Transcending scale dependence in identifying habitat with resource selection functions

Multi-scale resource selection modeling is used to identify factors that limit species distributions across scales of space and time. This multi-scale nature of habitat suitability complicates the translation of inferences to single, spatial depictions of habitat required for conservation of species. We estimated resource selection functions (RSFs) across three scales for a threatened ungulate, woodland caribou (Rangifer tarandus caribou), with two objectives: (1) to infer the relative effects of two forms of anthropogenic disturbance (forestry and linear features) on woodland caribou distributions at multiple scales and (2) to estimate scale-integrated resource selection functions (SRSFs) that synthesize results across scales for management-oriented habitat suitability mapping. We found a previously undocumented scale-specific switch in woodland caribou response to two forms of anthropogenic disturbance. Caribou avoided forestry cut-blocks at broad scales according to first- and second-order RSFs and avoided linear features at fine scales according to third-order RSFs, corroborating predictions developed according to predator-mediated effects of each disturbance type. Additionally, a single SRSF validated as well as each of three single-scale RSFs when estimating habitat suitability across three different spatial scales of prediction. We demonstrate that a single SRSF can be applied to predict relative habitat suitability at both local and landscape scales in support of critical habitat identification and species recovery.     

Is the Mantel correlogram powerful enough to be useful in ecological analysis? A simulation study

The Mantel correlogram is an elegant way to compute a correlogram for multivariate data. However, recent papers raised concerns about the power of the Mantel test itself. Hence the question: Is the Mantel correlogram powerful enough to be useful? To explore this issue, we compared the performances of the Mantel correlogram to those of other methods, using numerical simulations based on random, normally distributed data. For a single response variable, we compared it to the Moran and Geary correlograms. Type I error rates of the three methods were correct. Power of the Mantel correlogram was nearly as high as that of the univariate methods. For the multivariate case, the test of the multivariate variogram developed in the context of multiscale ordination is in fact a Mantel test, so that the power of the two methods is the same by definition. We devised an alternative permutation test based on the variance, which yielded similar results. Overall, the power of the Mantel test was high, the method successfully detecting spatial correlation at rates similar to the permutation test of the variance statistic in multivariate variograms. We conclude that the Mantel correlogram deserves its place in the ecologist's toolbox.     

Carbon dynamics of forests in Washington, U.S.A.: 21st century projections based on climate-driven changes in fire regimes

During the 21st century, climate-driven changes in fire regimes will be a key agent of change in forests of the U.S. Pacific Northwest (PNW). Understanding the response of forest carbon (C) dynamics to increases in fire will help quantify limits on the contribution of forest C storage to climate change mitigation and prioritize forest types for monitoring C storage and fire management to minimize C loss. In this study, we used projections of 21st century area burned to explore the consequences of changes in fire regimes on C dynamics in forests of Washington State. We used a novel empirical approach that takes advantage of chronosequences of C pools and fluxes and statistical properties of fire regimes to explore the effects of shifting age class distributions on C dynamics. Forests of the western Cascades are projected to be more sensitive to climate-driven increases in fire, and thus projected changes in C dynamics, than forests of the eastern Cascades. In the western Cascades, mean live biomass C is projected to decrease by 24-37%, and coarse woody debris (CWD) biomass C by 15-25% for the 2040s. Loss of live biomass C is projected to be lower for forests of the eastern Cascades and Okanogan Highlands (17-26%), and CWD biomass is projected to increase. Landscape mean net primary productivity is projected to increase in wet low-elevation forests of the western Cascades, but decrease elsewhere. These forests, and moist forests of the Okanogan Highlands, are projected to have the greatest percentage increases in consumption of live biomass. Percentage increases in consumption of CWD biomass are greater than 50% for all regions and up to four times greater than increases in consumption of live biomass. Carbon sequestration in PNW forests will be highly sensitive to increases in fire, suggesting a cautious approach to managing these forests for C sequestration to mitigate anthropogenic CO2 emissions.     

Soft systems thinking and social learning for adaptive management

The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning.     

Nutrient chemistry of River Pinios (Thessalia, Greece)

The impact of human activities with 3-year monitoring on the fluctuation of nutrients along the Pinios River and its tributaries were studied. Their seasonal variations throughout the years 1996-1998 were also presented. High temperatures, from June to August, cause a restriction of the water flow, an enhancement of nutrient concentration with the subsequent increase of eutrophication. High concentrations of nutrients were observed first in winter (wet period), caused by leaching of fertilizers from terrestrial systems after heavy rainfall, later during the warm months due to low water flow of the river, and at last in autumn when plant organisms began to decompose. The intensive algal and macrophyte growth (spring, summer) resulted in severe depletion of nutrients. Organic carbon showed no seasonal trend but its values were high near the estuaries. Nitrate fluxes were high at the initial station (sources) and the Titarisios tributary, whereas nitrites and ammonium were low. In contrary, the Kalentzis tributary with relatively low nitrate values showed increased values of nitrite ammonium or total nitrogen. On the other hand, the Enipeas tributary showed high SO4 values. Phosphates are remarkably present mainly after the city of Larissa, where sewage and industrial discharges occur. None of the nutrients measured in the Pinios River and its tributaries showed a clear seasonal cycle of concentration. Concentrations of nutrients and organic carbon increased as a consequence of anthropogenic inputs, particularly point discharges from sewage treatment plants (i.e. showing distinct, but variable, concentration peaks), as well as diffuse urban and/or agricultural runoff over long areas during storm events. The agricultural management, the urban pollution, mainly from Larissa City, and the climate conditions in the catchment basin (Thessalia Plain) of Pinios River and its tributaries greatly affect the chemical composition of their waters.     

Distribution and temporal trends of butyltins monitored by molluscs along the Chinese Bohai coast from 2002 to 2005

Thirteen areas around the Chinese Bohai coast, individuals including ten kinds of bivalves and two kinds of snails were collected during the period of 2002-2005 for the investigation of spatial distribution and temporal variations of butyltin compounds (BTs). BTs including tributyltin (TBT) and its derivates, dibutyltin (DBT) and monobutyltin (MBT) were quantified by gas chromatography/flame photometric detection after extraction and Grignard derivatization. BTs compounds were widely existed in the samples and TBT was the dominant composition, indicating recent TBT input along Bohai coast. As a whole, BTs concentration remained high during the sampling years except a slightly decreased in samples from several sites in 2005. The contamination characteristics of BTs in different sampling sites were analyzed using principal component analysis (PCA) method, and the species specific bioaccumulation of BTs was also identified using cluster analysis.     

A theoretical approach to indoor radon and thoron distribution

A model based on the Finite Element Method was developed to simulate indoor behavior of radon ((222)Rn), thoron ((220)Rn) and their progeny, as well as, to calculate their spatial distributions. Since complex physical processes govern the distribution several simplifications were made in the presented model. Different locations of possible radon/thoron sources, diffusion of these gases, their radioactive decay, etc were taken into account. Influences of different parameters on thoron/radon as well as indoor distribution of their progeny, such as the geometry and room dimension, the presence of aerosols and their size distribution expressed through the diffusion coefficient, different kinds of ventilation, etc, were investigated. It has been found that radon is distributed homogeneously, while the thoron concentration is rather inhomogeneous and decreases exponentially with the distance from the source. Regardless of the source distribution, the distribution of radon was homogeneous, except at places near an air inlet and outlet. However, the distribution of thoron depends on the source distribution. If thoron emanates from walls or the floor, its concentration decreases with the distance from the wall. Moreover, the concentration gradient is much larger near walls. This suggests that the actual selection of the site effect should be taken into account when obtaining a representative value of indoor (220)Rn and their progeny for dose assessment. The simulation results of activities and their distribution were in accordance with the results of other studies and experiments.     

The use of the shanny Lipophrys pholis for pollution monitoring: a new sentinel species for the northwestern European marine ecosystems

The contamination of aquatic ecosystems by organic contaminants such as polycyclic aromatic hydrocarbons (PAHs) is a matter of great concern. Mussels have been extensively used as sentinel species in a large number of monitoring programs. However, the use of bivalves as the sole species has some limitations, because they are not as responsive as fish to Aryl Hydrocarbon Receptor agonists. Hence, for many marine areas, there is the need to validate new sentinel fish species that can be used in the assessment of pollution by organic contaminants. The shanny Lipophrys pholis is an intertidal fish that combines many characteristics required in a sentinel species: is abundant and easy to catch, has a wide geographical distribution and restrict home range. After larvae recruitment to the intertidal rocky shores, they remain in the same area for the rest of the life-cycle, thus reflecting local pollutants exposure. In order to evaluate the species sensitivity to organic contaminants under field conditions, L. pholis were collected at six sites reflecting different degrees of anthropogenic contamination. The induction of two biomarkers extensively validated in the assessment of PAHs contamination ethoxyresorufin-O-deethylase activity (EROD) and Fluorescent Aromatic Compounds (FACs) was evaluated. In parallel, mussels were collected at the same locations and levels of 16 PAHs and selected heavy metals determined. Overall, the specimens collected in the urban areas showed a significant induction of EROD and FACs (up to a six-fold induction) if compared with the reference sites. Additionally, a positive correlation was observed between the biomarkers and PAHs levels in mussel tissues. Even though further validation is currently in progress, the available data indicate that L. pholis is responsive to organic contaminants such as PAHs, suggesting its future integration in monitoring programmes designed to evaluate the presence of these contaminants in European marine ecosystems.     

Indoor radon distribution in Switzerland: lognormality and Extreme Value Theory

Analysis and modeling of statistical distributions of indoor radon concentration from data valorization to mapping and simulations are critical issues for real decision-making processes. The usual way to model indoor radon concentrations is to assume lognormal distributions of concentrations on a given territory. While these distributions usually model correctly the main body of the data density, they cannot model the extreme values, which are more important for risk assessment. In this paper, global and local indoor radon distributions are modeled using Extreme Value Theory (EVT). Emphasis is put on the tails of the distributions and their deviations from lognormality. The best fits of distributions to real data set density have been computed and goodness of fit with Root Mean Squared Error (RMSE) is evaluated. The results show that EVT performs better than lognormal pdf for real data sets characterized by high indoor radon concentrations.