Female reproductive qualities affect male painted turtle (Chrysemys picta marginata) reproductive success

Male reproductive success (RS) in polygamous species with minimal social systems is often determined by the number of mates. However, because male RS is translated through females, the number of offspring sired can also be influenced by female qualities. Empirically sufficient data to document how tradeoffs between mate number and quality influence male RS are seldom available for long-lived, iteroparous species. We combined long-term life history data (1983–2006) on the E. S. George Reserve (ESGR, MI, USA) with parentage data from 155 clutches of 59 female painted turtles (Chrysemys picta marginata) of varying reproductive frequencies (2003–2006) to determine the relative contribution of female numbers and qualities on male RS. One previously documented trait of female painted turtles that can have substantial influences on male RS is repeat paternity through the use of stored sperm to fertilize over 95 % of within-year clutches. In addition, our study found that second-clutch producing female painted turtles on the ESGR have higher among-year reproductive frequencies than do first-clutch only females. Multiple paternity was detected in 14.1 % of clutches (min-max?=?6.1–30.0 % annually), and the number of mates of both sexes was low annually (males 1.0; females 1.2) and over 4 years (males 1.1; females 1.7). Among successful males, RS varied substantially (1–32 offspring) and was strongly influenced by the combination of female reproductive frequency and repeat paternity (>38 % among years), but not mate number. Low mate number for both sexes was unexpected in a species without complex mating behaviors or parental care.     

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

Urinary stones as a novel matrix for human biomonitoring of toxic and essential elements

Monitoring of body burden of toxic elements is usually based on analysis of concentration of particular elements in blood, urine and/or hair. Analysis of these matrices, however, predominantly reflects short- or medium-term exposure to trace elements or pollutants. In this work, urinary stones were investigated as a matrix for monitoring long-term exposure to toxic and essential elements. A total of 431 samples of urinary calculi were subjected to mineralogical and elemental analysis by infrared spectroscopy and inductively coupled plasma mass spectrometry. The effect of mineralogical composition of the stones and other parameters such as sex, age and geographical location on contents of trace and minor elements is presented. Our results demonstrate the applicability of such approach and confirm that the analysis of urinary calculi can be helpful in providing complementary information on human exposure to trace metals and their excretion. Analysis of whewellite stones (calcium oxalate monohydrate) with content of phosphorus <0.6 % has been proved to be a promising tool for biomonitoring of trace and minor elements.

     

Geochemical distribution,bioavailability and potential toxicity of some trace metals in a complex micro-tidal estuary,Southwest India

The spatial and temporal variations of some trace metals in the surface sediments of Cochin Estuary were analyzed along with their geochemical associations to identify the possible sources, bioavailability and the health risks posed by them. The dominance of kaolinite and suggested that clay minerals distribution is influenced by sediment sorting. Total metal analysis revealed enrichment for Cd, Pb and Zn due to anthropogenic activities. The speciation analysis established that notwithstanding the large availability, carbonate as well as organic and sulfides bound fractions showed negligible associations with most of the metals. Hydrous Fe–Mn oxides appeared to play a major role in controlling the fate and transport of these metals in the sediments of Cochin Estuary. Lower contribution of the residual fractions for Cd (21%–26%), Pb (<60%) and Zn (24%–42%) indicated an obvious increase of other geochemical fractions. Risk assessment analysis revealed that regardless of total concentration, none of the analyzed metals were at safe levels in the estuary as appreciable percentages were found to be associated with mobile geochemical forms. The speciation study conspicuously established that the metals originating from non-geogenic sources are largely associated with the labile fractions and hence are more detrimental to the aquatic biota.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

Isoprene emissions and climate

Biogenic volatile organic compounds (BVOCs) play an important role in atmospheric chemistry and the carbon cycle. Isoprene is quantitatively the most important of the non-methane BVOCs (NMBVOCs), with an annual emission of about 400–600 TgC; about 90% of this is emitted by terrestrial plants. Incorporating a mechanistic treatment of isoprene emissions within land-surface schemes has recently become a focus for the modelling community, the aim being to quantify the potential magnitude of associated climate feedbacks. However, these efforts are hampered by major uncertainties about why plants emit isoprene and the relative importance of different environmental controls on isoprene emission. The availability and reliability of observations of isoprene fluxes from different types of vegetation is limited, and this also imposes constraints on model development. Nevertheless, progress is being made towards the development of mechanistic models of isoprene emission which, in conjunction with atmospheric chemistry models, will ultimately allow improved quantification of the feedbacks between the terrestrial biosphere and climate under past and future climate states.     

Assessment of essential and non-essential elements in selected traditional medicines from India,Ghana and China

Environmental Science and Pollution Research - Traditional medicine (TM) also known as folk medicine consists of medical knowledge systems that were developed over generations in various countries...     

Distribution of genetic elements associated with antibiotic resistance in treated and untreated animal husbandry waste and wastewater

Environmental Science and Pollution Research - Animal breeding for meat production based on swine, cattle, poultry, and aquaculture is an activity that generates several impacts on the environment,...     

Optimisation of systems to locate discrete gamma-ray sources within a large search area

Most systems used to locate discrete gamma-ray sources involve systematically passing a detector over the search area while seeking a significant increase in the observed count-rate. This paper discusses the ways in which such systems may be designed to maximise the probability of locating a source. It is shown that optimised systems use a collimated, energy-discriminating detector and overlapping counting intervals determined by the scanning geometry and speed.