187(P > 0.05). Anthropogenic activites such as cultivation and tourism are dominant factors that have caused the significant decrease in taxonomic diversity and non-uniform sapatial distribution of species of different taxa in Yellow River Wetlands. 参考文献 相似文献 引证文献

Exploring species distribution patterns and understanding the environmental factors determining their distribution are essential for biodiversity conservation, especially in the context of global change. However, this knowledge is still lacking for many species, particularly at large spatial extents. Fungi, as one of the most diverse groups of organisms, play key roles in regulating global carbon and nutrient cycling. However, compared to plants or animals, studying the diversity and distribution of fungal species at large spatial extents is rather rare, partly due to the cryptic characteristics of fungal species, which result in many challenges with sampling. The ongoing digitization of natural history museum collections and the development of citizen science means more biodiversity data are becoming available and published by various cloud platforms, such as Global Biodiversity Information Facility (GBIF). Furthermore, the development of species distribution models and the availability of spatial environment data have further stimulated the use of opensource biodiversity data to inform governments and societies about the status of biodiversity and the impact of development. However, doubts about sampling bias, such as spatial bias and taxon bias of these open-source biodiversity data, have raised questions about the use of these data when drawing inferences about fungal diversity and distribution. By using macrofungal occurrence data integrated by Global Biodiversity Information Facility (GBIF) in Europe, this thesis aims to investigate the utility of open-source biodiversity data for understanding macrofungal diversity and distribution and to predict macrofungal distribution patterns under both now and future climate change over large spatial extents, using species distribution models. The research in this thesis firstly examined three widely used bias correction methods, i.e., geographical filtering of occurrence data, environmental filtering of occurrence data, and weighted background data selection, in predicting diversity patterns of macrofungal species. The results showed that the weighted background data selection method is an effective approach to mitigate the effects of sampling bias, which is useful for predicting macrofungal species diversity and distribution at a large spatial extent using MaxEnt, especially when there are species with a small sample size or with an unknown sampling effort. Secondly, using the weighted background data selection method, this thesis investigated whether long-term accumulated open biodiversity data could be used to reveal macrofungal diversity patterns at a large spatial extent. The results showed that the cumulative number of macrofungal species stabilized into distinct distribution patterns with localized hotspots of predicted macrofungal diversity with sampling efforts greater than approximately 30 years. Thirdly, this thesis predicted macrofungal diversity and distribution patterns and explored the determining factors at the continental level using long-term accumulated macrofungal data and weighted background data selection method in SDM. Analysis of the modelling results showed that eastern Denmark and southern Sweden are biodiversity hotspots for both functional groups of macrofungal species. Tree species and human disturbance (i.e., the human footprint index) were found to be the two most important predictor variables explaining the distribution of ectomycorrhizal and saprotrophic macrofungi. Lastly, this thesis predicted macrofungal response under future climate and tree distribution change. Overall, the models projected that large areas would exhibit increased macrofungal species richness under future climate change. However, the projected tree species distribution could restrict future macrofungi distributional shifts. This thesis contributes insights into the utility of open-source biodiversity data for understanding species diversity and distribution at large spatial extents. Our findings also provide information about macrofungal diversity and distribution patterns under current and future scenarios at a large spatial extent. Furthermore, the thesis highlights the importance of integrating open-source biodiversity data using SDMs and spatial data layers of geophysical variables to implement the post-2020 global biodiversity framework of the Convention on Biological Diversity and the 2030 EU Biodiversity Framework.

BackgroundPredicting the geographic distribution of widespread species through modeling is problematic for several reasons including high rates of omission errors. One potential source of error for modeling widespread species is that subspecies and/or races of species are frequently pooled for analyses, which may mask biologically relevant spatial variation within the distribution of a single widespread species. We contrast a presence-only maximum entropy model for the widely distributed oldfield mouse (Peromyscus polionotus) that includes all available presence locations for this species, with two composite maximum entropy models. The composite models either subdivided the total species distribution into four geographic quadrants or by fifteen subspecies to capture spatially relevant variation in P. polionotus distributions.ResultsDespite high Area Under the ROC Curve (AUC) values for all models, the composite species distribution model of P. polionotus generated from individual subspecies models represented the known distribution of the species much better than did the models produced by partitioning data into geographic quadrants or modeling the whole species as a single unit.ConclusionsBecause the AUC values failed to describe the differences in the predictability of the three modeling strategies, we suggest using omission curves in addition to AUC values to assess model performance. Dividing the data of a widespread species into biologically relevant partitions greatly increased the performance of our distribution model; therefore, this approach may prove to be quite practical and informative for a wide range of modeling applications.

Climate change poses a risk for rare plant species distribution in the future. The aim of this study was to predict the impact of moderate climate change on the growth and distribution of the rare endemic steppe species Artemisia salsoloides Willd. with the use of the maximum entropy method (MaxEnt). A. salsoloides distribution under moderate climate change (RCP 4.5 scenario) for 2040-2060 and 2061-2080 was modelled using a set of bioclimatic rasters (BIOCLIM) from the CHELSA database and topographic variables from GMTED2010. Model results showed an increase in the area of low and medium suitable habitats to the northeast of the current range, with no significant change in the area of highly suitable habitat predicted. The resulting models also showed no significant decline in habitat suitability in the current present sites in the future. Thus, moderate climate change will not have a significant negative impact on the distribution of the species, and no additional protection measures for the species in response to climate change are needed.

Potential impact of climate change on the distribution and conservation status of Pterocarpus marsupium, a Near Threatened South Asian medicinal tree species

When the species is also a habitat: Comparing the predictively modelled distributions of Lophelia pertusa and the reef habitat it forms