Evaluating the causal basis of ecological success within the scleractinia: an integral projection model approach

Many tropical corals have declined in abundance in the last few decades, and evaluating the causal basis of these losses is critical to understanding how coral reefs will change in response to ongoing environmental challenges. Motivated by the likelihood that marine environments will become increasingly unfavorable for coral growth as they warm and become more acidic (i.e., ocean acidification), it is reasonable to evaluate whether specific phenotypic traits of the coral holobiont are associated with ecological success (or failure) under varying environmental conditions including those that are adverse to survival. Initially, we asked whether it was possible to identify corals that are resistant or sensitive to such conditions by compiling quantitative measures of their phenotypic traits determined through empirical studies, but we found only weak phenotypic discrimination between ecological winners and losers, or among taxa. To reconcile this outcome with ecological evidence demonstrating that coral taxa are functionally unequal, we looked beyond the notion that phenotypic homogeneity arose through limitations of empirical data. Instead, we examined the validity of contemporary means of categorizing corals based on ecological success. As an alternative means to distinguish among functional groups of corals, we present a demographic approach using integral projection models (IPMs) that link organismal performance to demographic outcomes, such as the rates of population growth and responses to environmental stress. We describe how IPMs can be applied to corals so that future research can evaluate within a quantitative framework the extent to which changes in physiological performance influence the demographic underpinnings of ecological performance.     

Distribution and partitioning of iron, zinc, and arsenic in surface sediments in the Grande River mouth to Cuitzeo Lake, Mexico

Cuitzeo Lake is one of the largest and most important lakes in Mexico. It receives different types of pollutants through its main tributary, the Grande River of Morelia. The aim of this work was to determine if high concentrations of iron, zinc, and arsenic are present in sediments in an area near the river mouth to the lake, as well as to estimate the partitioning of these metals using a sequential extraction procedure in order to obtain information of their potential bioavailability. Sediment samples were collected from three different sites in Cuitzeo Lake and two sites in Grande River in both dry and wet seasons. A sequential extraction procedure was carried out to determine the concentrations of these elements in different geochemical phases of the sediments. Total metal concentrations were evaluated by using the enrichment factor and the geoaccumulation index. A comparison with sediment quality guidelines and shale values has also been made. The results indicate that sediments are considered unpolluted by iron and moderately polluted by zinc and arsenic. However, fractionation studies showed that significant amounts of Zn and As could be released to the lake ecosystem depending on the environmental conditions, representing a medium risk potential of bioavailability to the biota.     

Synthesizing habitat connectivity analyses of a globally important human-dominated tiger-conservation landscape

As ecological data and associated analyses become more widely available, synthesizing results for effective communication with stakeholders is essential. In the case of wildlife corridors, managers in human-dominated landscapes need to identify both the locations of corridors and multiple stakeholders for effective oversight. We synthesized five independent studies of tiger (Panthera tigris) connectivity in central India, a global priority landscape for tiger conservation, to quantify agreement on landscape permeability for tiger movement and potential movement pathways. We used the latter analysis to identify connectivity areas on which studies agreed and stakeholders associated with these areas to determine relevant participants in corridor management. Three or more of the five studies’ resistance layers agreed in 63% of the study area. Areas in which all studies agree on resistance were of primarily low (66%, e.g., forest) and high (24%, e.g., urban) resistance. Agreement was lower in intermediate resistance areas (e.g., agriculture). Despite these differences, the studies largely agreed on areas with high levels of potential movement: >40% of high average (top 20%) current-flow pixels were also in the top 20% of current-flow agreement pixels (measured by low variation), indicating consensus connectivity areas (CCAs) as conservation priorities. Roughly 70% of the CCAs fell within village administrative boundaries, and 100% overlapped forest department management boundaries, suggesting that people live and use forests within these priority areas. Over 16% of total CCAs’ area was within 1 km of linear infrastructure (437 road, 170 railway, 179 transmission line, and 339 canal crossings; 105 mines within 1 km of CCAs). In 2019, 78% of forest land diversions for infrastructure and mining in Madhya Pradesh (which comprises most of the study region) took place in districts with CCAs. Acute competition for land in this landscape with globally important wildlife corridors calls for an effective comanagement strategy involving local communities, forest departments, and infrastructure planners.     

Non-Thermal Effect of Microwave Radiation on Human Brain

Summary This study focuses on an origin of interaction mechanism of microwave radiation with nervous system—quasi-thermal field effect. The microwave field can cause fluctuations and vibration of the charged particles and membranes in tissues. The hypothesis is, that this phenomenon is similar to the effect caused by Brown motion initiated by temperature and results in the same effects without rise in temperature. The electric field of 1 V/cm can introduce disturbance of the thermal equilibrium inside a cell of 10 μm radius, which is equivalent to disturbance produced by temperature rise of 1 K. The hypothesis, that microwave heating should cause an effect independent of the microwave modulation frequency, while field effect depends on modulation frequency, was examined experimentally. The 450 MHz microwave radiation, modulated at 7, 14 and 21 Hz frequencies, power density at the skin 0.16 mW/cm², was applied. The experimental protocol consisted of two series of five cycles of the repetitive microwave exposure at fixed modulation frequencies. Relative changes in EEG theta, alpha and beta rhythms of the group of 13 healthy volunteers were analysed. Analysis of the experimental data shows that: (1) statistically significant changes in EEG rhythms depend on modulation frequency of the microwave field; (2) microwave stimulation causes an increase of the EEG energy level; (3) the effect is most intense at beta1 rhythm and higher modulation frequencies. These findings confirm the quasi-thermal origin of the effect, different from average heating.     

Predicting phosphorus losses with the PLEASE model on a local scale in Denmark and the Netherlands

To reduce losses from agricultural soils to surface water, mitigation options have to be implemented as a local scale. For a cost-effective implementation of these measures, an instrument to identify critical areas for P leaching is indispensable. In many countries, P-index methods are used to identify areas as risk for P losses to surface water. In flat areas, where losses by leaching are dominant, these methods have their limitations because leaching is often not described in detail, PLEASE, is a simple mechanistic model designed to stimulate P Losses by leaching at the field scale using a limited amount of local field data. In this study, PLEASE, was applied to 17 lowland sites in Denmark and 14 lowland sites in the Netherlands. Results show that the simple model simulated measured fluxes and concentrations in water from pipe drains, suction cups, and groundwater quite well. The modeling efficiency ranged from 0.92 for modeling total-P fluxes to 0.36 fr modeling concentrations in groundwater. Poor results were obtained for heavy clay soils and eutrophic peat soils, where fluxes and concentration were strongly underestimated by the model. The poot performance for the heavy clay soil can be explained by the transport of P through macropores to the drain pipes and the underestimation of overland flow on this heavy-textured soil. In the eutrophic peat soils, fluxes were underestimated due to the release of P from deep soil layers.