Equity and modeling in sustainability science: Examples and opportunities throughout the process.

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Expansion of a retrovirus lineage in the koala genome.

Retroviruses have left their legacy in host genomes over millions of years as endogenous retroviruses (ERVs), and their structure, diversity, and prevalence provide insights into the historical dynamics of retrovirus-host interactions. In bioinformatic analyses of koala (Phascolarctos cinereus) whole-genome sequences, we identify a recently expanded ERV lineage (phaCin-ß) that is related to the New World squirrel monkey retrovirus. This ERV expansion shares many parallels with the ongoing koala retrovirus (KoRV) invasion of the koala genome, including highly similar and mostly intact sequences, and polymorphic ERV loci in the sampled koala population. The recent phaCin-ß ERV colonization of the koala genome appears to predate the current KoRV invasion, but polymorphic ERVs and divergence comparisons between these two lineages predict a currently uncharacterized, possibly still extant, phaCin-ß retrovirus. The genomics approach to ERV-guided discovery of novel retroviruses in host species provides a strong incentive to search for phaCin-ß retroviruses in the Australasian fauna.

Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality.

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.

Estimating the environmental impacts of 57,000 food products.

Understanding and communicating the environmental impacts of food products is key to enabling transitions to environmentally sustainable food systems [El Bilali and Allahyari, Inf. Process. Agric. 5, 456-464 (2018)]. While previous analyses compared the impacts of food commodities such as fruits, wheat, and beef [Poore and Nemecek, Science 360, 987-992 (2018)], most food products contain numerous ingredients. However, because the amount of each ingredient in a product is often known only by the manufacturer, it has been difficult to assess their environmental impacts. Here, we develop an approach to overcome this limitation. It uses prior knowledge from ingredient lists to infer the composition of each ingredient, and then pairs this with environmental databases [Poore and Nemecek Science 360, 987-992 (2018); Gephart et al., Nature 597, 360-365 (2021)] to derive estimates of a food product's environmental impact across four indicators: greenhouse gas emissions, land use, water stress, and eutrophication potential. Using the approach on 57,000 products in the United Kingdom and Ireland shows food types have low (e.g., sugary beverages, fruits, breads), to intermediate (e.g., many desserts, pastries), to high environmental impacts (e.g., meat, fish, cheese). Incorporating NutriScore reveals more nutritious products are often more environmentally sustainable but there are exceptions to this trend, and foods consumers may view as substitutable can have markedly different impacts. Sensitivity analyses indicate the approach is robust to uncertainty in ingredient composition and in most cases sourcing. This approach provides a step toward enabling consumers, retailers, and policy makers to make informed decisions on the environmental impacts of food products.

Low Mutation Load in a Supergene Underpinning Alternative Male Mating Strategies in Ruff (Calidris pugnax).

A paradox in evolutionary biology is how supergenes can maintain high fitness despite reduced effective population size, the suppression of recombination, and the expected accumulation of mutational load. The ruff supergene involves 2 rare inversion haplotypes (satellite and faeder). These are recessive lethals but with dominant effects on male mating strategies, plumage, and body size. Sequence divergence to the wild-type (independent) haplotype indicates that the inversion could be as old as 4 million years. Here, we have constructed a highly contiguous genome assembly of the inversion region for both the independent and satellite haplotypes. Based on the new data, we estimate that the recombination event(s) creating the satellite haplotype occurred only about 70,000 yr ago. Contrary to expectations for supergenes, we find no substantial expansion of repeats and only a modest mutation load on the satellite and faeder haplotypes despite high sequence divergence to the non-inverted haplotype (1.46%). The essential centromere protein N (CENPN) gene is disrupted by the inversion and is as well conserved on the inversion haplotypes as on the noninversion haplotype. These results suggest that the inversion may be much younger than previously thought. The low mutation load, despite recessive lethality, may be explained by the introgression of the inversion from a now extinct lineage.

Phase 3 trial of gilteritinib plus azacitidine vs azacitidine for newly diagnosed FLT3mut+ AML ineligible for intensive chemotherapy.

Treatment results for patients with newly diagnosed FMS-like tyrosine kinase 3 (FLT3)-mutated (FLT3mut+) acute myeloid leukemia (AML) ineligible for intensive chemotherapy are disappointing. This multicenter, open-label, phase 3 trial randomized (2:1) untreated adults with FLT3mut+ AML ineligible for intensive induction chemotherapy to receive gilteritinib (120 mg/d orally) and azacitidine (GIL + AZA) or azacitidine (AZA) alone. The primary end point was overall survival (OS). At the interim analysis (August 26, 2020), a total of 123 patients were randomized to treatment (GIL + AZA, n = 74; AZA, n = 49). Subsequent AML therapy, including FLT3 inhibitors, was received by 20.3% (GIL + AZA) and 44.9% (AZA) of patients. Median OS was 9.82 (GIL + AZA) and 8.87 (AZA) months (hazard ratio, 0.916; 95% CI, 0.529-1.585; P = .753). The study was closed based on the protocol-specified boundary for futility. Median event-free survival was 0.03 month in both arms. Event-free survival defined by using composite complete remission (CRc) was 4.53 months for GIL + AZA and 0.03 month for AZA (hazard ratio, 0.686; 95% CI, 0.433-1.087; P = .156). CRc rates were 58.1% (GIL + AZA) and 26.5% (AZA) (difference, 31.4%; 95% CI, 13.1-49.7; P < .001). Adverse event (AE) rates were similar for GIL + AZA (100%) and AZA (95.7%); grade ≥3 AEs were 95.9% and 89.4%, respectively. Common AEs with GIL + AZA included pyrexia (47.9%) and diarrhea (38.4%). Gilteritinib steady-state trough concentrations did not differ between GIL + AZA and gilteritinib. GIL + AZA resulted in significantly higher CRc rates, although similar OS compared with AZA. Results support the safety/tolerability and clinical activity of upfront therapy with GIL + AZA in older/unfit patients with FLT3mut+ AML. This trial was registered at www.clinicaltrials.gov as #NCT02752035.

Air quality-related health damages of food.

Agriculture is a major contributor to air pollution, the largest environmental risk factor for mortality in the United States and worldwide. It is largely unknown, however, how individual foods or entire diets affect human health via poor air quality. We show how food production negatively impacts human health by increasing atmospheric fine particulate matter (PM2.5), and we identify ways to reduce these negative impacts of agriculture. We quantify the air quality-related health damages attributable to 95 agricultural commodities and 67 final food products, which encompass >99% of agricultural production in the United States. Agricultural production in the United States results in 17,900 annual air quality-related deaths, 15,900 of which are from food production. Of those, 80% are attributable to animal-based foods, both directly from animal production and indirectly from growing animal feed. On-farm interventions can reduce PM2.5-related mortality by 50%, including improved livestock waste management and fertilizer application practices that reduce emissions of ammonia, a secondary PM2.5 precursor, and improved crop and animal production practices that reduce primary PM2.5 emissions from tillage, field burning, livestock dust, and machinery. Dietary shifts toward more plant-based foods that maintain protein intake and other nutritional needs could reduce agricultural air quality-related mortality by 68 to 83%. In sum, improved livestock and fertilization practices, and dietary shifts could greatly decrease the health impacts of agriculture caused by its contribution to reduced air quality.

High Throughput UHPLC-MS-Based Lipidomics Using Vacuum Jacketed Columns.

Reversed-phase UHPLC-MS is extensively employed for both the profiling of biological fluids and tissues to characterize lipid dysregulation in disease and toxicological studies. With conventional LC-MS systems the chromatographic performance and throughput are limited due to dispersion from the fluidic connections as well as radial and longitudinal thermal gradients in the LC column. In this study vacuum jacketed columns (VJC), positioned at the source of the mass spectrometer, were applied to the lipidomic analysis of plasma extracts. Compared to conventional UHPLC, the VJC-based methods offered greater resolution, faster analysis, and improved peak intensity. For a 5 min VJC analysis, the peak capacity increased by 66%, peak tailing reduced by up to 34%, and the number of lipids detected increased by 30% compared to conventional UHPLC. The narrower peaks, and thus increased resolution, compared to the conventional system resulted in a 2-fold increase in peak intensity as well a significant improvement in MS and MS/MS spectral quality resulting in a 22% increase in the number of lipids identified. When applied to mouse plasma samples, reproducibility of the lipid intensities in the pooled QC ranged from 1.8-12%, with no related drift in tR observed.

A chromosome-level assembly of the Atlantic herring genome-detection of a supergene and other signals of selection.

The Atlantic herring is a model species for exploring the genetic basis for ecological adaptation, due to its huge population size and extremely low genetic differentiation at selectively neutral loci. However, such studies have so far been hampered because of a highly fragmented genome assembly. Here, we deliver a chromosome-level genome assembly based on a hybrid approach combining a de novo Pacific Biosciences (PacBio) assembly with Hi-C-supported scaffolding. The assembly comprises 26 autosomes with sizes ranging from 12.4 to 33.1 Mb and a total size, in chromosomes, of 726 Mb, which has been corroborated by a high-resolution linkage map. A comparison between the herring genome assembly with other high-quality assemblies from bony fishes revealed few inter-chromosomal but frequent intra-chromosomal rearrangements. The improved assembly facilitates analysis of previously intractable large-scale structural variation, allowing, for example, the detection of a 7.8-Mb inversion on Chromosome 12 underlying ecological adaptation. This supergene shows strong genetic differentiation between populations. The chromosome-based assembly also markedly improves the interpretation of previously detected signals of selection, allowing us to reveal hundreds of independent loci associated with ecological adaptation.

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Multiple health and environmental impacts of foods.

Food choices are shifting globally in ways that are negatively affecting both human health and the environment. Here we consider how consuming an additional serving per day of each of 15 foods is associated with 5 health outcomes in adults and 5 aspects of agriculturally driven environmental degradation. We find that while there is substantial variation in the health outcomes of different foods, foods associated with a larger reduction in disease risk for one health outcome are often associated with larger reductions in disease risk for other health outcomes. Likewise, foods with lower impacts on one metric of environmental harm tend to have lower impacts on others. Additionally, of the foods associated with improved health (whole grain cereals, fruits, vegetables, legumes, nuts, olive oil, and fish), all except fish have among the lowest environmental impacts, and fish has markedly lower impacts than red meats and processed meats. Foods associated with the largest negative environmental impacts-unprocessed and processed red meat-are consistently associated with the largest increases in disease risk. Thus, dietary transitions toward greater consumption of healthier foods would generally improve environmental sustainability, although processed foods high in sugars harm health but can have relatively low environmental impacts. These findings could help consumers, policy makers, and food companies to better understand the multiple health and environmental implications of food choices.

Fine-scale damage estimates of particulate matter air pollution reveal opportunities for location-specific mitigation of emissions.

Fine particulate matter (PM2.5) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.

Recurrent convergent evolution at amino acid residue 261 in fish rhodopsin.

The evolutionary process that occurs when a species colonizes a new environment provides an opportunity to explore the mechanisms underlying genetic adaptation, which is essential knowledge for understanding evolution and the maintenance of biodiversity. Atlantic herring has an estimated total breeding stock of about 1 trillion (1012) and has colonized the brackish Baltic Sea within the last 10,000 y. Minute genetic differentiation between Atlantic and Baltic herring populations at selectively neutral loci combined with this rapid adaptation to a new environment facilitated the identification of hundreds of loci underlying ecological adaptation. A major question in the field of evolutionary biology is to what extent such an adaptive process involves selection of novel mutations with large effects or genetic changes at many loci, each with a small effect on phenotype (i.e., selection on standing genetic variation). Here we show that a missense mutation in rhodopsin (Phe261Tyr) is an adaptation to the red-shifted Baltic Sea light environment. The transition from phenylalanine to tyrosine differs only by the presence of a hydroxyl moiety in the latter, but this results in an up to 10-nm red-shifted light absorbance of the receptor. Remarkably, an examination of the rhodopsin sequences from 2,056 species of fish revealed that the same missense mutation has occurred independently and been selected for during at least 20 transitions between light environments across all fish. Our results provide a spectacular example of convergent evolution and how a single amino acid change can have a major effect on ecological adaptation.

Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure.

Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore "pollution inequity": the difference between the environmental health damage caused by a racial-ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a "pollution advantage": They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a "pollution burden" of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002-2015 for all three racial-ethnic groups, but pollution inequity has remained high.

High-Throughput UHPLC/MS/MS-Based Metabolic Profiling Using a Vacuum Jacketed Column.

In UHPLC, frictional heating from the eluent flowing through the column at pressures of ca. 10-15 Kpsi causes radial diffusion via temperature differences between the center of the column and its walls. Longitudinal dispersion also occurs due to temperature gradients between the inlet and outlet. These effects cause band broadening but can be mitigated via a combination of vacuum jacketed stainless steel tubing, reduced column end nut mass, and a constant temperature in the column from heating the inlet fitting. Here, vacuum jacketed column (VJC) technology, employing a novel column housing located on the source of the mass spectrometer and minimized tubing from the column outlet to the electrospray probe, was applied to profiling metabolites in urine. For a 75 s reversed-phase gradient separation, the average peak widths for endogenous compounds in urine were 1.2 and 0.6 s for conventional LC/MS and VJC systems, respectively. The peak tailing factor was reduced from 1.25 to 1.13 when using the VJC system compared to conventional UHPLC, and the peak capacity increased from 65 to 120, with a 25% increase in features detected in urine. The increased resolving power of the VJC system reduced co-elution, simplifying MS and MS/MS spectra, providing a more confident metabolite identification. The increased LC performance also gave more intense MS peaks, with a 10-120% increase in response, improving the quality of the MS data and detection limits. Reducing the LC gradient duration to 37 s gave peak widths of ca. 0.4 s and a peak capacity of 84.

Fossil Energy Use, Climate Change Impacts, and Air Quality-Related Human Health Damages of Conventional and Diversified Cropping Systems in Iowa, USA.

Cropping system diversification can reduce the negative environmental impacts of agricultural production, including soil erosion and nutrient discharge. Less is known about how diversification affects energy use, climate change, and air quality, when considering farm operations and supply chain activities. We conducted a life cycle study using measurements from a nine-year Iowa field experiment to estimate fossil energy (FE) use, greenhouse gas (GHG) emissions, PM2.5-related emissions, human health impacts, and other agronomic and economic metrics of contrasting crop rotation systems and herbicide regimes. Rotation systems consisted of 2-year corn-soybean, 3-year corn-soybean-oat/clover, and 4-year corn-soybean-oat/alfalfa-alfalfa systems. Each was managed with conventional and low-herbicide treatments. FE consumption was 56% and 64% lower in the 3-year and 4-year rotations than in the 2-year rotation, and GHG emissions were 54% and 64% lower. Diversification reduced combined monetized damages from GHG and PM2.5-related emissions by 42% and 57%. Herbicide treatment had no significant impact on environmental outcomes, while corn and soybean yields and whole-rotation economic returns improved significantly under diversification. Results suggest that diversification via shifting from conventional corn-soybean rotations to longer rotations with small grain and forage crops substantially reduced FE use, GHG emissions, and air quality damages, without compromising economic or agronomic performance.

Structural complexity and molecular heterogeneity of a butterfly ejaculate reflect a complex history of selection.

Male ejaculates are often structurally complex, and this complexity is likely to influence key reproductive interactions between males and females. However, despite its potential evolutionary significance, the molecular underpinnings of ejaculate structural complexity have received little empirical attention. To address this knowledge gap, we sought to understand the biochemical and functional properties of the structurally complex ejaculates of Pieris rapae butterflies. Males in this species produce large ejaculates called spermatophores composed of an outer envelope, an inner matrix, and a bolus of sperm. Females are thought to benefit from the nutrition contained in the soluble inner matrix through increases in longevity and fecundity. However, the indigestible outer envelope of the spermatophore delays female remating, allowing males to monopolize paternity for longer. Here, we show that these two nonsperm-containing spermatophore regions, the inner matrix and the outer envelope, differ in their protein composition and functional properties. We also reveal how these divergent protein mixtures are separately stored in the male reproductive tract and sequentially transferred to the female reproductive tract during spermatophore assembly. Intriguingly, we discovered large quantities of female-derived proteases in both spermatophore regions shortly after mating, which may contribute to spermatophore digestion and hence, female control over remating rate. Finally, we report evidence of past selection on these spermatophore proteins and female proteases, indicating a complex evolutionary history. Our findings illustrate how structural complexity of ejaculates may allow functionally and/or spatially associated suites of proteins to respond rapidly to divergent selective pressures, such as sexual conflict or reproductive cooperation.

Cropping System Diversity Effects on Nutrient Discharge, Soil Erosion, and Agronomic Performance.

Nutrient, herbicide, and sediment loading from agricultural fields cause environmental and economic damage. Nutrient leaching and runoff pollution can lead to eutrophication and impaired drinking water resources, while soil erosion reduces water quality and agronomic productivity. Increased cropping system diversification has been proposed to address these problems. We used the ArcSWAT model and long-term Iowa field experimental measurements to estimate eutrophication and erosion impacts of three crop rotation systems under two weed management regimes. Rotations were comprised of 2-year corn-soybean, 3-year corn-soybean-oat/clover, and 4-year corn-soybean-oat/alfalfa-alfalfa systems. All were managed with conventional or low herbicide applications. Total N and P runoff losses were up to 39% and 30% lower, respectively, in the more diverse systems than the 2-year corn-soybean system, but NO3--N leaching losses were unaffected by cropping system. Diversification reduced erosion losses up to 60%. The 3- and 4-year systems maintained or increased crop yields and net returns relative to the 2-year conventional system. Reductions in herbicide use intensity generally did not affect nutrient and sediment losses nor crop yields and profitability. These results indicate that diversifying the corn-soybean rotation that dominates the central United States could reduce water nutrient contamination and soil erosion while maintaining farm productivity and profitability.