Keeping the blood flowing—plasminogen activator genes and feeding behavior in vampire bats

The blood feeding vampire bats emerged from New World leaf-nosed bats that fed on fruit and insects. Plasminogen activator, a serine protease that regulates blood coagulation, is known to be expressed in the saliva of Desmodus rotundus (common vampire bat) and is thought to be a key enzyme for the emergence of blood feeding in vampire bats. To better understand the evolution of this biological function, we studied the plasminogen activator (PA) genes from all vampire bat species in light of their feeding transition to bird and subsequently mammalian blood. We include the rare species Diphylla ecaudata and Diaemus youngi, where plasminogen activator had not previously been studied and demonstrate that PA gene duplication observed in Desmodus is not essential to the vampire phenotype, but relates to the emergence of predominant mammalian blood feeding in this species. Plasminogen activator has evolved through gene duplication, domain loss, and sequence evolution leading to change in fibrin-specificity and susceptibility to plasminogen activator inhibitor-1. Before undertaking this study, only the four plasminogen activator isoforms from Desmodus were known. The evolution of vampire bat plasminogen activators can now be linked phylogenetically to the transition in feeding behavior among vampire bat species from bird to mammalian blood. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

杂草对重金属的生物积累特性的研究

采用小区实验法对东北地区 1 1科 2 2种田间杂草进行重金属累积特性研究。结果表明 :欧洲千里光、巨荬菜、欧亚旋覆花、猪毛蒿、黄花蒿、石防风和柳叶刺蓼 7种植物对 Cd的富集系数最大 ,且地上部 Cd的含量大于根部 Cd的含量 ,具备了重金属超富集植物的基本特征 ;植物地上部重金属含量与植物上部生物量的大小无关 ;以杂草为研究对象 ,有可能筛选出地上部重金属富集量大并且地上部生物量也高的超富集植物。     

Species diversity variation of Cupressus funebris secondary forest in landslide site after 5.12 Wenchuan Earthquake北大核心CSCD

The characteristics of species diversity in Cupressus funebris secondary forest under the effect of geological hazard were explored by selecting the typical landslide surface of Fenghuang Mountain, Leigu Town, Beichuan County, which was derived from the 5.12 Wenchuan earthquake. The results showed that 93 species belonged to 42 families, and 78 genera were found in the landslide area, where the main families were Compositae, Leguminosae, and Gramineae-based. Further, 97 species in the transition area belonged to 39 families and 80 genera, and the main families were Compositae, Gramineae, and Rosaceae-based. In all, 108 species were recorded in the non-landslide area, which belonged to 59 families and 92 genera, the main families of which were Compositae, Rosaceae, and Gramineae-based. Compositae and Gramineae played important roles in the landslide recovery process after earthquake. The Pielou index (JSW) was the highest in the non-landslide area of the herb layer, whereas the richness index (D) was the lowest; the Shannon-Wiener index (H) and Simpson index (H') showed medium values. In the non-landslide area, the D, H, and H' were the highest in the shrub layer, whereas the JSW was the lowest. Further, the species diversity index of the transitional area was higher than that of the landslide area. In the tree layer, the D and H were both the highest and lowest in the landslide area and transition area, respectively. In contrast, the H' and JSW were the highest in the transition area and the lowest in the non-landslide area. The distribution of vegetation was generally consistent with the distribution of soil nutrients in the spatial distribution of surface soil nutrients. The succession of trees in the landslide area was relatively slow and at the initial stage, and the pioneer species were Coriaria nepalensis, Leptopus chinensis, and Arthraxon lanceolatus in this area. Taken together, the findings suggested that the stability of a plant community can be increased by improving the soil and stabilizing the slope. © 2018 Science Press. All rights reserved.     

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

Advancing indigenous self-determination through endangered species protection: Idaho gray wolf recovery

As part of the right of indigenous cultures to self-determination, several international bodies have recognized and addressed the role of indigenous communities in natural resources management, including the conservation of biodiversity. In the United States, disagreements regarding the application of the federal Endangered Species Act to Native American tribes have hindered the relationship between the federal and tribal governments on endangered species recovery. Our research examines the efforts of one Native American tribe, the Nez Perce, and the United States federal government to collaborate on federal gray wolf recovery in central Idaho. We interviewed members of the Nez Perce Tribe and U.S. Fish and Wildlife Service to characterize their relationship and explore the context in which the recovery program was implemented. Respondents attributed the success of the biological aspects of wolf recovery to the robustness of the wolf as a species and to close interagency coordination at the operational level. However, differences of opinion existed between the Tribe and Service concerning program funding, policy planning, and the rights and role of the Tribe in wolf management via co-management and cooperative management regimes. Respondents from both governments noted a clear hierarchical relationship at the strategic level, where policy planning and decision-making rested with the federal government. Lessons drawn from this case study can be applied across the international spectrum to improving partnerships, particularly at the strategic level, between indigenous and non-indigenous governance structures for protecting endangered species.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Estimating the vulnerability of fifteen tree species under changing climate in Northwest North America

In the Pacific northwestern (PNW) region of North America, climatic conditions have significantly warmed since a predominantly cool phase of the Pacific North American circulation patterns between 1950 and 1975. What are the implications of this shift in climate for the vulnerability of native tree species? To address this question, we combined mechanistic and statistical models to assess where a variety of native tree species might be more vulnerable within their recorded ranges and where they might potentially migrate. For long-lived species that are well adapted to compete, seasonal differences in photosynthesis and water use offer insights helpful in predicting their distributions. To evaluate the general response of conifers to climatic variation across the region, we previously applied a process-based model (3-PG), to simulate the growth and maximum leaf area index that Douglas-fir could attain within recognized forested areas. We then constructed automated decision tree models to define and map the ecological distributions of 15 tree species based on differences in how photosynthesis was constrained by drought, daytime temperatures, high evaporative demand, and the frequency of frost. For the baseline climate period (1950-1975), the decision tree models predicted presence and absence of each species at ∼23,000 observations with an average accuracy of 81%, with an average kappa statistic of 0.74. In this paper the same models were run annually for the period between 1976 and 2006 for each species, and the areas defined as remaining suitable or becoming vulnerable to disturbance were identified based on whether more or less than half of the years fell within the originally defined limits. Based on these criteria, 70% of the species recorded ranges remained suitable, with 30% deemed vulnerable. Results varied notably by species with western red cedar and western hemlock remaining highly adapted, with potential for range expansion in area of up to 50% relative to the baseline period. In contrast, ponderosa pine, lodgepole pine, grand, and noble fir were classified as vulnerable with potential net contractions in their ranges. The analysis was extended through the rest of the 21st century using climatic projections from the Canadian global circulation model with a high fossil fuel emission scenario (A2) and compared to other previously published species range predictions.