Testate amoebae are widely used in ecological and palaeoecological studies of peatlands, particularly as indicators of surface wetness. To ensure data are robust and comparable it is important to consider methodological factors which may affect results. One significant question which has not been directly addressed in previous studies is how sample size (expressed here as number of Sphagnum stems) affects data quality. In three contrasting locations in a Russian peatland we extracted samples of differing size, analysed testate amoebae and calculated a number of widely-used indices: species richness, Simpson diversity, compositional dissimilarity from the largest sample and transfer function predictions of water table depth. We found that there was a trend for larger samples to contain more species across the range of commonly-used sample sizes in ecological studies. Smaller samples sometimes failed to produce counts of testate amoebae often considered minimally adequate. It seems likely that analyses based on samples of different sizes may not produce consistent data. Decisions about sample size need to reflect trade-offs between logistics, data quality, spatial resolution and the disturbance involved in sample extraction. For most common ecological applications we suggest that samples of more than eight Sphagnum stems are likely to be desirable.
The ocean's midwaters (the mesopelagic and bathypelagic zones) make up the largest living space on the planet, but are undersampled and relatively poorly understood. The true distribution of many midwater species, let alone the abiotic factors most important in determining that distribution, is not well known. Because collecting specimens and data from the deep ocean is expensive and logistically difficult, it would be useful to be able to predict where species of interest are likely to occur so that sampling effort can be concentrated in appropriate areas. The distribution of two representative midwater fishes, the gulper eel Eurypharynx pelecanoides and the bobtail eel Cyema atrum (Teleostei: Saccopharyngiformes), were modeled with MaxEnt software to examine the viability of species distribution modeling (SDM) for globally distributed midwater fishes using currently available environmental data from the ocean surface and bottom. These species were chosen because they are relatively abundant, easily recognized, and unlikely to have been misidentified in database records, and are true midwater fishes, not known to undertake significant vertical diurnal migration. Models for both species show a generally worldwide distribution with some exceptions, including the Southern Ocean and Bering Sea. Variable contributions show that surface and bottom environmental variables correlate with species presence. Both species are more likely to be found in areas with low levels of silicate. SDM is a promising method for better understanding the ecology of midwater organisms.
Contemporary factors that affect the health of the population have been analyzed. There was shown the growing activity of chemical pollution of the environment. Therefore, in order to prevent the growth of negative health and environment consequences caused by increased levels of exposure to chemicals preventive potential for solutions of this complex problem and all strenuous efforts to assist possibly of the sound management of the chemicals should be enhanced. Problematic issues of harmonization of the Russian normative and guidance documents have been actualized. Perspective directions of science development in the field of human ecology and environmental health are suggested.
Inclusion of spatially explicit information on ecosystem services in conservation planning is a fairly new practice. This study analyses how the incorporation of ecosystem services as conservation features can affect conservation of forest biodiversity and how different opportunity cost constraints can change spatial priorities for conservation. We created spatially explicit cost-effective conservation scenarios for 59 forest biodiversity features and five ecosystem services in the county of Telemark (Norway) with the help of the heuristic optimisation planning software, Marxan with Zones. We combined a mix of conservation instruments where forestry is either completely (non-use zone) or partially restricted (partial use zone). Opportunity costs were measured in terms of foregone timber harvest, an important provisioning service in Telemark. Including a number of ecosystem services shifted priority conservation sites compared to a case where only biodiversity was considered, and increased the area of both the partial (+36.2%) and the non-use zone (+3.2%). Furthermore, opportunity costs increased (+6.6%), which suggests that ecosystem services may not be a side-benefit of biodiversity conservation in this area. Opportunity cost levels were systematically changed to analyse their effect on spatial conservation priorities. Conservation of biodiversity and ecosystem services trades off against timber harvest. Currently designated nature reserves and landscape protection areas achieve a very low proportion (9.1%) of the conservation targets we set in our scenario, which illustrates the high importance given to timber production at present. A trade-off curve indicated that large marginal increases in conservation target achievement are possible when the budget for conservation is increased. Forty percent of the maximum hypothetical opportunity costs would yield an average conservation target achievement of 79%.
Cites: Nature. 2000 May 11;405(6783):243-5310821285
Birds and other animals are frequently killed by cars, causing the death of many million individuals per year. Why some species are killed more often than others has never been investigated. In this work hypothesized that risk taking behavior may affect the probability of certain kinds of individuals being killed disproportionately often. Furthermore, behavior of individuals on roads, abundance, habitat preferences, breeding sociality, and health status may all potentially affect the risk of being killed on roads. We used information on the abundance of road kills and the abundance in the surrounding environment of 50 species of birds obtained during regular censuses in 2001-2006 in a rural site in Denmark to test these predictions. The frequency of road kills increased linearly with abundance, while the proportion of individuals sitting on the road or flying low across the road only explained little additional variation in frequency of road casualties. After having accounted for abundance, we found that species with a short flight distance and hence taking greater risks when approached by a potential cause of danger were killed disproportionately often. In addition, solitary species, species with a high prevalence of Plasmodium infection, and species with a large bursa of Fabricius for their body size had a high susceptibility to being killed by cars. These findings suggest that a range of different factors indicative of risk-taking behavior, visual acuity and health status cause certain bird species to be susceptible to casualties due to cars.
There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC95%) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC5%) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level.
The rapid decline in Arctic sea ice (ASI) extent, area and volume during recent decades is occurring before we can understand many of the mechanisms through which ASI interacts with biological processes both at sea and on land. As a consequence, our ability to predict and manage the effects of this enormous environmental change is limited, making this a crisis discipline Here, we propose a framework to study these effects, defining direct effects as those acting on life-history events of Arctic biota, and indirect effects, where ASI acts upon biological systems through chains of events, normally involving other components of the physical system and/or biotic interactions. Given the breadth and complexity of ASI's effects on Arctic biota, Arctic research requires a truly multidisciplinary approach to address this issue. In the absence of effective global efforts to tackle anthropogenic global warming, ASI will likely continue to decrease, compromising the conservation of many ASI-related taxonomic groups and ecosystems. Mitigation actions will rely heavily on the knowledge acquired on the mechanisms and components involved with the biological effects of ASI.
Thermal stress, food poisoning, infectious diseases, malnutrition, psychiatric illness as well as injury and death from floods, storms and fire are all likely to become more common as the earth warms and the climate becomes more variable. In contrast, obesity, type II diabetes and coronary artery disease do not result from climate change, but they do share causes with climate change. Burning fossil fuels, for example, is the major source of greenhouse gases, but it also makes pervasive physical inactivity possible. Similarly, modern agriculture's enormous production of livestock contributes substantially to greenhouse gas emissions, and it is the source of many of our most energy-rich foods. Physicians and societies of medical professionals have a particular responsibility, therefore, to contribute to the public discourse about climate change and what to do about it.
ReprintIn: Ugeskr Laeger. 2008 Aug 25;170(35):2667-818761852
The necessity of taking into account the interests of public health care informing and implementing solutions for water management has been substantiated. Scientific frameworks and regulatory sanitary legislative documents relating to various areas of water management have been considered. The possibilities and the importance of performing complex territory medical ecological forecasts of effects of changes in hydrological situation have been demonstrated.
Denmark was considered not to have an established population of free-ranging wild boar. Today, sporadic observations of wild boar challenge that view. Due to its reservoir role for economic devastating swine diseases, wild boar represents a potential threat for Denmark's position as a large pig- and pork-exporting country. This study assessed the prospects of wild boar invasion in Denmark. Multi-source citizen science data of wild boar observations were integrated into a multi-modelling approach linking habitat suitability models with agent-based, spatially-explicit simulations. We tested whether the currently observed presence of wild boar is due to natural immigration across the Danish-German border, or whether it is more likely that wild boar escaped fenced premises. Five observational data sources served as evaluation data: (1) questionnaires sent to all 1625 registered owners of Danish farm land, located in the 60 parishes closest to the border, (2) an online questionnaire, (3) a mobile web-based GPS application, (4) reports in the media or by governmental agencies, and (5) geo-referenced locations of fenced wild boar populations. Data covering 2008-2013 included 195 observations of wild boar, including 16 observations of breeding sows. The data from the Danish Nature Agency and the mailed questionnaires were consistent regarding the location of wild boar observations, while data from the Danish Veterinary and Food Administration, the media and the electronic questionnaires documented individual scattered observations in the rest of Jutland. Most observations were made in the region bordering Germany. It is uncertain whether the relatively few observations represent an established population. Model outcomes suggested that the origin of wild boar in about half of the area with sporadic observations of wild boar could be attributed to spatial expansions from a local Danish population near the border and consisting of wild boar originally of German origin. However, the other half, located distant to the border, were likely a result of animals escaping fenced premises inside the country. The approach serves as a template to assess the status of an invading species and improve the knowledge base for risk assessment and management decision.