Assessing the long-term supply risks for mineral raw materials—a combined evaluation of past and future trends

This paper develops a method for identifying and assessing long-term supply risks for mineral raw materials. The method is based on a combined evaluation of past and future supply and demand trends. By analysing raw material boom and bust cycles over the past 50 years, we have quantified indicators and defined benchmarks for identifying critical market situations. By applying the method, risks for supply shortage may be identified at an early stage. In addition, a numerical evaluation model has been developed for better comparison between various mineral raw materials. Compared to other assessment methods this method uses specific benchmarks for each raw material to better assess supply risks. The method is embedded within a systematic and comprehensive analytical approach.     

Organophosphorus flame retardants and plasticizers in the atmosphere of the North Sea

Air samples collected in the German part of the North Sea from March to July 2010 were investigated for organophosphorus compounds (OPs) being applied as flame retardants and plasticizers. The ∑₈OPs concentration ranged from 110 to 1400 pg m⁻³ while tris(2-chloroisopropyl) phosphate (TCPP) dominated all samples with individual concentrations up to 1200 pg m⁻³. The highest concentrations were observed in continental air masses showing the high influence of industrialized regions including production sites on atmospheric emissions and concentrations. The occurrence of OPs even in oceanic/Arctic air masses shows that OPs can undergo long-range atmospheric transport. Dry particle-bound deposition fluxes from 9 to 240 ng m⁻² d⁻¹ for ∑₈OPs were estimated leading to a minimum annual flux of 710 ± 580 kg y⁻¹ OPs into the German North Sea. This study presents the first occurrence of OPs in the marine atmosphere together with important information on their long-range transport potential.     

Levels and distribution of Dechlorane Plus in coastal sediments of the Yellow Sea, North China

Dechlorane Plus (DP) has been determined in surface sediments from three Chinese coastal bays, e.g. Jiaozhou, Sishili and Taozi Bay in North China. DP concentrations ranged from <1.2 to 187 pg g⁻¹ dry weight (dw) (mean: 24.7 pg g⁻¹ dw) in Jiaozhou Bay, <1.2 to 135 pg g⁻¹ dw (mean 69.9 pg g⁻¹ dw) in Sishili Bay and <1.2 to 66.7 pg g⁻¹ dw (mean: 40.4 pg g⁻¹ dw) in Taozi Bay, respectively. Additionally, two dechlorinated species were quantified, which accounted for 0.6-5.1% of the ∑DP concentration.The f_syn values (syn-isomer/(syn- + anti-isomer)) in sediments from Jiaozhou Bay (mean 0.29) were close to the technical DP mixture (0.2-0.4), probably indicating local inputs of DP. In contrast, sediments in Sishili and Taozi Bay showed much lower f_syn values (mean 0.16). During transportation the DP isomers are subject to stereo selective degradation which partly resulted in the relative enrichment of anti-DP in coastal sediments.     

Modeling kelp forest distribution and biomass along temperate rocky coastlines

We address the global deficit of data describing kelp forest distribution, relative covers and biomass by testing the ability of species distribution models to predict these attributes at locations where data are currently limited. We integrated biological ground truth data with high-resolution environmental datasets to develop generalized additive models that accurately predict the structure of Laminaria forests within the Bay of Morlaix (48°42′42″N, 3°55′40″W). Forest distribution and proportional covers were predicted using water depth, light availability, wave exposure and sediment dynamics. The biomass of individual kelp species was modeled by supplementing these same variables with measures of seafloor slope and benthic position. Biomass predictions for Laminaria digitata and Laminaria hyperborea contrast the physiological tolerances of these species to light and wave exposure gradients. As a direct management output, we produced high-resolution maps (25 m² grids) that closely match independent field data and provide vital information for marine spatial planning.     

Lower thermal capacity limits of the common brown shrimp (Crangon crangon,L.)

Brown shrimp (Crangon crangon, L.) are subjected to a huge annual temperature range, and certain thermal conditions during winter have been identified to affect the brown shrimp population. Despite that, little is known about its thermal biology with regard to critically low temperatures. In the present study, we determined the critical thermal minima (CT_min) and the critical lethal minima (CL_min) of male and female brown shrimp of different body sizes in laboratory-based experiments. For the CT_min trials, shrimp were acclimated to 4.0, 9.0, and 14.0 °C and exposed to a cooling rate of ?0.2 °C min^?1. In the CL_min trials, brown shrimp were exposed to a cooling rate of ?1.0 °C day^?1 without prior thermal acclimation. Acclimation temperature significantly affected the temperature tolerance of brown shrimp (p < 0.001). CT_min among the experimental groups just varied slightly, and no clear effect of gender or body size was observed. In the CL_min trials, brown shrimp even tolerated the coldest temperature of ?1.7 °C that could be established in the experimental setup. However, we observed a negative relationship between temperature and reactivity within the range of 7.0 and 1.0 °C that was determined by means of the flicking response. This relationship suddenly broke between 1.0 and 0.0 °C where an abrupt drop in the reactivity of the shrimp became apparent. The results of this study revealed that brown shrimp hold a wider thermal range as originally reported and that it can cope with subzero temperatures. Implications of low-temperature tolerance are discussed in the context of the brown shrimp’s ecology as well as stock assessment.     

Review of International Investment and Climate Change: Energy Technologies for Developing Countries by T. Forsyth

Mitigation and Adaptation Strategies for Global Change -     

Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

Using thermal units for estimating critical period of weed competition in off-season maize crop

Brazilian off-season maize production is characterized by low yield due to several factors, such as climate variability and inadequate management practices, specifically weed management. Thus, the goal of this study was to determinate the critical period of weed competition in off-season maize (Zea mays L.) crop using thermal units or growing degree days (GDD) approach to characterize crop growth and development. The study was carried out in experimental area of the University of S?o Paulo, Brazil, with weed control (C), as well as seven coexistence periods, 2, 4, 6, 8, and 12 leaves, flowering, and all crop cycle; fourteen treatments were done. Climate data were obtained from a weather station located close to the experimental area. To determine the critical period for weed control (CPWC) logistic models were fitted to yield data obtained in both W and C, as a function of GDD. For an arbitrary maximum yield loss fixed in 2.5%, the CPWC was found between 301 and 484 GDD (7-8 leaves). Also, when the arbitrary loss yield was fixed in 5 and 10%, the period before interference (PBI) was higher than the critical weed-free period (CWFP), suggesting that the weeds control can be done with only one application, between 144 and 410 GDD and 131 and 444 GDD (3-8 leaves), respectively. The GDD approach to characterize crop growth and development was successfully used to determine the critical period of weeds control in maize sown off-season. Further works will be necessary to better characterize the interaction and complexity of maize sown off-season with weeds. However, these results are encouraging because the possibility of the results to be extrapolated and because the potential of the method on providing important results to researchers, specifically crop modelers.