Plant blindness and the implications for plant conservation

Plant conservation initiatives lag behind and receive considerably less funding than animal conservation projects. We explored a potential reason for this bias: a tendency among humans to neither notice nor value plants in the environment. Experimental research and surveys have demonstrated higher preference for, superior recall of, and better visual detection of animals compared with plants. This bias has been attributed to perceptual factors such as lack of motion by plants and the tendency of plants to visually blend together but also to cultural factors such as a greater focus on animals in formal biological education. In contrast, ethnographic research reveals that many social groups have strong bonds with plants, including nonhierarchical kinship relationships. We argue that plant blindness is common, but not inevitable. If immersed in a plant‐affiliated culture, the individual will experience language and practices that enhance capacity to detect, recall, and value plants, something less likely to occur in zoocentric societies. Therefore, conservation programs can contribute to reducing this bias. We considered strategies that might reduce this bias and encourage plant conservation behavior. Psychological research demonstrates that people are more likely to support conservation of species that have human‐like characteristics and that support for conservation can be increased by encouraging people to practice empathy and anthropomorphism of nonhuman species. We argue that support for plant conservation may be garnered through strategies that promote identification and empathy with plants.     

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.     

Phosphorus-based metabolic pathway tracers in surface waters

Environmental Science and Pollution Research - Trophic status in surface waters has been mostly monitored by measuring soluble reactive phosphorus (SRP) and total phosphorus (TP). Additional to...     

Probabilistic risk assessment for long-range atmospheric transport of radionuclides

A simplified means of probabilistic risk assessment (PRA) for long-range atmospheric transport based on a K-diffusion model is presented. In a case study, model parameters are estimated by comparing with the results of long-range atmospheric dispersion model calculations using one-year numerical weather prediction model data. It is found that the estimated ensemble mean provides a reasonable first approximation to the total dry and wet deposition from the one-year continuous release.     

Zinc removal from synthetic waters using magnetite/graphene oxide composites

The removal of heavy metals from wastewater has become a global challenge, which demands the continuous study of efficient and low-cost treatment alternatives such as adsorption. In this research, the removal of zinc was evaluated using batch adsorption processes with nonconventional materials such as graphene oxide (GO), magnetite (MG), and their composites (GO:MG), formulated with three weight ratios (2:1, 1:1, and 1:2). Graphene was synthesized by the modified Marcano method, using pencil lead graphite as a precursor. MG and the composites were synthesized by chemical coprecipitation of ferrous sulfate and ferric chloride. The materials were characterized by Raman and Fourier transform infrared spectroscopies, scanning electron microscopy, X-ray diffraction, and the Brunauer–Emmett–Teller method to determine the functional groups, microstructural and morphological characteristics, and specific surface area. Batch adsorption tests were carried out to optimize the adsorbent dose and contact time with zinc solutions of 10 ppm. Zinc adsorption reached equilibrium at 2 h, with an optimal dose between 0.25 and 1.0 g/L. The maximum zinc removal efficiencies/adsorption capacities were 98.6%/165.6, 83.4%/47.6, 83.5%/21.9, 72.8%/19.9, and 82.2%/9.25 mg/g using GO, 2GO:1MG, 1GO:1MG, 1GO:2MG, and MG, respectively. Furthermore, the analysis of the isotherm and adsorption kinetics models determined that the adsorption processes using MG and the composites fit the Sips and pseudo-second-order models.     

Muskox status,recent variation,and uncertain future

Ambio - Muskoxen (Ovibos moschatus) are an integral component of Arctic biodiversity. Given low genetic diversity, their ability to respond to future and rapid Arctic change is unknown, although...