Biophysical suitability,economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R ² = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R ² = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage.     

ASsessment Of Alcohol Ethoxylate Surfactants And Fatty Alcohols Mixtures In River Sediments And Prospective Risk Assessment

A feasible and relatively readily available analytical method was adapted for the assessment of alcohol ethoxylates (AE) and fatty alcohols (FA) in sediments. This study illustrates the simultaneous measurement of 38 of 114 possible alcohol ethoxylate ethoxymers (AE) and fatty alcohols (FA) found in commercially important AE products. We predicted toxicity for all identified fractions, as well as the total mixture toxicity, relative to three exposure scenarios via sewage treatment plants (STP) for these widely used chemicals in consumer products and hence generate a preliminary environmental risk screening for AE and FA in sediments. The method is based on derivatization of solvent or solid-phase extracts with 2-fluoro-N-methylpyridinium p-toluenesulfonate (Pyr+). The derivatized extracts were analyzed with liquid chromatography/mass spectrometry (LC/MS) operating in the positive ion electrospray mode. The extraction efficiency of AE and FA in three different sediments of varying composition was evaluated with spike-recovery studies, ranging from 64% to 80%. The detection limits for individual ethoxymers typically ranged from 1 to 5ngg⁻¹on a dry weight basis. The mean limit of detection (LOD) was 6ngg⁻¹and the median LOD was 3ngg⁻¹. AE and FA in sediments were found to be stable for two weeks if preserved with 3% (v/v) formalin and stored at 4–6^∘C. Based on equilibrium partitioning, background concentrations of AE and FA were predicted to be below concentrations known to elicit chronically toxic effects. Total worst case mixture toxicities for all AE ethoxymers combined with FA were predicted to result in a risk quotient less than 0.6. Activated sludge treatment (STP) significantly reduced the release of total AE and FA by four-fold, suggesting that the total mixture risk quotient would be < 0.15 for sediment dependent organisms.     

Mechanical Property and Biodegradability of Cast Films Prepared from Blends of Oppositely Charged Biopolymers

Biodegradable cast films of about 50 m thickness were fabricated by blending oppositely charged biopolymers such as anionic starch–chitosan, and cationic starch–pectin. The tensile strength and elongation at break (%) of films were evaluated as well as their capacity to degrade in compost. Films recovered from soil every 48 h showed consistent degradation (weight loss), diminution of the polymers characteristic peak absorbance in the carbohydrate fingerprint region of the FTIR, and changes in the surface morphology via scanning electron microscopy (SEM). Anionic starch–chitosan films had much superior tensile strength and elongation compared to cationic starch–pectin, suggesting that the ionic bonds formed between anionic-starch and positively charged groups in chitosan polymer were much more stable and stronger. Initially, both films lost about 36% weight within 96 h, which also correlated well with the loss in the characteristic absorption peaks in the region of the infrared spectrum typical of biopolymers. The total mineralization of films by microorganisms in compost soil was also measured using respirometric techniques. Though the rate of mineralization differed for two formulations, total mineralization (extent) for both films were achieved within 45 days.     

Outsourcing sustainability: a game-theoretic modeling approach

As a response to stakeholders’ interest in sustainable products and services, an organization may change its approach to sustainability issues, from isolated social and environmental projects to corporate sustainability strategies and practices that are part of their core business. However, many of the efforts associated with these sustainability strategies cannot be directly exerted by focal organizations. We consider the situation in which a focal organization (sustainability buyer) outsources sustainability efforts to another organization (sustainability seller). While buyers cannot directly exert sustainability efforts, they can provide economic or technical support to their sellers in order to incentivize these efforts. We investigate how the effort and support decisions change according to characteristics of stakeholders, buyers, and sellers. Additionally, the presence of sustainability-minded stakeholders may lead to buyers’ competition on the sustainability effort exerted by their sellers. Therefore, we extend our analysis of sustainability efforts and incentives to the case of two competing buyers, and we determine conditions under which sharing a seller is preferred by the buyers to having a separate seller for each buyer.     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.