Refining the ecological footprint

Ecological footprint measures how much of the biosphere’s annual regenerative capacity is required to renew the natural resources used by a defined population in a given year. Ecological footprint analysis (EFA) compares the footprint with biocapacity. When a population’s footprint is greater than biocapacity it is reported to be engaging in ecological overshoot. Recent estimates show that humanity’s footprint exceeds Earth’s biocapacity by 23%. Despite increasing popularity of EFA, definitional, theoretical, and methodological issues hinder more widespread scientific acceptance and use in policy settings. Of particular concern is how EFA is defined and what it actually measures, exclusion of open oceans and less productive lands from biocapacity accounts, failure to allocate space for other species, use of agricultural productivity potential as the basis for equivalence factors (EQF), how the global carbon budget is allocated, and failure to capture unsustainable use of aquatic or terrestrial ecosystems. This article clarifies the definition of EFA and proposes several methodological and theoretical refinements. Our new approach includes the entire surface of the Earth in biocapacity, allocates space for other species, changes the basis of EQF to net primary productivity (NPP), reallocates the carbon budget, and reports carbon sequestration biocapacity. We apply the new approach to footprint accounts for 138 countries and compare our results with output from the standard model. We find humanity’s global footprint and ecological overshoot to be substantially greater, and suggest the new approach is an important step toward making EFA a more accurate and meaningful sustainability assessment tool.

Impact of proposed changes in IESTI equations for short-term dietary exposure to pesticides from Australian and Codex perspective

ABSTRACT

In 2015 a scientific workshop was held in Geneva, where updating the four equations for estimating the short-term dietary exposure (International Estimated Short Term Intake, IESTI) to pesticides was suggested. The impact of these proposed changes on the exposure was studied by using residue data and large portion consumption data from Codex and Australia. For the Codex data, the exposure increased by a median factor of 2.5 per commodity when changing to the proposed IESTI equations. The increase in exposure was highest for bulked and blended food commodities (case 3 equations), followed by medium-sized food commodities (case 2a equations) and small- and large-sized food commodities (case 1 and case 2b equations). For the Australian data, out of 184 maximum residue limit (MRL) large portion combinations showing acute exposures below the acute reference dose (ARfD) with the current IESTI equations, 23 exceeded the ARfD with the proposed IESTI equations (12%). The percentage exceeding the ARfD was higher for the Australian MRL large portion combinations (12% of 184) than for those of Codex (1.3% of 8,366). However, the percentage MRL loss in the Australian dataset may not be representative of all pesticide MRLs since it concerns six pesticides only, specifically selected to elucidate the potential effects of the use of the proposed IESTI equations. For the Codex data, the increase in exposure using the proposed equations resulted in a small increased loss of 2.6% of the 1,110 MRLs estimated by the Joint FAO/WHO Meeting on Pesticide Residues (JMPR): 1.4% of the MRLs were already not acceptable with the current equations, 4.0% of the MRLs were not acceptable with the newly proposed equations. Our study revealed that case 3 commodities may be impacted more by the proposed changes than other commodities. This substantiates one of the conclusions of the Geneva workshop to gather information on bulking and blending practices in order to refine MRL setting and dietary risk assessment for case 3 commodities where possible.     

Feasibility of detection and quantification of gas-phase carbonyls in indoor environments using PFBHA derivatization and solid-phase microextraction (SPME)

Solid-phase microextraction (SPME) was evaluated for the detection and quantification of the gas-phase carbonyls: citronellal, glyoxal, methylglyoxal, and beta-ionone. Prepared air samples containing the carbonyl compounds were collected at a flow rate of 2.8 L min(-1) in an impinger containing a 25% reagent water/75% methanol collection liquid. The aqueous samples were then derivatized with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA), extracted with a PDMS/DVB coated SPME fiber, and analyzed by GC-MS. Detection limits with a sample air volume of 76 L were calculated to be 0.03 ppbv, 0.34 ppbv, 0.12 ppbv, and 0.28 ppbv for citronellal, glyoxal, methylglyoxal, and beta-ionone, respectively.     

Regional assessment of herbicide sorption and degradation in two sampling years

Sorption and degradation of the herbicide 2,4-D [2,4-dichlorophenoxyacetic acid] were determined for 123 surface soils (0 to 15 cm) collected in 2002 and in 2004 between 49 degrees to 60 degrees north longitude and 110 degrees to 120 degrees west latitude in Alberta, Canada. The soils were characterized by soil organic carbon content (SOC), pH, electrical conductivity, soil texture, cation exchange capacity, carbonate content, and total soil microbial activity. The 2,4-D sorption coefficients, Kd and Koc, were highly variable with coefficients of variation of 89 and 59%, respectively, at the provincial scale. Both Kd and Koc were well described by regression models with SOC and soil pH as variables, regardless of scale. Surprisingly, variations in 2,4-D mineralization were much smaller than variations in sorption. Variability in total 2,4-D mineralization was particularly low, with a coefficient of variation of only 7% at the provincial scale. Average 2,4-D half-lives in ecoregions ranged from 1.7 to 3.5 d, much lower than the field dissipation half-life of 10 d reported for 2,4-D in general pesticide property databases. Regression models describing degradation parameters were generally poor or not significant because 2,4-D mineralization was only weakly associated with measured 2,4-D sorption parameters and soil properties. As such, regional variations in herbicide sorption coefficients should be measured or calculated based on soil properties, to assign distinct pesticide fate model input parameters when estimating 2,4-D off-site transport at the provincial scale. Spatial variations in herbicide degradation appear less important for Alberta as 2,4-D half-lives were similar in soils across the province. The rapid mineralization of 2,4-D is noteworthy because 2,4-D is widely used in Alberta and perhaps adaptation of soil microbial communities allowed for accelerated degradation regardless of soil properties or the extent of 2,4-D sorption by soil.     

Atrazine dissipation in s-triazine-adapted and nonadapted soil from Colorado and Mississippi: implications of enhanced degradation on atrazine fate and transport parameters

Soil bacteria have developed novel metabolic abilities resulting in enhanced atrazine degradation. Consequently, there is a need to evaluate the effects of enhanced degradation on parameters used to model atrazine fate and transport. The objectives of this study were (i) to screen Colorado (CO) and Mississippi (MS) atrazine-adapted and non-adapted soil for genes that code for enzymes able to rapidly catabolize atrazine and (ii) to compare atrazine persistence, Q(10), beta, and metabolite profiles between adapted and non-adapted soils. The atzABC and/or trzN genes were detected only in adapted soil. Atrazine's average half-life in adapted soil was 10-fold lower than that of the non-adapted soil and 18-fold lower than the USEPA estimate of 3 to 4 mo. Q(10) was greater in adapted soil. No difference in beta was observed between soils. The accumulation and persistence of mono-N-dealkylated metabolites was lower in adapted soil; conversely, under suboptimal moisture levels in CO adapted soil, hydroxyatrazine concentrations exceeded 30% of the parent compounds' initial mass. Results indicate that (i) enhanced atrazine degradation and atzABC and/or trzN genes are likely widespread across the Western and Southern corn-growing regions of the USA; (ii) persistence of atrazine and its mono-N-dealkylated metabolites is significantly reduced in adapted soil; (iii) hydroxyatrazine can be a major degradation product in adapted soil; and (iv) fate, transport, and risk assessment models that assume historic atrazine degradation pathways and persistence estimates will likely overpredict the compounds' transport potential in adapted soil.     

Pesticides in rain in four agricultural watersheds in the United States

Rainfall samples were collected during the 2003 and 2004 growing seasons at four agricultural locales across the USA in Maryland, Indiana, Nebraska, and California. The samples were analyzed for 21 insecticides, 18 herbicides, three fungicides, and 40 pesticide degradates. Data from all sites combined show that 7 of the 10 most frequently detected pesticides were herbicides, with atrazine (70%) and metolachlor (83%) detected at every site. Dacthal, acetochlor, simazine, alachlor, and pendimethalin were detected in more than 50% of the samples. Chlorpyrifos, carbaryl, and diazinon were the only insecticides among the 10 most frequently detected compounds. Of the remaining pesticide parent compounds, 18 were detected in fewer than 30% of the samples, and 13 were not detected. The most frequently detected degradates were deethylatrazine; the oxygen analogs (OAs) of the organophosphorus insecticides chlorpyrifos, diazinon, and malathion; and 1-napthol (degradate of carbaryl). Deethylatrazine was detected in nearly 70% of the samples collected in Maryland, Indiana, and Nebraska but was detected only once in California. The OAs of chlorpyrifos and diazinon were detected primarily in California. Degradates of the acetanilide herbicides were rarely detected in rain, indicating that they are not formed in the atmosphere or readily volatilized from soils. Herbicides accounted for 91 to 98% of the total pesticide mass deposited by rain except in California, where insecticides accounted for 61% in 2004. The mass of pesticides deposited by rainfall was estimated to be less than 2% of the total applied in these agricultural areas.     

Role of Propagule Size in the Success of Incipient Colonies of the Invasive Argentine Ant

Abstract: Factors that contribute to the successful establishment of invasive species are often poorly understood. Propagule size is considered a key determinant of establishment success, but experimental tests of its importance are rare. We used experimental colonies of the invasive Argentine ant (   Linepithema humile ) that differed both in worker and queen number to test how these attributes influence the survivorship and growth of incipient colonies. All propagules without workers experienced queen mortality, in contrast to only 6% of propagules with workers. In small propagules (10–1,000 workers), brood production increased with worker number but not queen number. In contrast, per capita measures of colony growth decreased with worker number over these colony sizes. In larger propagules ( 1,000–11,000 workers), brood production also increased with increasing worker number, but per capita brood production appeared independent of colony size. Our results suggest that queens need workers to establish successfully but that propagules with as few as 10 workers can grow quickly. Given the requirements for propagule success in Argentine ants, it is not surprising how easily they spread via human commerce.     

Effective monitoring of agriculture: a response

The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. We welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on our earlier paper, "Monitoring the World's Agriculture" (Sachs et al., Nature, 2010, 466, 558-560). In this response, we address their three main critiques labeled as 'the passive approach', 'the problem with uniform metrics' and 'the problem with composite metrics'. We expand on specific research questions at the core of the network design, on the distinction between key universal and site-specific metrics to detect change over time and across scales, and on the need for composite metrics in decision-making. We believe that simultaneously measuring indicators of the three pillars of sustainability (environmentally sound, social responsible and economically viable) in an effectively integrated monitoring system will ultimately allow scientists and land managers alike to find solutions to the most pressing problems facing global food security.     

Rangeland and pasture monitoring: an approach to interpretation of high-resolution imagery focused on observer calibration for repeatability

Collection of standardized assessment and monitoring data is critically important for supporting policy and management at local to continental scales. Remote sensing techniques, including image interpretation, have shown promise for collecting plant community composition and ground cover data efficiently. More work needs to be done, however, evaluating whether these techniques are sufficiently feasible, cost-effective, and repeatable to be applied in large programs. The goal of this study was to design and test an image-interpretation approach for collecting plant community composition and ground cover data appropriate for local and continental-scale assessment and monitoring of grassland, shrubland, savanna, and pasture ecosystems. We developed a geographic information system image-interpretation tool that uses points classified by experts to calibrate observers, including point-by-point training and quantitative quality control limits. To test this approach, field data and high-resolution imagery (∼3 cm ground sampling distance) were collected concurrently at 54 plots located around the USA. Seven observers with little prior experience used the system to classify 300 points in each plot into ten cover types (grass, shrub, soil, etc.). Good agreement among observers was achieved, with little detectable bias and low variability among observers (coefficient of variation in most plots <0.5). There was a predictable relationship between field and image-interpreter data (R ² > 0.9), suggesting regression-based adjustments can be used to relate image and field data. This approach could extend the utility of expensive-to-collect field data by allowing it to serve as a validation data source for data collected via image interpretation.