Identifying socioeconomic and biophysical factors driving forest loss in protected areas

Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.     

An abbreviated alternatives assessment process for product designers: a children’s furniture manufacturing case study

Alternatives assessment is becoming increasingly popular to evaluate the potential environmental and human health hazards of materials. A three step process was used to identify and evaluate alternative products for a children's furniture manufacturer. An alternatives assessment framework was developed to analyze alternative mattresses. The framework specifically addresses those environmental and safety attributes applicable to the product and the product components in accordance with the product’s intended use. The result of the assessment allowed the manufacturer to select the most environmentally friendly alternative and eliminate polyvinyl chloride from their product.     

Assessing the ecological effects of human impacts on coral reefs in Bocas del Toro,Panama

Environmental and biological reef monitoring was conducted in Almirante Bay (Bahía Almirante) in Bocas del Toro, Panama, to assess impacts from anthropogenic developments. An integrated monitoring investigated how seasonal temperature stress, turbidity, eutrophication and physical impacts threatened reef health and biodiversity throughout the region. Environmental parameters such as total suspended solids [TSS], carbon isotopes (δ¹³C), C/N ratios, chlorophyll a, irradiance, secchi depth, size fractions of the sediments and isotope composition of dissolved inorganic carbon [DIC] of the water were measured throughout the years 2010 and 2011 and were analysed in order to identify different impact sources. Compared to data from Collin et al. (Smithsonian Contributions to the Marine Sciences 38:324–334, 2009) chlorophyll a has doubled at sites close to the city and the port Almirante (from 0.46–0.49 to 0.78–0.97 μg l^?1) and suspension load increased, visible by a decrease in secchi depth values. Visibility decreased from 9-13 m down to 4 m at the bay inlet Boca del Drago, which is strongly exposed to river run off and dredging for the shipping traffic. Eutrophication and turbidity levels seemed to be the determining factor for the loss of hard coral diversity, most significant at chlorophyll a levels higher than 0.5 μg l^?1 and TSS levels higher than 4.7 mg l^?1. Hard coral cover within the bay has also declined, at some sites down to <10 % with extremely low diversities (7 hard coral species). The hard coral species Porites furcata dominated the reefs in highly impacted areas and showed a strong recovery after bleaching and a higher tolerance to turbidity and eutrophication compared to other hard coral species in the bay. Serious overfishing was detected in the region by a lack of adult and carnivorous fish species, such as grunts, snappers and groupers. Study sites less impacted by anthropogenic activities and/or those with local protection showed a higher hard coral cover and fish abundance; however, an overall loss of hard coral diversity was observed.     

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.     

Blowing policy bubbles: rethinking emissions targets and low-carbon energy policies in the U.K.

The issue of proportionality is central to climate policy debates about setting targets for the reduction of greenhouse gas emissions and the development of low-carbon energy. In effect, these debates centre on whether the perceived social costs outweigh the benefits of policies and, if not, whether this may lead to over-investment or ‘policy bubbles’. Political attention, agenda setting and policy image are all crucial drivers of ambitious policy formation, as seen in the case of the United Kingdom's (U.K.) Climate Change Act (2008). However, as political salience waned and economic depression dragged on, the cost of long-term climate targets has been reconsidered. Based on documentary analysis and 33 interviews with central political actors, this article presents a detailed account of how economic arguments have been used to reinterpret and challenge policies, using the heuristics of ‘over-investment’ and ‘policy bubbles’. Ultimately, arguments about proportionality hinge on which costs and benefits are considered. In the U.K., economic and technical framings are typically prioritised, but they do not explain contradictory and politically motivated policy decisions. We discuss these dynamics within the context of maturing renewable energy technologies, high energy prices and the U.K.’s cross-party consensus approach to climate politics.     

Analysis of a Farquhar-von Caemmerer-Berry leaf-level photosynthetic rate model for Populus tremuloides in the context of modeling and measurement limitations

The balance of mechanistic detail with mathematical simplicity contributes to the broad use of the Farquhar, von Caemmerer and Berry (FvCB) photosynthetic rate model. Here the FvCB model was coupled with a stomatal conductance model to form an [A,g_s] model, and parameterized for mature Populus tremuloides leaves under varying CO₂ and temperature levels. Data were selected to be within typical forest light, CO₂ and temperature ranges, reducing artifacts associated with data collected at extreme values. The error between model-predicted photosynthetic rate (A) and A data was measured in three ways and found to be up to three times greater for each of two independent data sets than for a base-line evaluation using parameterization data. The evaluation methods used here apply to comparisons of model validation results among data sets varying in number and distribution of data, as well as to performance comparisons of [A,g_s] models differing in internal-process components.