“No fences make bad neighbors” but markets make better ones: cap-and-trade reduces cross-border SO2 in a natural experiment

The clean air interstate rule (CAIR) was a regional cap-and-trade program announced in 2005 which covered 27 eastern US states and sought to reduce sulfur dioxide emissions from coal-fired power plants. The rule was later vacated after a court found that the non-targeted design of the program did not comply with the Clean Air Act provision to regulate interstate air pollution. Using a custom air pollution dispersion model, I calculate the interstate SO₂ pollution from 493 coal-fired power plants across the United States between 1997 and 2020. In a difference-in-differences setup with plants not covered by CAIR in the control group, I estimate the treatment effect of the program on overall- and cross-border SO₂ emissions and find a 24% reduction in overall emissions and reduces the risk that a plant violates air quality standards across state borders by 2–4%. I report evidence of heterogeneous treatment effects where the reduction in overall emissions attributed to CAIR is lower among plants transporting SO₂ in excess of 1% of the National Air Quality Standards to another state.

     

Application of the QuEChERS method for the determination of organochlorine pesticide residues in Brazilian fruit pulps by GC-ECD

The Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method was applied to the extraction of 14 organochlorine pesticides (OCPs) residues from commercial fruit pulps available in supermarkets in Fortaleza, Northeastern Brazil. The analyses were carried out by gas chromatography (GC), coupled to an electron-capture detector (ECD), and were confirmed by GC-tandem mass spectrometry (MS). The parameters of the analytical method, such as accuracy, precision, linear range, limits of detection and quantification, were determined for each pesticide. The results showed good linearity (R² ≥ 0.9916) and the overall average recoveries were considered satisfactory obtaining values between 69 and 110%, RSD of 2–15 %, except for hexachlorobenzene (HCB) in açai, acerola and guava pulp samples. The OCPs were detected in guava (α–HCH; lindane) and soursop (α, β–HCH isomers) samples. The QuEChERS method and GC–ECD were successfully used to analyze OCPs in commercially available Brazilian fruit pulps and can be applied in routine analytical laboratories.     

Assessing effects of non-native crayfish on mosquito survival

Introductions of non-native predators often reduce biodiversity and affect natural predator–prey relationships and may increase the abundance of potential disease vectors (e.g., mosquitoes) indirectly through competition or predation cascades. The Santa Monica Mountains (California, U.S.A.), situated in a global biodiversity hotspot, is an area of conservation concern due to climate change, urbanization, and the introduction of non-native species. We examined the effect of non-native crayfish (Procambarus clarkii) on an existing native predator, dragonfly nymphs (Aeshna sp.), and their mosquito larvae (Anopheles sp.) prey. We used laboratory experiments to compare the predation efficiency of both predators, separately and together, and field data on counts of dragonfly nymphs and mosquito larvae sampled from 13 local streams. We predicted a lower predation efficiency of crayfish compared with native dragonfly nymphs and a reduced predation efficiency of dragonfly nymphs in the presence of crayfish. Dragonfly nymphs were an order of magnitude more efficient predators than crayfish, and dragonfly nymph predation efficiency was reduced in the presence of crayfish. Field count data showed that populations of dragonfly nymphs and mosquito larvae were strongly correlated with crayfish presence in streams, such that sites with crayfish tended to have fewer dragonfly nymphs and more mosquito larvae. Under natural conditions, it is likely that crayfish reduce the abundance of dragonfly nymphs and their predation efficiency and thereby, directly and indirectly, lead to higher mosquito populations and a loss of ecosystem services related to disease vector control.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.