Predicting inter-taxa differences in plant uptake of cesium-134/137

For (134/137)Cs, and many other soil contaminants, research into transfer to plants has focused on particular crops and phytoremediation candidates, producing uptake data for a small proportion of all plant taxa. Despite the significance of differences in uptake between plant taxa, the capacity of soil-to-plant transfer models to predict them is currently confined to those taxa for which data exist, there being no method to predict uptake by other taxa. We used residual maximum likelihood (REML) analysis on data from experiments (including 89 plant taxa from China plus 32 phytoremediation candidates) together with data from the literature, to construct a database of relative (134/137)Cs concentrations in 273 plant taxa. The REML (134/137)Cs concentrations in plants are not normally distributed but significantly clustered. Analysis of variance (ANOVA), coded with a recent ordinal phylogeny for flowering plants, showed that plant taxa do not behave independently for (134/137)Cs concentration because 42 and 15% of inter-taxa differences are associated with phylogeny above the species and ordinal level, respectively. In general, Eudicots, and especially the Caryophyllales, Asterales, and Brassicales, have high (134/137)Cs concentrations, while the Fabales and Magnoliids, in particular Poales, have low (134/137)Cs concentrations. Plants of the stress-tolerant ruderal (S-R) growth strategy sensu Grime have, in general, high concentrations of Cs, while those of the competitive (C) and generalist (C-S-R) strategies have low concentrations, although these effects are less pronounced than those of phylogeny. Plant phylogeny and growth strategy might thus be used to predict a significant portion of inter-taxa differences in plant uptake of (134/137)Cs.     

The acetochlor registration partnership surface water monitoring program for four corn herbicides

A surface drinking water monitoring program for four corn (Zea mays L.) herbicides was conducted during 1995-2001. Stratified random sampling was used to select 175 community water systems (CWSs) within a 12-state area, with an emphasis on the most vulnerable sites, based on corn intensity and watershed size. Finished drinking water was monitored at all sites, and raw water was monitored at many sites using activated carbon, which was shown capable of removing herbicides and their degradates from drinking water. Samples were collected biweekly from mid-March through the end of August, and twice during the off-season. The analytical method had a detection limit of 0.05 microg L(-1) for alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide] and 0.03 microg L(-1) for acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide]. Of the 16528 drinking water samples analyzed, acetochlor, alachlor, atrazine, and metolachlor were detected in 19, 7, 87, and 53% of the samples, respectively. During 1999-2001, samples were also analyzed for the presence of six major degradates of the chloroacetanilide herbicides, which were detected more frequently than their parent compounds, despite having higher detection limits of 0.1 to 0.2 microg L(-1). Overall detection frequencies were correlated with product use and environmental fate characteristics. Reservoirs were particularly vulnerable to atrazine, which exceeded its 3 microg L(-1) maximum contaminant level at 25 such sites during 1995-1999. Acetochlor annualized mean concentrations (AMCs) did not exceed its mitigation trigger (2 microg L(-1)) at any site, and comparisons of observed levels with standard measures of human and ecological hazards indicate that it poses no significant risk to human health or the environment.     

Projected twenty-first-century changes in the Central American mid-summer drought using statistically downscaled climate projections

Regional Environmental Change - In addition to periodic long-term drought, much of Central America experiences a rainy season with two peaks separated by a dry period of weeks to over a month in...     

Novel mesoporous microspheres of Al and Ni doped LMO spinels and their performance as cathodes in secondary lithium ion batteries

A facile, scalable, and solution-based technique is used to fabricate Al and Ni-doped (LiAl_0.1Mn_1.9O₄ and LiAl_0.1Ni_0.1Mn_1.8O₄) microspheres of lithium manganese oxide (LMO) spinels for use as reversible cathode materials for lithium ion batteries (LIBs). The spheres of the two samples exhibit different porosities. Cells with these LMO-based cathodes are then cycled between 4.5 V and 2 V to study their stabilities while simultaneously being subjected to the undesirable Jahn-Teller distortion that occurs around the ~3 V regime. The LiAl_0.1Mn_1.9O₄ (LAMO) and the LiAl_0.1Ni_0.1Mn_1.8O₄ (LANMO) cells exhibit comparable open circuit voltages (OCV) of 2.94 V and 2.97 V, respectively. During cell cycling, the LAMO cell exhibits a maximum specific capacity of 122.51 mAh g^?1 with a capacity fade of 65.35% after 75 cycles. The LiAl_0.1Ni_0.1Mn_1.8O₄ (LAMO) sample fares better and exhibits a maximum of 140.49 mAh g^?1 and a capacity drop of 52.59%. Detailed structural studies indicate that Ni doping and the greater degree of porosity of the LANMO sample to be a stabilizing factor. This is further confirmed by cyclic voltammetry (CV) and AC impedance spectra analysis.     

Examining adaptations to water stress among farming households in Sri Lanka’s dry zone

Climate change is increasing water scarcity in Sri Lanka. Whether these changes will undermine national-level food security depends upon the ability of the small-scale farmers that dominate rice production and the institutions that support them to overcome the challenges presented by changing water availability. Analyzing household survey data, this research identifies household, institutional, and agroecological factors that influence how water-stressed farmers are working to adapt to changing conditions and how the strategies they employ impact rice yields. Paralleling studies conducted elsewhere, we identified institutional factors as particularly relevant in farmer adaptation decisions. Notably, our research identified farmers’ use of hybrid seed varietals as the only local climate adaptation strategy to positively correlate with farmers’ rice yields. These findings provide insight into additional factors pertinent to successful agricultural adaptation and offer encouraging evidence for policies that promote plant breeding and distribution in Sri Lanka as a means to buffer the food system to climate change-exacerbated drought.     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Estimating abundance without recaptures of marked pallid sturgeon in the Mississippi River

Abundance estimates are essential for assessing the viability of populations and the risks posed by alternative management actions. An effort to estimate abundance via a repeated mark‐recapture experiment may fail to recapture marked individuals. We devised a method for obtaining lower bounds on abundance in the absence of recaptures for both panmictic and spatially structured populations. The method assumes few enough recaptures were expected to be missed by random chance. The upper Bayesian credible limit on expected recaptures allows probabilistic statements about the minimum number of individuals present in the population. We applied this method to data from a 12‐year survey of pallid sturgeon (Scaphirhynchus albus) in the lower and middle Mississippi River (U.S.A.). None of the 241 individuals marked was recaptured in the survey. After accounting for survival and movement, our model‐averaged estimate of the total abundance of pallid sturgeon ≥3 years old in the study area had a 1%, 5%, or 25% chance of being <4,600, 7,000, or 15,000, respectively. When we assumed fish were distributed in proportion to survey catch per unit effort, the farthest downstream reach in the survey hosted at least 4.5–15 fish per river kilometer (rkm), whereas the remainder of the reaches in the lower and middle Mississippi River hosted at least 2.6–8.5 fish/rkm for all model variations examined. The lower Mississippi River had an average density of pallid sturgeon ≥3 years old of at least 3.0–9.8 fish/rkm. The choice of Bayesian prior was the largest source of uncertainty we considered but did not alter the order of magnitude of lower bounds. Nil‐recapture estimates of abundance are highly uncertain and require careful communication but can deliver insights from experiments that might otherwise be considered a failure.