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• pan3.10695 comment "Social connections among individuals are essential components of social-ecological systems (SESs), enabling people to take actions to more effectively adapt or transform in response to widespread social-ecological change. Although scholars have associated social connections and cognitions with adaptive capacity, measuring actors' social networks may further clarify pathways for bolstering resilience-enhancing actions. We asked how social networks and socio-cognitions, as components of adaptive capacity, and SES regime shift severity affect individual landscape management behaviours using a quantitative analysis of ego network survey data from livestock producers and landcover data on regime shift severity (i.e. juniper encroachment) in the North American Great Plains. Producers who experienced severe regime shifts or perceived high risks from such shifts were not more likely to engage in transformative behaviour like prescribed burning. Instead, we found that social network characteristics explained significant variance in transformative behaviours. Policy implications: Our results indicate that social networks enable behaviours that have the potential to transform SESs, suggesting possible leverage points for enabling capacity and coordination toward sustainability. Particularly where private lands dominate and cultural practices condition regime shifts, clarifying how social connections promote resilience may provide much needed insight to bolster adaptive capacities in the face of global change. Major findings: This research explores how social networks and individual beliefs influence land management behaviors among livestock producers in the North American Great Plains. The study found that social networks are significantly more effective at predicting "transformative" behaviors—such as prescribed burning—than the actual ecological condition of the land. While "adaptive" behaviors like mechanical tree removal are often triggered by observing physical changes in the environment (regime shifts), major transformative actions depend heavily on the social support, information access, and trust provided by an individual's community and professional connections. These findings highlight that social constraints often limit environmental management more than a lack of information about ecological risks." assertion.
• pan3.10695 comment "Social connections among individuals are essential components of social-ecological systems (SESs), enabling people to take actions to more effectively adapt or transform in response to widespread social-ecological change. Although scholars have associated social connections and cognitions with adaptive capacity, measuring actors' social networks may further clarify pathways for bolstering resilience-enhancing actions. We asked how social networks and socio-cognitions, as components of adaptive capacity, and SES regime shift severity affect individual landscape management behaviours using a quantitative analysis of ego network survey data from livestock producers and landcover data on regime shift severity (i.e. juniper encroachment) in the North American Great Plains. Producers who experienced severe regime shifts or perceived high risks from such shifts were not more likely to engage in transformative behaviour like prescribed burning. Instead, we found that social network characteristics explained significant variance in transformative behaviours. Policy implications: Our results indicate that social networks enable behaviours that have the potential to transform SESs, suggesting possible leverage points for enabling capacity and coordination toward sustainability. Particularly where private lands dominate and cultural practices condition regime shifts, clarifying how social connections promote resilience may provide much needed insight to bolster adaptive capacities in the face of global change. Major findings: This research explores how social networks and individual beliefs influence land management behaviors among livestock producers in the North American Great Plains. The study found that social networks are significantly more effective at predicting "transformative" behaviors—such as prescribed burning—than the actual ecological condition of the land. While "adaptive" behaviors like mechanical tree removal are often triggered by observing physical changes in the environment (regime shifts), major transformative actions depend heavily on the social support, information access, and trust provided by an individual's community and professional connections. These findings highlight that social constraints often limit environmental management more than a lack of information about ecological risks." assertion.
• 2024JD041640 comment "Salt Lake City, Utah has higher concentrations of ozone, a pollutant harmful to human and plant life, in the atmosphere than the standard set by the United States Environmental Protection Agency (US EPA). The reasons for the high levels of ozone remain uncertain. Volatile organic compounds (VOCs) are a class of air pollutants that undergo reactions that produce ozone. Understanding their sources and reactions is important to be able to reduce air pollution. In this study, we measured 35 VOCs in SLC in August and September 2022 and used a model to identify their major sources. Concentrations of hazardous VOCs identified by the US EPA increased by 45%–217% when wildfire smoke was present in the air. Methanol and ethanol were the most important VOCs in terms of total concentration in the air, while isoprene and monoterpenes were the most important in terms of reactions that could create ozone. According to the model results, VOCs are emitted from five major sources including traffic and solvent use. Further measurements are needed to confirm the model results and reduce uncertainty of the important sources of VOCS. Major findings:The Salt Lake regional Smoke, Ozone and Aerosol Study (SAMOZA) conducted in late 2022 measured 35 different volatile organic compounds (VOCs) using advanced mass spectrometry and liquid chromatography. The researchers found that total VOC levels in the city averaged 32 parts per billion (ppb), but spiked as high as 141 ppb during certain hours. This data is used to calculate "OH reactivity," which helps scientists understand how quickly these chemicals react in the air to form pollutants like smog and ozone." assertion.
• 2024JD041640 comment "Salt Lake City, Utah has higher concentrations of ozone, a pollutant harmful to human and plant life, in the atmosphere than the standard set by the United States Environmental Protection Agency (US EPA). The reasons for the high levels of ozone remain uncertain. Volatile organic compounds (VOCs) are a class of air pollutants that undergo reactions that produce ozone. Understanding their sources and reactions is important to be able to reduce air pollution. In this study, we measured 35 VOCs in SLC in August and September 2022 and used a model to identify their major sources. Concentrations of hazardous VOCs identified by the US EPA increased by 45%–217% when wildfire smoke was present in the air. Methanol and ethanol were the most important VOCs in terms of total concentration in the air, while isoprene and monoterpenes were the most important in terms of reactions that could create ozone. According to the model results, VOCs are emitted from five major sources including traffic and solvent use. Further measurements are needed to confirm the model results and reduce uncertainty of the important sources of VOCS. Major findings:The Salt Lake regional Smoke, Ozone and Aerosol Study (SAMOZA) conducted in late 2022 measured 35 different volatile organic compounds (VOCs) using advanced mass spectrometry and liquid chromatography. The researchers found that total VOC levels in the city averaged 32 parts per billion (ppb), but spiked as high as 141 ppb during certain hours. This data is used to calculate "OH reactivity," which helps scientists understand how quickly these chemicals react in the air to form pollutants like smog and ozone." assertion.
• cobi.14243 comment "Wildlife conservation depends on supportive social as well as biophysical conditions. Social identities such as hunter and nonhunter are often associated with different attitudes toward wildlife. However, it is unknown whether dynamics within and among these identity groups explain how attitudes form and why they differ. To investigate how social identities help shape wildlife-related attitudes and the implications for wildlife policy and conservation, we built a structural equation model with survey data from Montana (USA) residents (n = 1758) that tested how social identities affect the relationship between experiences with grizzly bears (Ursus arctos horribilis) and attitudes toward the species. Model results (r2 = 0.51) demonstrated that the hunter identity magnified the negative effect of vicarious property damage on attitudes toward grizzly bears (β = −0.381, 95% confidence interval [CI]: −0.584 to −0.178, p < 0.001), which in turn strongly influenced acceptance (β = −0.571, 95% CI: −0.611 to −0.531, p < 0.001). Our findings suggested that hunters’ attitudes toward grizzly bears likely become more negative primarily because of in-group social interactions about negative experiences, and similar group dynamics may lead nonhunters to disregard the negative experiences that out-group members have with grizzly bears. Given the profound influence of social identity on human cognitions and behaviors in myriad contexts, the patterns we observed are likely important in a variety of wildlife conservation situations. To foster positive conservation outcomes and minimize polarization, management strategies should account for these identity-driven perceptions while prioritizing conflict prevention and promoting positive wildlife narratives within and among identity groups. This study illustrates the utility of social identity theory for explaining and influencing human–wildlife interactions. Major findings: This study examined how belonging to a social group—specifically identifying as a "hunter" or "nonhunter"—affects how people in Montana feel about grizzly bears. The researchers found that hunters' attitudes become much more negative when they hear stories of property damage from other hunters (their "in-group"), because people naturally trust and empathize more with members of their own group. Conversely, nonhunters are less influenced by these negative stories but tend to develop more positive feelings after having neutral or peaceful experiences with bears. The findings suggest that to protect wildlife effectively, managers must understand these social identities and work to prevent groups from becoming divided or angry with each other." assertion.
• cobi.14243 comment "Wildlife conservation depends on supportive social as well as biophysical conditions. Social identities such as hunter and nonhunter are often associated with different attitudes toward wildlife. However, it is unknown whether dynamics within and among these identity groups explain how attitudes form and why they differ. To investigate how social identities help shape wildlife-related attitudes and the implications for wildlife policy and conservation, we built a structural equation model with survey data from Montana (USA) residents (n = 1758) that tested how social identities affect the relationship between experiences with grizzly bears (Ursus arctos horribilis) and attitudes toward the species. Model results (r2 = 0.51) demonstrated that the hunter identity magnified the negative effect of vicarious property damage on attitudes toward grizzly bears (β = −0.381, 95% confidence interval [CI]: −0.584 to −0.178, p < 0.001), which in turn strongly influenced acceptance (β = −0.571, 95% CI: −0.611 to −0.531, p < 0.001). Our findings suggested that hunters’ attitudes toward grizzly bears likely become more negative primarily because of in-group social interactions about negative experiences, and similar group dynamics may lead nonhunters to disregard the negative experiences that out-group members have with grizzly bears. Given the profound influence of social identity on human cognitions and behaviors in myriad contexts, the patterns we observed are likely important in a variety of wildlife conservation situations. To foster positive conservation outcomes and minimize polarization, management strategies should account for these identity-driven perceptions while prioritizing conflict prevention and promoting positive wildlife narratives within and among identity groups. This study illustrates the utility of social identity theory for explaining and influencing human–wildlife interactions. Major findings: This study examined how belonging to a social group—specifically identifying as a "hunter" or "nonhunter"—affects how people in Montana feel about grizzly bears. The researchers found that hunters' attitudes become much more negative when they hear stories of property damage from other hunters (their "in-group"), because people naturally trust and empathize more with members of their own group. Conversely, nonhunters are less influenced by these negative stories but tend to develop more positive feelings after having neutral or peaceful experiences with bears. The findings suggest that to protect wildlife effectively, managers must understand these social identities and work to prevent groups from becoming divided or angry with each other." assertion.
• 10871209.2024.2318330?needAccess=true comment "Despite years of research, concepts such as human tolerance andacceptability of wildlife remain inconsistently defined and measured,creating confusion, undermining comparative and longitudinalresearch, and limiting utility to practitioners. To address these short-comings, the wildlife attitude-acceptability framework proposed inter-secting attitudes toward wildlife species with acceptability of impactsfrom that species to reveal four archetypes of human cognitionstoward wildlife. Here, we use data from western US household surveysto populate the conceptual space of the wildlife attitude-acceptabilityframework with human cognitions toward three carnivore species:gray wolf (Canis lupis), cougar (Puma concolor), and grizzly bear(Ursus arctos horribilis). This empirical application of the wildlife atti-tude-acceptability framework demonstrates its potential to informmanagement and conservation efforts, promote consistent measure-ment across species and studies, and extend theoretical understand-ing of concepts like tolerance, which are necessary for human–wildlifecoexistence. We discuss these opportunities and remaining needs forimprovement before wider adoption.KEYWORDSCarnivores; coexistence;cognitions; conservation;methods; quantitativesurvey; toleranceIntroduction and Literature ReviewHuman dimensions of wildlife researchers have increasingly sought to define and oper-ationalize concepts relating to human–wildlife interactions, including people’s cognitionstoward species and their evaluations of wildlife-related costs and benefits (Carlson et al.,2023; König et al., 2020). Despite this literature, or perhaps because of it (Bruskotter et al.,2015), wildlife scientists and practitioners continue to hold shared, contested, and some-times confused perspectives toward concepts such as tolerance, acceptability, coexistence,and other cognitions such as beliefs, attitudes, and behavioral intentions when used withregard to wildlife (Glikman et al., 2021; Hill, 2021). Universally shared definitions of theseCONTACT Alexander L. Metcalf alex.metcalf@umontana.edu Wildlife Biology Degree Program, Department ofSociety & Conservation, W.A. Franke College of Forestry & Conservation, University of Montana, 440 CHCB, 32 Campus Drive,Missoula, MT 59812, USAThis article has been republished with a minor change. This change does not impact on the academic content of the article.HUMAN DIMENSIONS OF WILDLIFE2025, VOL. 30, NO. 4, 415–429https://doi.org/10.1080/10871209.2024.2318330© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided theoriginal work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. Major findings: Researchers developed a new tool called the "wildlife attitude-acceptability framework" to better understand how people think about large predators like wolves, cougars, and grizzly bears. By looking at whether people like the animal (their attitude) and whether they are okay with the impacts the animal has on their lives (their acceptability), the researchers identified four main groups: advocates, conditional supporters, opponents, and those who tolerate the species. The study found that while many people like these animals, they are often "conditional supporters" who only want them around if they don't cause too much trouble. This framework helps wildlife managers set clearer goals and create better plans for helping humans and wildlife coexist." assertion.
• 10871209.2024.2318330?needAccess=true comment "Despite years of research, concepts such as human tolerance andacceptability of wildlife remain inconsistently defined and measured,creating confusion, undermining comparative and longitudinalresearch, and limiting utility to practitioners. To address these short-comings, the wildlife attitude-acceptability framework proposed inter-secting attitudes toward wildlife species with acceptability of impactsfrom that species to reveal four archetypes of human cognitionstoward wildlife. Here, we use data from western US household surveysto populate the conceptual space of the wildlife attitude-acceptabilityframework with human cognitions toward three carnivore species:gray wolf (Canis lupis), cougar (Puma concolor), and grizzly bear(Ursus arctos horribilis). This empirical application of the wildlife atti-tude-acceptability framework demonstrates its potential to informmanagement and conservation efforts, promote consistent measure-ment across species and studies, and extend theoretical understand-ing of concepts like tolerance, which are necessary for human–wildlifecoexistence. We discuss these opportunities and remaining needs forimprovement before wider adoption.KEYWORDSCarnivores; coexistence;cognitions; conservation;methods; quantitativesurvey; toleranceIntroduction and Literature ReviewHuman dimensions of wildlife researchers have increasingly sought to define and oper-ationalize concepts relating to human–wildlife interactions, including people’s cognitionstoward species and their evaluations of wildlife-related costs and benefits (Carlson et al.,2023; König et al., 2020). Despite this literature, or perhaps because of it (Bruskotter et al.,2015), wildlife scientists and practitioners continue to hold shared, contested, and some-times confused perspectives toward concepts such as tolerance, acceptability, coexistence,and other cognitions such as beliefs, attitudes, and behavioral intentions when used withregard to wildlife (Glikman et al., 2021; Hill, 2021). Universally shared definitions of theseCONTACT Alexander L. Metcalf alex.metcalf@umontana.edu Wildlife Biology Degree Program, Department ofSociety & Conservation, W.A. Franke College of Forestry & Conservation, University of Montana, 440 CHCB, 32 Campus Drive,Missoula, MT 59812, USAThis article has been republished with a minor change. This change does not impact on the academic content of the article.HUMAN DIMENSIONS OF WILDLIFE2025, VOL. 30, NO. 4, 415–429https://doi.org/10.1080/10871209.2024.2318330© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided theoriginal work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. Major findings: Researchers developed a new tool called the "wildlife attitude-acceptability framework" to better understand how people think about large predators like wolves, cougars, and grizzly bears. By looking at whether people like the animal (their attitude) and whether they are okay with the impacts the animal has on their lives (their acceptability), the researchers identified four main groups: advocates, conditional supporters, opponents, and those who tolerate the species. The study found that while many people like these animals, they are often "conditional supporters" who only want them around if they don't cause too much trouble. This framework helps wildlife managers set clearer goals and create better plans for helping humans and wildlife coexist." assertion.
• s43621-024-00253-y comment "Beef production systems are at the center of ongoing discussion and debate on food systems sustainability. There is a growing interest among beef producers, consumers, and other beef supply chain stakeholders in achieving greater sustainability within the industry, but the relationship of this interest to general sustainability issues such as climate change, biodiversity loss, food security, livelihood risks, and animal welfare concerns is unclear. Specifically, there is very little research documenting how beef producers define and view the concept of sustainability and how to achieve it. Producer perspectives are critical to identifying constraints to sustainability transitions or to help build agreement with other producers about the shared values such transitions may support. Through a secondary analysis of survey data of U.S. beef producers (n = 911) conducted in 2021 by the Trust in Food division of Farm Journal, a corporation that provides content, data, and business insights to the agricultural community (e.g., producers, processors/distributors, and retailers), we investigated what “sustainable beef” means to U.S. beef producers, highlighting the key components and constraints they perceive to achieving desirable sustainability outcomes. Leveraging the three-pillar model of sustainability as a framework for analysis, we identified key themes producers use to define “sustainable beef.” We found that producers collectively viewed sustainability as: (1) multidimensional and interconnected; (2) semi-closed and regenerative; (3) long-lasting; and (4) producer-centered, although an integrated perspective uniting these aspects was rare. We discuss how these perspectives may be the basis for sustainability efforts supported by producers and raise future research considerations toward a shared understanding of what sustainability is and what is needed for enduring sustainability solutions in the U.S. beef industry. Major findings: A 2021 survey of 911 U.S. beef producers investigated how those in the industry define "sustainable beef." The study found that 71% (n = 649) of respondents came from families with three or more generations in beef production. Producers collectively identified sustainability through four themes: it is multidimensional (covering environmental, social, and economic needs), semi-closed (minimizing outside inputs), long-lasting (focused on the future), and producer-centered (focused on fair markets). While 49% of responses mentioned environmental topics and 43% discussed economic viability, only 5% of producers expressed a fully integrated view including all three "pillars" of sustainability. The research highlights that while the industry accounts for 17% of total U.S. agricultural cash receipts ($72.9 billion in 2021), producers face significant external constraints, such as market consolidation where the four largest packing firms control roughly 75% of the market." assertion.
• s43621-024-00253-y comment "Beef production systems are at the center of ongoing discussion and debate on food systems sustainability. There is a growing interest among beef producers, consumers, and other beef supply chain stakeholders in achieving greater sustainability within the industry, but the relationship of this interest to general sustainability issues such as climate change, biodiversity loss, food security, livelihood risks, and animal welfare concerns is unclear. Specifically, there is very little research documenting how beef producers define and view the concept of sustainability and how to achieve it. Producer perspectives are critical to identifying constraints to sustainability transitions or to help build agreement with other producers about the shared values such transitions may support. Through a secondary analysis of survey data of U.S. beef producers (n = 911) conducted in 2021 by the Trust in Food division of Farm Journal, a corporation that provides content, data, and business insights to the agricultural community (e.g., producers, processors/distributors, and retailers), we investigated what “sustainable beef” means to U.S. beef producers, highlighting the key components and constraints they perceive to achieving desirable sustainability outcomes. Leveraging the three-pillar model of sustainability as a framework for analysis, we identified key themes producers use to define “sustainable beef.” We found that producers collectively viewed sustainability as: (1) multidimensional and interconnected; (2) semi-closed and regenerative; (3) long-lasting; and (4) producer-centered, although an integrated perspective uniting these aspects was rare. We discuss how these perspectives may be the basis for sustainability efforts supported by producers and raise future research considerations toward a shared understanding of what sustainability is and what is needed for enduring sustainability solutions in the U.S. beef industry. Major findings: A 2021 survey of 911 U.S. beef producers investigated how those in the industry define "sustainable beef." The study found that 71% (n = 649) of respondents came from families with three or more generations in beef production. Producers collectively identified sustainability through four themes: it is multidimensional (covering environmental, social, and economic needs), semi-closed (minimizing outside inputs), long-lasting (focused on the future), and producer-centered (focused on fair markets). While 49% of responses mentioned environmental topics and 43% discussed economic viability, only 5% of producers expressed a fully integrated view including all three "pillars" of sustainability. The research highlights that while the industry accounts for 17% of total U.S. agricultural cash receipts ($72.9 billion in 2021), producers face significant external constraints, such as market consolidation where the four largest packing firms control roughly 75% of the market." assertion.
• 2023GL105811 comment "Climate change has led to an increase in the frequency and size of wildfires in the Western United States. The gases and particles released from wildfires impact air quality and climate, so it is important to understand the chemical composition of these emissions. In current air quality forecasts and climate models, the composition of wildfire emissions is based on the dominant vegetation burned and is assumed to be constant over time. In contrast, measurements from laboratory burns indicate that the composition of emissions from fires changes over time, as fires progress from more flaming combustion to flameless burning dominated by smoke (smoldering). It is challenging to have daily field measurements of the emissions from long-lived wildfires, but there are instruments in space that can make daily observations of wildfires globally. In this study, we show how the composition of emissions from wildfires in California, Oregon, and Washington changed over time, as they progressed from more flaming to more smoldering combustion, using observations from a satellite instrument called TROPOMI. The analysis of the composition of wildfire emissions and their evolution over time using TROPOMI could improve air quality forecasting and climate modeling globally. Major findings: A 2023 study used the TROPOMI satellite instrument to track how the chemical composition of wildfire smoke changes as fires evolve. By analyzing 15 large wildfires in the Western U.S., researchers discovered that the ratio of nitrogen dioxide (NO2) to carbon monoxide (CO) drops significantly as a fire moves from its "flaming" stage to its "smoldering" stage. This is a vital finding because current air quality forecasts often assume smoke composition stays the same throughout a fire's duration. Using daily satellite observations allows scientists to see these shifts in real-time, even when ground-based measurements are unavailable. This information helps improve models that predict how wildfire smoke will impact public health and the global climate over several weeks." assertion.
• 2023GL105811 comment "Climate change has led to an increase in the frequency and size of wildfires in the Western United States. The gases and particles released from wildfires impact air quality and climate, so it is important to understand the chemical composition of these emissions. In current air quality forecasts and climate models, the composition of wildfire emissions is based on the dominant vegetation burned and is assumed to be constant over time. In contrast, measurements from laboratory burns indicate that the composition of emissions from fires changes over time, as fires progress from more flaming combustion to flameless burning dominated by smoke (smoldering). It is challenging to have daily field measurements of the emissions from long-lived wildfires, but there are instruments in space that can make daily observations of wildfires globally. In this study, we show how the composition of emissions from wildfires in California, Oregon, and Washington changed over time, as they progressed from more flaming to more smoldering combustion, using observations from a satellite instrument called TROPOMI. The analysis of the composition of wildfire emissions and their evolution over time using TROPOMI could improve air quality forecasting and climate modeling globally. Major findings: A 2023 study used the TROPOMI satellite instrument to track how the chemical composition of wildfire smoke changes as fires evolve. By analyzing 15 large wildfires in the Western U.S., researchers discovered that the ratio of nitrogen dioxide (NO2) to carbon monoxide (CO) drops significantly as a fire moves from its "flaming" stage to its "smoldering" stage. This is a vital finding because current air quality forecasts often assume smoke composition stays the same throughout a fire's duration. Using daily satellite observations allows scientists to see these shifts in real-time, even when ground-based measurements are unavailable. This information helps improve models that predict how wildfire smoke will impact public health and the global climate over several weeks." assertion.
• S1550742423000830 comment "Rangelands across the world are facing rapid and unprecedented social and ecological change. In the US West, sustaining the ecological and economic integrity of rangelands across both public and private lands depends largely on ranchers who make adaptive decisions in the face of variability and uncertainty. In this study, we build on previous conceptualizations of adaptive decision making that situate individual-level decisions within complex rangeland social-ecological systems. We surveyed 450 (36% response rate) Montana ranchers to gain insight into how key factors influenced adaptive decision making, specifically in the context of ongoing drought and climate-related change affecting rangeland ecology and productivity. We predicted that ranchers’ management goals, their use of information sources, and their use of monitoring would significantly influence the use of adaptive practices, with monitoring mediating the relationship between the explanatory and response variables. We tested these predictions using a path model analysis and found that management goals related to both stewardship and profit/production, the number of information sources used, and monitoring were all significantly and positively related to ranchers’ use of adaptive management practices. Interestingly, we found that these factors were hierarchical with monitoring and the use of information was the strongest predictor while management goals were secondary. The significant, mediating effect of monitoring on the use of adaptive practices suggests that monitoring may be an important means for providing ranchers with useful and timely information about rangeland condition that is needed to adjust their actions, meet their management goals, and adapt to drought and climate-related change. We argue there is a need to better understand the efficacy of monitoring designs—of what, by whom, and how—for adaptive decision making, and we discuss other considerations related to the provision of useful drought and climate information for adaptive decision making based on our findings. Major findings: A 2023 study of 450 Montana ranchers explored how they make management decisions during periods of drought and climate change. The researchers found that while a rancher's goals (like taking care of the land or making a profit) and their sources of information are important, the single strongest predictor of whether they use "adaptive" management practices is whether they have a formal monitoring program. Monitoring acts as a "feedback loop," giving ranchers the data they need to adjust their grazing plans or water usage in real-time. Even though monitoring is incredibly helpful for keeping land healthy, fewer than half of the ranchers surveyed (42.9%) currently use a formal system, suggesting that helping ranchers with the cost and time of monitoring could greatly improve how rangelands are managed in the future." assertion.
• S1550742423000830 comment "Rangelands across the world are facing rapid and unprecedented social and ecological change. In the US West, sustaining the ecological and economic integrity of rangelands across both public and private lands depends largely on ranchers who make adaptive decisions in the face of variability and uncertainty. In this study, we build on previous conceptualizations of adaptive decision making that situate individual-level decisions within complex rangeland social-ecological systems. We surveyed 450 (36% response rate) Montana ranchers to gain insight into how key factors influenced adaptive decision making, specifically in the context of ongoing drought and climate-related change affecting rangeland ecology and productivity. We predicted that ranchers’ management goals, their use of information sources, and their use of monitoring would significantly influence the use of adaptive practices, with monitoring mediating the relationship between the explanatory and response variables. We tested these predictions using a path model analysis and found that management goals related to both stewardship and profit/production, the number of information sources used, and monitoring were all significantly and positively related to ranchers’ use of adaptive management practices. Interestingly, we found that these factors were hierarchical with monitoring and the use of information was the strongest predictor while management goals were secondary. The significant, mediating effect of monitoring on the use of adaptive practices suggests that monitoring may be an important means for providing ranchers with useful and timely information about rangeland condition that is needed to adjust their actions, meet their management goals, and adapt to drought and climate-related change. We argue there is a need to better understand the efficacy of monitoring designs—of what, by whom, and how—for adaptive decision making, and we discuss other considerations related to the provision of useful drought and climate information for adaptive decision making based on our findings. Major findings: A 2023 study of 450 Montana ranchers explored how they make management decisions during periods of drought and climate change. The researchers found that while a rancher's goals (like taking care of the land or making a profit) and their sources of information are important, the single strongest predictor of whether they use "adaptive" management practices is whether they have a formal monitoring program. Monitoring acts as a "feedback loop," giving ranchers the data they need to adjust their grazing plans or water usage in real-time. Even though monitoring is incredibly helpful for keeping land healthy, fewer than half of the ranchers surveyed (42.9%) currently use a formal system, suggesting that helping ranchers with the cost and time of monitoring could greatly improve how rangelands are managed in the future." assertion.
• d3ea00098b comment "Formic acid (FA) and acetic acid (AA), two of the most abundant organic acids in the atmosphere, are typically underestimated by atmospheric models. Here we investigate their emissions, chemistry, and measurement uncertainties in biomass burning smoke sampled during the WE-CAN and FIREX-AQ aircraft campaigns. Our observed FA emission ratios (ERs) and emission factors (EFs) were generally higher than the 75th percentile of literature values, with little dependence on fuel type or combustion efficiency. Rapid in-plume FA production was observed (2.7 ppb ppmCO−1 h−1), representing up to ∼20% of the total emitted reactive organic carbon being converted to FA within half a day. AA ERs and EFs showed good agreement with the literature, with little or no secondary production observed within <8 hours of plume aging. Observed FA and AA trends in the near-field were not captured by a box model using the explicit Master Chemical Mechanism nor simplified GEOS-Chem chemistry, even after tripling the model's initial VOC concentrations. Consequently, the GEOS-Chem chemical transport model underestimates both acids in the western U.S. by a factor of >4. This is likely due to missing secondary chemistry in biomass burning smoke and/or coniferous forest biogenic emissions. This work highlights uncertainties in measurements (up to 100%) and even large unknowns in the chemical formation of organic acids in polluted environments, both of which need to be addressed to better understand their global budget. Major findings:Using data from the WE-CAN and FIREX-AQ aircraft campaigns, researchers discovered that formic acid emissions and secondary production in wildfire smoke are 3.5 times higher than previously reported in scientific literature. Despite these significantly higher observed levels, current global atmospheric models (such as GEOS-Chem) still underestimate formic and acetic acids by more than a factor of four. This study suggests that models are missing key chemical pathways—including secondary production from unknown precursors in biomass burning and biogenic emissions from coniferous forests—which are critical for accurately predicting air quality and cloud chemistry during wildfire seasons." assertion.
• d3ea00098b comment "Formic acid (FA) and acetic acid (AA), two of the most abundant organic acids in the atmosphere, are typically underestimated by atmospheric models. Here we investigate their emissions, chemistry, and measurement uncertainties in biomass burning smoke sampled during the WE-CAN and FIREX-AQ aircraft campaigns. Our observed FA emission ratios (ERs) and emission factors (EFs) were generally higher than the 75th percentile of literature values, with little dependence on fuel type or combustion efficiency. Rapid in-plume FA production was observed (2.7 ppb ppmCO−1 h−1), representing up to ∼20% of the total emitted reactive organic carbon being converted to FA within half a day. AA ERs and EFs showed good agreement with the literature, with little or no secondary production observed within <8 hours of plume aging. Observed FA and AA trends in the near-field were not captured by a box model using the explicit Master Chemical Mechanism nor simplified GEOS-Chem chemistry, even after tripling the model's initial VOC concentrations. Consequently, the GEOS-Chem chemical transport model underestimates both acids in the western U.S. by a factor of >4. This is likely due to missing secondary chemistry in biomass burning smoke and/or coniferous forest biogenic emissions. This work highlights uncertainties in measurements (up to 100%) and even large unknowns in the chemical formation of organic acids in polluted environments, both of which need to be addressed to better understand their global budget. Major findings:Using data from the WE-CAN and FIREX-AQ aircraft campaigns, researchers discovered that formic acid emissions and secondary production in wildfire smoke are 3.5 times higher than previously reported in scientific literature. Despite these significantly higher observed levels, current global atmospheric models (such as GEOS-Chem) still underestimate formic and acetic acids by more than a factor of four. This study suggests that models are missing key chemical pathways—including secondary production from unknown precursors in biomass burning and biogenic emissions from coniferous forests—which are critical for accurately predicting air quality and cloud chemistry during wildfire seasons." assertion.
• 620 comment "Post-industrial communities across the world are transitioning from industrial economies and identities to an uncertain future. Their successful transitions depend on communities’ abilities to navigate change and maintain a quality of life, or their community’s resilience. Previous scholarship offers resources and capabilities that facilitate or inhibit community resilience such as leadership, social capital, and information. However, collective memory is not well integrated within the community resilience literature. Drawing on data from interviews with 33 community leaders in the town of Anaconda, Montana, we illuminate the impact of collective memory on community resilience. The AnacondaSmelter Stack stands out as a specific landmark and prominent feature of the built environment that perpetuates particular collective memories in Anaconda. We find that collective memory is an integral part of community resilience, where memories can aid in a community’s recovery and rebuilding or constrain thinking and divide viewpoints. We argue that ignoring collective memory’s connections to resilience can undermine efforts to face changes in these communities. Keywords: Community resilience, collective memory, post-industrial towns, mining A 2023 study of Anaconda, Montana, explores how a community's "collective memory" of its industrial past—symbolized by the iconic 585-foot Smelter Stack—impacts its ability to transition to a new future. Researchers found that while these shared memories can be a source of pride and a "galvanizing force" for recovery, they can also act as a constraint that divides viewpoints and makes it harder for the town to embrace new economic paths like tourism. The study concludes that ignoring these deep emotional ties to history can undermine efforts to build community resilience, suggesting that successful transitions in post-industrial towns require cleanups and development plans that are "historically informed" and respect the community's lived experiences. Major Findings: A 2023 study of Anaconda, Montana, explores how a community's "collective memory" of its industrial past—symbolized by the iconic 585-foot Smelter Stack—impacts its ability to transition to a new future. Researchers found that while these shared memories can be a source of pride and a "galvanizing force" for recovery, they can also act as a constraint that divides viewpoints and makes it harder for the town to embrace new economic paths like tourism. The study concludes that ignoring these deep emotional ties to history can undermine efforts to build community resilience, suggesting that successful transitions in post-industrial towns require cleanups and development plans that are "historically informed" and respect the community's lived experiences." assertion.
• 620 comment "Post-industrial communities across the world are transitioning from industrial economies and identities to an uncertain future. Their successful transitions depend on communities’ abilities to navigate change and maintain a quality of life, or their community’s resilience. Previous scholarship offers resources and capabilities that facilitate or inhibit community resilience such as leadership, social capital, and information. However, collective memory is not well integrated within the community resilience literature. Drawing on data from interviews with 33 community leaders in the town of Anaconda, Montana, we illuminate the impact of collective memory on community resilience. The AnacondaSmelter Stack stands out as a specific landmark and prominent feature of the built environment that perpetuates particular collective memories in Anaconda. We find that collective memory is an integral part of community resilience, where memories can aid in a community’s recovery and rebuilding or constrain thinking and divide viewpoints. We argue that ignoring collective memory’s connections to resilience can undermine efforts to face changes in these communities. Keywords: Community resilience, collective memory, post-industrial towns, mining A 2023 study of Anaconda, Montana, explores how a community's "collective memory" of its industrial past—symbolized by the iconic 585-foot Smelter Stack—impacts its ability to transition to a new future. Researchers found that while these shared memories can be a source of pride and a "galvanizing force" for recovery, they can also act as a constraint that divides viewpoints and makes it harder for the town to embrace new economic paths like tourism. The study concludes that ignoring these deep emotional ties to history can undermine efforts to build community resilience, suggesting that successful transitions in post-industrial towns require cleanups and development plans that are "historically informed" and respect the community's lived experiences. Major Findings: A 2023 study of Anaconda, Montana, explores how a community's "collective memory" of its industrial past—symbolized by the iconic 585-foot Smelter Stack—impacts its ability to transition to a new future. Researchers found that while these shared memories can be a source of pride and a "galvanizing force" for recovery, they can also act as a constraint that divides viewpoints and makes it harder for the town to embrace new economic paths like tourism. The study concludes that ignoring these deep emotional ties to history can undermine efforts to build community resilience, suggesting that successful transitions in post-industrial towns require cleanups and development plans that are "historically informed" and respect the community's lived experiences." assertion.
• 2403.10730 comment "In Precision Agriculture, the utilization of management zones (MZs) that take into account within-field variability facilitates effective fertilizer management. This approach enables the optimization of nitrogen (N) rates to maximize crop yield production and enhance agronomic use efficiency. However, existing works often neglect the consideration of responsivity to fertilizer as a factor influencing MZ determination. In response to this gap, we present a MZ clustering method based on fertilizer responsivity. We build upon the statement that the responsivity of a given site to the fertilizer rate is described by the shape of its corresponding N fertilizer-yield response (N-response) curve. Thus, we generate N-response curves for all sites within the field using a convolutional neural network (CNN). The shape of the approximated N-response curves is then characterized using functional principal component analysis. Subsequently, a counterfactual explanation (CFE) method is applied to discern the impact of various variables on MZ membership. The genetic algorithm-based CFE solves a multi-objective optimization problem and aims to identify the minimum combination of features needed to alter a site's cluster assignment. Results from two yield prediction datasets indicate that the features with the greatest influence on MZ membership are associated with terrain characteristics that either facilitate or impede fertilizer runoff, such as terrain slope or topographic aspect. Major findings:Researchers at Montana State University developed a new method for creating "management zones" in farm fields by using artificial intelligence to predict how crops will respond to nitrogen fertilizer. Unlike older methods that only look at historical yields, this approach uses a neural network to generate "N-response curves"—graphs showing how yield changes as fertilizer increases—for every spot in a field. To make the AI's decisions easier to understand, the researchers used "counterfactual explanations," which essentially ask: "What would have to change for this spot to behave differently?" The study found that terrain features like slope and soil moisture are the most important factors; for example, steep slopes often lead to fertilizer runoff, which makes those areas less responsive to treatment. This helps farmers apply fertilizer more accurately, saving money and reducing environmental impact." assertion.
• 2403.10730 comment "In Precision Agriculture, the utilization of management zones (MZs) that take into account within-field variability facilitates effective fertilizer management. This approach enables the optimization of nitrogen (N) rates to maximize crop yield production and enhance agronomic use efficiency. However, existing works often neglect the consideration of responsivity to fertilizer as a factor influencing MZ determination. In response to this gap, we present a MZ clustering method based on fertilizer responsivity. We build upon the statement that the responsivity of a given site to the fertilizer rate is described by the shape of its corresponding N fertilizer-yield response (N-response) curve. Thus, we generate N-response curves for all sites within the field using a convolutional neural network (CNN). The shape of the approximated N-response curves is then characterized using functional principal component analysis. Subsequently, a counterfactual explanation (CFE) method is applied to discern the impact of various variables on MZ membership. The genetic algorithm-based CFE solves a multi-objective optimization problem and aims to identify the minimum combination of features needed to alter a site's cluster assignment. Results from two yield prediction datasets indicate that the features with the greatest influence on MZ membership are associated with terrain characteristics that either facilitate or impede fertilizer runoff, such as terrain slope or topographic aspect. Major findings:Researchers at Montana State University developed a new method for creating "management zones" in farm fields by using artificial intelligence to predict how crops will respond to nitrogen fertilizer. Unlike older methods that only look at historical yields, this approach uses a neural network to generate "N-response curves"—graphs showing how yield changes as fertilizer increases—for every spot in a field. To make the AI's decisions easier to understand, the researchers used "counterfactual explanations," which essentially ask: "What would have to change for this spot to behave differently?" The study found that terrain features like slope and soil moisture are the most important factors; for example, steep slopes often lead to fertilizer runoff, which makes those areas less responsive to treatment. This helps farmers apply fertilizer more accurately, saving money and reducing environmental impact." assertion.
• 10365540 comment "Accurate uncertainty quantification is necessary to enhance the reliability of deep learning (DL) models in real-world applications. In the case of regression tasks, prediction intervals (PIs) should be provided along with the deterministic predictions of DL models. Such PIs are useful or “high-quality (HQ)” as long as they are sufficiently narrow and capture most of the probability density. In this article, we present a method to learn PIs for regression-based neural networks (NNs) automatically in addition to the conventional target predictions. In particular, we train two companion NNs: one that uses one output, the target estimate, and another that uses two outputs, the upper and lower bounds of the corresponding PI. Our main contribution is the design of a novel loss function for the PI-generation network that takes into account the output of the target-estimation network and has two optimization objectives: minimizing the mean PI width and ensuring the PI integrity using constraints that maximize the PI probability coverage implicitly. Furthermore, we introduce a self-adaptive coefficient that balances both objectives within the loss function, which alleviates the task of fine-tuning. Experiments using a synthetic dataset, eight benchmark datasets, and a real-world crop yield prediction dataset showed that our method was able to maintain a nominal probability coverage and produce significantly narrower PIs without detriment to its target estimation accuracy when compared to those PIs generated by three state-of-the-art neural-network-based methods. In other words, our method was shown to produce higher quality PIs. Major findings:The DualAQD framework produces "prediction intervals" that inform users of the confidence level associated with an AI model's specific estimate. This method generates narrower and more accurate confidence ranges than existing methods while maintaining high overall target accuracy. The system successfully identifies regions of high uncertainty in crop yield predictions, increasing the reliability of deep learning models for high-stakes decision-making." assertion.
• 10365540 comment "Accurate uncertainty quantification is necessary to enhance the reliability of deep learning (DL) models in real-world applications. In the case of regression tasks, prediction intervals (PIs) should be provided along with the deterministic predictions of DL models. Such PIs are useful or “high-quality (HQ)” as long as they are sufficiently narrow and capture most of the probability density. In this article, we present a method to learn PIs for regression-based neural networks (NNs) automatically in addition to the conventional target predictions. In particular, we train two companion NNs: one that uses one output, the target estimate, and another that uses two outputs, the upper and lower bounds of the corresponding PI. Our main contribution is the design of a novel loss function for the PI-generation network that takes into account the output of the target-estimation network and has two optimization objectives: minimizing the mean PI width and ensuring the PI integrity using constraints that maximize the PI probability coverage implicitly. Furthermore, we introduce a self-adaptive coefficient that balances both objectives within the loss function, which alleviates the task of fine-tuning. Experiments using a synthetic dataset, eight benchmark datasets, and a real-world crop yield prediction dataset showed that our method was able to maintain a nominal probability coverage and produce significantly narrower PIs without detriment to its target estimation accuracy when compared to those PIs generated by three state-of-the-art neural-network-based methods. In other words, our method was shown to produce higher quality PIs. Major findings:The DualAQD framework produces "prediction intervals" that inform users of the confidence level associated with an AI model's specific estimate. This method generates narrower and more accurate confidence ranges than existing methods while maintaining high overall target accuracy. The system successfully identifies regions of high uncertainty in crop yield predictions, increasing the reliability of deep learning models for high-stakes decision-making." assertion.
• 2023JD039309 comment "Crop residue and prescribed fires emit pollution that impacts air quality. FIREX-AQ provided observations of these emissions to better characterize their variability with a detailed set of chemical observations. These observations showed significant differences in the emissions from burning different crops (corn, rice, soybean, wheat) compared to other prescribed fires or grasslands that may be due to differences in the fuel composition, the use of agricultural chemicals, and moisture levels. Overall, FIREX-AQ observations for crop residue fires compared better with previous results in the region than with globally averaged information. The campaign observed even greater variability across EFs than previous studies, suggesting that new methods must be developed to take this into account to improve predictions of the air quality impacts of burning these fuels. Major findings:The FIREX-AQ campaign provided a comprehensive chemical characterization of 53 crop residue and 22 prescribed fires in the Eastern United States to establish regionally specific emission factors. Research revealed that corn residue burns at a significantly higher modified combustion efficiency than rice or soybean residues, leading to distinct emission profiles. The study identified twenty-three chemical species where crop residue emissions differed by over fifty percent from prescribed fires at similar combustion efficiencies, noting higher levels of nitrogen, halogens, and markers related to agricultural chemical use. Conversely, prescribed fires released ten times more monoterpenes than agricultural residues due to the presence of stored plant resins in woody biomass. These findings indicate that fuel-specific and regionally specific data are essential for reducing uncertainty in air quality models that previously relied on global averages." assertion.
• 2023JD039309 comment "Crop residue and prescribed fires emit pollution that impacts air quality. FIREX-AQ provided observations of these emissions to better characterize their variability with a detailed set of chemical observations. These observations showed significant differences in the emissions from burning different crops (corn, rice, soybean, wheat) compared to other prescribed fires or grasslands that may be due to differences in the fuel composition, the use of agricultural chemicals, and moisture levels. Overall, FIREX-AQ observations for crop residue fires compared better with previous results in the region than with globally averaged information. The campaign observed even greater variability across EFs than previous studies, suggesting that new methods must be developed to take this into account to improve predictions of the air quality impacts of burning these fuels. Major findings:The FIREX-AQ campaign provided a comprehensive chemical characterization of 53 crop residue and 22 prescribed fires in the Eastern United States to establish regionally specific emission factors. Research revealed that corn residue burns at a significantly higher modified combustion efficiency than rice or soybean residues, leading to distinct emission profiles. The study identified twenty-three chemical species where crop residue emissions differed by over fifty percent from prescribed fires at similar combustion efficiencies, noting higher levels of nitrogen, halogens, and markers related to agricultural chemical use. Conversely, prescribed fires released ten times more monoterpenes than agricultural residues due to the presence of stored plant resins in woody biomass. These findings indicate that fuel-specific and regionally specific data are essential for reducing uncertainty in air quality models that previously relied on global averages." assertion.
• acs.est.3c05017?ref=article_openPDF comment "Biomass burning particulate matter (BBPM) affects regional air quality and global climate, with impacts expected to continue to grow over the coming years. We show that studies of North American fires have a systematic altitude dependence in measured BBPM normalized excess mixing ratio (NEMR; ΔPM/ΔCO), with airborne and high-altitude studies showing a factor of 2 higher NEMR than ground-based measurements. We report direct airborne measurements of BBPM volatility that partially explain the difference in the BBPM NEMR observed across platforms. We find that when heated to 40− 45 °C in an airborne thermal denuder, 19% of lofted smoke PM1 evaporates. Thermal denuder measurements are consistent with evaporation observed when a single smoke plume was sampled across a range of temperatures as the plume descended from 4 to 2 km altitude. We also demonstrate that chemical aging of smoke and differences in PM emission factors can not fully explain the platformdependent differences. When the measured PM volatility is applied to output from the High Resolution Rapid Refresh Smoke regional model, we predict a lower PM NEMR at the surface compared to the lofted smoke measured by aircraft. These results emphasize the significant role that gas-particle partitioning plays in determining the air quality impacts of wildfire smoke. KEYWORDS: Biomass burning organic aerosol volatility, volatility basis set. Major findings: Research regarding biomass burning organic aerosol volatility reveals a systematic altitude dependence in particulate matter concentrations, with airborne studies recording values twice as high as ground-based measurements. Direct airborne quantification demonstrates that approximately 19% of lofted smoke particulate matter evaporates when subjected to surface-level temperatures. These findings indicate that gas-particle partitioning, rather than chemical aging or initial emission factors, is the primary driver of platform-dependent differences in smoke density. Applying these volatility constraints to regional models reduces predicted surface smoke concentrations by 31%, aligning model outputs more closely with observed ground-level impacts." assertion.
• acs.est.3c05017?ref=article_openPDF comment "Biomass burning particulate matter (BBPM) affects regional air quality and global climate, with impacts expected to continue to grow over the coming years. We show that studies of North American fires have a systematic altitude dependence in measured BBPM normalized excess mixing ratio (NEMR; ΔPM/ΔCO), with airborne and high-altitude studies showing a factor of 2 higher NEMR than ground-based measurements. We report direct airborne measurements of BBPM volatility that partially explain the difference in the BBPM NEMR observed across platforms. We find that when heated to 40− 45 °C in an airborne thermal denuder, 19% of lofted smoke PM1 evaporates. Thermal denuder measurements are consistent with evaporation observed when a single smoke plume was sampled across a range of temperatures as the plume descended from 4 to 2 km altitude. We also demonstrate that chemical aging of smoke and differences in PM emission factors can not fully explain the platformdependent differences. When the measured PM volatility is applied to output from the High Resolution Rapid Refresh Smoke regional model, we predict a lower PM NEMR at the surface compared to the lofted smoke measured by aircraft. These results emphasize the significant role that gas-particle partitioning plays in determining the air quality impacts of wildfire smoke. KEYWORDS: Biomass burning organic aerosol volatility, volatility basis set. Major findings: Research regarding biomass burning organic aerosol volatility reveals a systematic altitude dependence in particulate matter concentrations, with airborne studies recording values twice as high as ground-based measurements. Direct airborne quantification demonstrates that approximately 19% of lofted smoke particulate matter evaporates when subjected to surface-level temperatures. These findings indicate that gas-particle partitioning, rather than chemical aging or initial emission factors, is the primary driver of platform-dependent differences in smoke density. Applying these volatility constraints to regional models reduces predicted surface smoke concentrations by 31%, aligning model outputs more closely with observed ground-level impacts." assertion.
• assertion comment "I retract this role, bacause it is not relevant for this workshop." assertion.
• trrust comment "A manually curated database of human and mouse transcriptional regulatory networks. Contains 8427 human transcriptional regulatory interactions including 2428 activation, 1581 repression, and 4418 unknown interactions." assertion.
• dataset comment "1500 synthetic networks generated for benchmarking QOMIC algorithm. Networks vary in size (200-1000 nodes), density (average degree 2-10), and activation ratio (0.2, 0.5, 0.8) across four motif topologies: cascade, FFL, bifan, and biparallel." assertion.
• DANS-DataStationSSH-SubjectList comment "This list contains the controlled vocabulary Subject used in the DANS Data Station Social Sciences and Humanities (SSH)." assertion.
• DANS_DataStationPolicy comment "The scope of the DANS Data Stations Policy (“the Policy”) is limited to datasets for which DANS performs ingestion, curation, archiving, long-term preservation, and dissemination. Such datasets are stored and managed in the repository services referred to as a ‘DANS Data Station’, which combines a public facing, domain specific repository based on Dataverse software where the datasets are managed and made accessible, and a service referred to as ‘the Vault’ where datasets are archived for long-term preservation. The Policy does not consider archiving and preservation of other materials, such as DANS’s web pages, internal and external documents, and digital objects in any other services that DANS provides. The Policy governs the obligations, responsibilities, and expectations of the role players." assertion.
• 2024 comment "Extensive airborne measurements from the FIREX-AQ campaign established new parameterizations for US wildfire emissions by correlating primary pollutant levels with modified combustion efficiency. Researchers demonstrated that the sum of primary non-methane organic gas (NMOG) mixing ratios maintains a near-perfect correlation with carbon monoxide ($R^2$ = 0.98), identifying CO as a robust proxy for initializing organic gas emissions in models. Nitrogen-containing species correlate more effectively with nitrogen dioxide and black carbon than with carbon monoxide, reflecting their origin in high-temperature flaming combustion. The findings indicate that nitrogen dioxide typically represents over half of the total reactive nitrogen in fresh plumes, and the ratio of reactive nitrogen to organic gases increases exponentially with combustion efficiency. These parameterizations provide more accurate boundary conditions for predicting the formation of secondary pollutants like ozone downwind of fire events." assertion.
• 2024 comment "Extensive airborne measurements from the FIREX-AQ campaign established new parameterizations for US wildfire emissions by correlating primary pollutant levels with modified combustion efficiency. Researchers demonstrated that the sum of primary non-methane organic gas (NMOG) mixing ratios maintains a near-perfect correlation with carbon monoxide ($R^2$ = 0.98), identifying CO as a robust proxy for initializing organic gas emissions in models. Nitrogen-containing species correlate more effectively with nitrogen dioxide and black carbon than with carbon monoxide, reflecting their origin in high-temperature flaming combustion. The findings indicate that nitrogen dioxide typically represents over half of the total reactive nitrogen in fresh plumes, and the ratio of reactive nitrogen to organic gases increases exponentially with combustion efficiency. These parameterizations provide more accurate boundary conditions for predicting the formation of secondary pollutants like ozone downwind of fire events." assertion.
• s10640-023-00813-2 comment "There is growing recognition of the connection between ecosystem conservation and human health. For example, protection of tropical forests can affect the spread of infectious diseases, water quality, and dietary diversity, while forest loss can have important consequences for respiratory health due to the use of fire for converting land to alternative uses in many countries. Studies demonstrating links between ecosystems and health often conclude with recommendations to expand policies that protect natural ecosystems. However, there is little empirical evidence on the extent to which conservation policies actually deliver health benefits when they are implemented in real contexts. We estimate the effects of protected areas (PAs), the dominant type of conservation policy, on hospitalizations for respiratory illness in the Brazilian Amazon biome. We find that doubling upwind PAs reduces PM2.5 by 10% and respiratory hospitalizations by 7% in the months of most active biomass burning. Brazil has an extensive network of PAs, but investments in management and enforcement have declined in recent years. Forest fires have increased dramatically over the same period. We estimate that the value of the health benefits exceed current average expenditures on PA management for the 1/3 of PAs with the largest local populations, although not for PAs in more remote locations. Our findings highlight how quantifying the contributions to the wellbeing of local populations can support conservation objectives, even if global environmental benefits are not a high priority for decision makers. Major findings: Doubling the area of upwind PAs results in a 10% reduction in $PM_{2.5}$ and a 7% decrease in hospital admissions during active biomass burning months. These health improvements are primarily driven by reduced cases of pneumonia and acute upper respiratory infections among children under 15 years old. For the most populous regions, the economic value of avoided hospitalizations exceeds the direct costs of managing and enforcing protected area boundaries." assertion.
• s10640-023-00813-2 comment "There is growing recognition of the connection between ecosystem conservation and human health. For example, protection of tropical forests can affect the spread of infectious diseases, water quality, and dietary diversity, while forest loss can have important consequences for respiratory health due to the use of fire for converting land to alternative uses in many countries. Studies demonstrating links between ecosystems and health often conclude with recommendations to expand policies that protect natural ecosystems. However, there is little empirical evidence on the extent to which conservation policies actually deliver health benefits when they are implemented in real contexts. We estimate the effects of protected areas (PAs), the dominant type of conservation policy, on hospitalizations for respiratory illness in the Brazilian Amazon biome. We find that doubling upwind PAs reduces PM2.5 by 10% and respiratory hospitalizations by 7% in the months of most active biomass burning. Brazil has an extensive network of PAs, but investments in management and enforcement have declined in recent years. Forest fires have increased dramatically over the same period. We estimate that the value of the health benefits exceed current average expenditures on PA management for the 1/3 of PAs with the largest local populations, although not for PAs in more remote locations. Our findings highlight how quantifying the contributions to the wellbeing of local populations can support conservation objectives, even if global environmental benefits are not a high priority for decision makers. Major findings: Doubling the area of upwind PAs results in a 10% reduction in $PM_{2.5}$ and a 7% decrease in hospital admissions during active biomass burning months. These health improvements are primarily driven by reduced cases of pneumonia and acute upper respiratory infections among children under 15 years old. For the most populous regions, the economic value of avoided hospitalizations exceeds the direct costs of managing and enforcing protected area boundaries." assertion.
• s10584-023-03648-4 comment "Rangeland social-ecological systems (SESs), which make up vast tracts of Earth’s terrestrial surface, are facing unprecedented change—from climate change and vegetation transitions to large-scale shifts in human land use and changing social and economic conditions. Understanding how people who manage and depend on rangeland resources are adapting to change has been the focus of a rapidly growing body of research, which has the potential to provide important insights for climate change adaptation policy and practice. Here, we use quantitative, qualitative, and bibliometric analyses to systematically review the scope, methods, and findings of 56 studies that examine the social dimensions of adaptation in rangeland SESs. Our review focuses on studies within the climate adaptation, adaptive capacity, and adaptive decision-making sub-fields, finding that this body of research is highly diverse in its disciplinary roots and theoretical origins, and therefore uses a wide range of frameworks and indicators to evaluate adaptation processes. Bibliometric analyses revealed that the field is fragmented into distinct scholarly communities that use either adaptive capacity or adaptive decision-making frameworks, with a lack of cross-field citation. Given the strengths (and weaknesses) inherent in each sub-field, this review suggests that greater cross-pollination across the scholarship could lead to new insights, particularly for capturing cross-scale interactions related to adaptation on rangelands. Results also showed that a majority of studies that examine adaptation in either “ranching” or “rangeland” systems are geographically concentrated in few, high-income countries (i.e., USA, Australia, China), demonstrating a need to extend future research efforts to understudied regions of the globe with rangeland-based livelihoods. Finally, our review highlights the need for more translational rangeland science, where policy- and practice-relevant frameworks evaluating adaptation in rangeland SESs might be developed by co-producing research working with rangeland communities. Major findings: The findings indicate that nitrogen dioxide typically represents over half of the total reactive nitrogen in fresh plumes, and the ratio of reactive nitrogen to organic gases increases exponentially with combustion efficiency. These parameterizations provide more accurate boundary conditions for predicting the formation of secondary pollutants like ozone downwind of fire events." assertion.
• s10584-023-03648-4 comment "Rangeland social-ecological systems (SESs), which make up vast tracts of Earth’s terrestrial surface, are facing unprecedented change—from climate change and vegetation transitions to large-scale shifts in human land use and changing social and economic conditions. Understanding how people who manage and depend on rangeland resources are adapting to change has been the focus of a rapidly growing body of research, which has the potential to provide important insights for climate change adaptation policy and practice. Here, we use quantitative, qualitative, and bibliometric analyses to systematically review the scope, methods, and findings of 56 studies that examine the social dimensions of adaptation in rangeland SESs. Our review focuses on studies within the climate adaptation, adaptive capacity, and adaptive decision-making sub-fields, finding that this body of research is highly diverse in its disciplinary roots and theoretical origins, and therefore uses a wide range of frameworks and indicators to evaluate adaptation processes. Bibliometric analyses revealed that the field is fragmented into distinct scholarly communities that use either adaptive capacity or adaptive decision-making frameworks, with a lack of cross-field citation. Given the strengths (and weaknesses) inherent in each sub-field, this review suggests that greater cross-pollination across the scholarship could lead to new insights, particularly for capturing cross-scale interactions related to adaptation on rangelands. Results also showed that a majority of studies that examine adaptation in either “ranching” or “rangeland” systems are geographically concentrated in few, high-income countries (i.e., USA, Australia, China), demonstrating a need to extend future research efforts to understudied regions of the globe with rangeland-based livelihoods. Finally, our review highlights the need for more translational rangeland science, where policy- and practice-relevant frameworks evaluating adaptation in rangeland SESs might be developed by co-producing research working with rangeland communities. Major findings: The findings indicate that nitrogen dioxide typically represents over half of the total reactive nitrogen in fresh plumes, and the ratio of reactive nitrogen to organic gases increases exponentially with combustion efficiency. These parameterizations provide more accurate boundary conditions for predicting the formation of secondary pollutants like ozone downwind of fire events." assertion.
• s10584-023-03648-4 comment "Rangeland social-ecological systems (SESs), which make up vast tracts of Earth’s terrestrial surface, are facing unprecedented change—from climate change and vegetation transitions to large-scale shifts in human land use and changing social and economic conditions. Understanding how people who manage and depend on rangeland resources are adapting to change has been the focus of a rapidly growing body of research, which has the potential to provide important insights for climate change adaptation policy and practice. Here, we use quantitative, qualitative, and bibliometric analyses to systematically review the scope, methods, and findings of 56 studies that examine the social dimensions of adaptation in rangeland SESs. Our review focuses on studies within the climate adaptation, adaptive capacity, and adaptive decision-making sub-fields, finding that this body of research is highly diverse in its disciplinary roots and theoretical origins, and therefore uses a wide range of frameworks and indicators to evaluate adaptation processes. Bibliometric analyses revealed that the field is fragmented into distinct scholarly communities that use either adaptive capacity or adaptive decision-making frameworks, with a lack of cross-field citation. Given the strengths (and weaknesses) inherent in each sub-field, this review suggests that greater cross-pollination across the scholarship could lead to new insights, particularly for capturing cross-scale interactions related to adaptation on rangelands. Results also showed that a majority of studies that examine adaptation in either “ranching” or “rangeland” systems are geographically concentrated in few, high-income countries (i.e., USA, Australia, China), demonstrating a need to extend future research efforts to understudied regions of the globe with rangeland-based livelihoods. Finally, our review highlights the need for more translational rangeland science, where policy- and practice-relevant frameworks evaluating adaptation in rangeland SESs might be developed by co-producing research working with rangeland communities. Major findings: The findings indicate that nitrogen dioxide typically represents over half of the total reactive nitrogen in fresh plumes, and the ratio of reactive nitrogen to organic gases increases exponentially with combustion efficiency. These parameterizations provide more accurate boundary conditions for predicting the formation of secondary pollutants like ozone downwind of fire events." assertion.
• egusphere-2023-3114 comment "The magnitude and evolution of Black Carbon (BC) and Brown Carbon (BrC) absorption with time remain unclear, causing uncertainty in climate models. Using data from the WE-CAN airborne measurement campaign, we show that absorption of BC from wildfire is relatively constant over time. BrC tends to be darker in more oxidated smoke plumes, challenging the idea that oxidation causes bleaching. We show that water-soluble BrC contributes 23 % of the total absorption at 660 nm." assertion.
• egusphere-2023-3114 comment "The magnitude and evolution of Black Carbon (BC) and Brown Carbon (BrC) absorption with time remain unclear, causing uncertainty in climate models. Using data from the WE-CAN airborne measurement campaign, we show that absorption of BC from wildfire is relatively constant over time. BrC tends to be darker in more oxidated smoke plumes, challenging the idea that oxidation causes bleaching. We show that water-soluble BrC contributes 23 % of the total absorption at 660 nm." assertion.
• assertion comment "tested retracting." assertion.
• rio.11.e168765 comment "This framing positions biodiversity loss within the broader context of interconnected global challenges, emphasizing the need for integrated solutions rather than siloed approaches." assertion.
• rio.11.e168765 comment "The paper explicitly positions STI as essential infrastructure for achieving post-2030 sustainability goals, not merely as tools but as central enablers of transformation." assertion.
• rio.11.e168765 comment "This statement challenges the traditional treatment of biodiversity as a separate environmental concern, positioning it as fundamental infrastructure for human wellbeing." assertion.
• rio.11.e168765 comment "Digital twins are presented as key tools for evidence-based conservation decision-making, bridging the gap between scientific modeling and policy implementation." assertion.
• rio.11.e168765 comment "This acknowledges the essential role of indigenous knowledge systems in biodiversity conservation, aligning with CARE principles and access and benefit sharing frameworks." assertion.
• rio.11.e168765 comment "The concept of a Biodiversity Supergraph represents an ambitious vision for integrating biodiversity data across domains using semantic web technologies." assertion.
• rio.11.e168765 comment "This outlines the strategic vision for international collaboration, positioning European research infrastructures as potential nodes in a global biodiversity science network." assertion.
• rio.11.e168765 comment "This policy recommendation explicitly links biodiversity to the broader UN Pact for the Future agenda, advocating for biodiversity as a core pillar of sustainable development." assertion.
• rio.11.e168765 comment "The paper originates from a European network of Research Infrastructures coordinated by LifeWatch ERIC with headquarters in Seville, Spain." assertion.
• rio.11.e168765 comment "LifeWatch ERIC statutory seat and ICT e-Infrastructure Technical Office location, coordinating the network described in the paper." assertion.
• rio.11.e168765 comment "Location of the 79th United Nations General Assembly Science Summit where the network presented its workshop." assertion.
• rio.11.e168765 comment "Location where the Kunming-Montreal Global Biodiversity Framework was adopted at COP15 in December 2022." assertion.
• rio.11.e176120 comment "This preamble establishes the multi-stakeholder commitment from European research infrastructures to collaborate on One Health challenges. It defines the scope of signatories and their shared purpose." assertion.
• rio.11.e176120 comment "This statement frames the key One Health challenges as interconnected and climate-amplified, establishing the rationale for integrated approaches across environmental, animal, and human health domains." assertion.
• rio.11.e176120 comment "This defines the One Health philosophy as requiring societal-level engagement and systemic thinking, moving beyond siloed disciplinary approaches to health challenges." assertion.
• rio.11.e176120 comment "This commitment to co-creation and open science principles reflects the modern research infrastructure approach emphasizing stakeholder engagement and data sharing." assertion.
• rio.11.e176120 comment "This statement links data quality to policy effectiveness and emphasizes that citizen engagement improves policy implementation - a key principle for evidence-based policymaking." assertion.
• rio.11.e176120 comment "Crete is the location where the One Health Declaration was developed and signed. The assembly was hosted by IMBBC-HCMR, a key research institute in marine biology." assertion.
• rio.11.e176120 comment "IMBBC-HCMR in Heraklion is the host institution where the Crete Declaration assembly took place. The HCMR is a major Greek marine research center." assertion.
• rio.11.e176120 comment "The Declaration's scope is European, involving research infrastructures, organizations, and projects across Europe committed to One Health collaboration." assertion.
• BDJ.10.e77516 comment "This establishes the ecological and economic significance of studying this invasive species. The categorization as 'worst invasive' justifies extensive research into its trophic ecology and impacts, and positions the dataset as a critical resource for invasion biology research in the Mediterranean." assertion.
• BDJ.10.e77516 comment "Provides methodological foundation for the dataset. The dual-isotope approach is powerful: δ13C traces carbon flow from basal sources to consumers, while δ15N indicates trophic position. This combination is now standard for invasion ecology studies investigating trophic impacts." assertion.
• BDJ.10.e77516 comment "Highlights both spatial and ontogenetic variation in blue crab trophic ecology. This finding supports the need for individual-based (rather than population-averaged) isotopic data, justifying the structure of this dataset which preserves individual measurements." assertion.
• BDJ.10.e77516 comment "Documents the trophic flexibility of the species, which is key to understanding its invasion success. This dietary breadth allows adaptation to local food availability in invaded ecosystems and may facilitate exploitation of multiple trophic pathways." assertion.
• BDJ.10.e77516 comment "Establishes the functional importance of the blue crab in its native range, providing a framework for understanding potential impacts in invaded Mediterranean ecosystems. If it maintains keystone functions in invaded systems, ecosystem-level effects may be substantial." assertion.
• BDJ.10.e77516 comment "Summarizes the scope of the dataset. The inclusion of prey data (primarily bivalves) enables calculation of trophic position using standardized baseline species, while the geographic breadth allows comparative analyses across the Mediterranean invasion front." assertion.
• BDJ.10.e77516 comment "Documents the baseline species selection and assigned trophic levels used for calculating blue crab trophic position. These assignments follow established ecological knowledge and enable standardized trophic position estimates across sites with different baseline species." assertion.
• BDJ.10.e77516 comment "Identifies a knowledge gap that this dataset helps address. Despite the blue crab's well-documented ecological importance in native ecosystems, there has been insufficient research on its trophic role in Mediterranean invaded systems. This dataset provides the foundation for such analyses." assertion.
• BDJ.10.e77516 comment "Westernmost sampling site in the dataset. This Spanish estuary represents the western extent of blue crab invasion in the Mediterranean, sampled in 2016." assertion.
• BDJ.10.e77516 comment "Italian estuary site on the Tyrrhenian coast where blue crab populations were sampled in 2019, representing the most recent sampling event in the dataset." assertion.
• BDJ.10.e77516 comment "Coastal lagoon in the Apulia region of Italy where established blue crab populations were sampled in 2016." assertion.
• BDJ.10.e77516 comment "Semi-enclosed lagoon near Taranto, Italy, representing one of the earliest sampling sites (2014) in the dataset." assertion.
• BDJ.10.e77516 comment "Coastal lagoon in the Apulia region sampled in 2014, part of a cluster of Italian sites providing detailed spatial coverage." assertion.
• BDJ.10.e77516 comment "Coastal lagoon near Lecce, Italy, sampled in 2016. Part of the intensive sampling effort in the Apulia region." assertion.
• BDJ.10.e77516 comment "Coastal lagoon ecosystem in the Salento peninsula, Italy, sampled in 2014." assertion.
• BDJ.10.e77516 comment "Seventh Italian sampling site, completing the comprehensive coverage of Italian coastal ecosystems invaded by blue crab." assertion.
• BDJ.10.e77516 comment "Northernmost sampling site in the dataset, located in the South Eastern Adriatic. Represents the northern extent of blue crab invasion documented in this study. Sampled in 2015." assertion.
• BDJ.10.e77516 comment "Southernmost sampling site in the dataset, located on the western coast of Greece. Sampled in 2016." assertion.
• BDJ.10.e77516 comment "Coastal ecosystem in northern Greece (Thermaikos Gulf region), representing the only non-lagoon coastal sampling site in the dataset. Sampled in 2016." assertion.
• BDJ.10.e77516 comment "Easternmost sampling site in the dataset, located on the Turkish Aegean coast. Sampled in 2017, extending the geographical coverage to the eastern Mediterranean." assertion.
• BDJ.10.e77516 comment "Overall geographical extent of the blue crab isotopic dataset, spanning from Spain in the west to Turkey in the east, covering coastal and transitional ecosystems where established populations of Callinectes sapidus were investigated between 2014-2019." assertion.
• 9CD2907F-8F44-4DF6-9070-6B21E1991B94 comment "Individual-based dataset of carbon (δ13C) and nitrogen (δ15N) isotopic values for the invasive Atlantic blue crab and its potential prey in Mediterranean waters. Contains 360 records: 236 blue crab isotopic values and 224 prey species values from 12 locations across 5 countries (Spain, Italy, Croatia, Greece, Turkey) collected between 2014-2019." assertion.
• BDJ.11.e101464 comment "This establishes the global importance of studying biological invasions. The paper aims to address this threat by providing comprehensive biodiversity datasets that enable assessment of invasion impacts on native species." assertion.
• BDJ.11.e101464 comment "This positions Italy and the Mediterranean as a critical region for invasion ecology research. The paper's datasets are therefore highly relevant for understanding invasion patterns in one of the world's most invaded marine regions." assertion.
• BDJ.11.e101464 comment "Italy's geographic position at the intersection of multiple marine subregions makes it an ideal location for monitoring alien species introductions and studying invasion pathways across the Mediterranean." assertion.
• BDJ.11.e101464 comment "This explains why the paper includes a separate dataset for transitional waters. These ecosystems require special attention in invasion monitoring due to their higher vulnerability compared to open marine environments." assertion.
• BDJ.11.e101464 comment "This identifies maritime traffic as the primary vector for alien species introductions in Italy, providing actionable information for management and policy interventions focused on shipping routes and port biosecurity." assertion.
• BDJ.11.e101464 comment "This justifies the paper's approach of including both alien AND native species in the datasets, rather than focusing solely on aliens. Understanding native community structure is essential for predicting invasion impacts." assertion.
• BDJ.11.e101464 comment "The expert validation step adds significant credibility to these datasets. Having specialists verify occurrence records and alien status assignments ensures high data quality suitable for research and management applications." assertion.
• BDJ.11.e101464 comment "This demonstrates the interoperability and practical utility of the datasets. Their compatibility with LifeWatch ERIC's analytical workflows means they can be immediately used for standardized vulnerability assessments across European biotopes." assertion.
• BDJ.11.e101464 comment "Primary study area covering marine (91 sites) and transitional waters (23 sites) along 7,000 km of Italian coastline. Encompasses Ligurian, Tyrrhenian, Ionian and Adriatic Seas." assertion.
• BDJ.11.e101464 comment "Regional context for the study. The Mediterranean has experienced the highest rate of biological introductions over the last five decades." assertion.
• BDJ.11.e101464 comment "One of four Italian sea areas covered by the marine dataset sampling locations." assertion.
• BDJ.11.e101464 comment "One of four Italian sea areas covered by the marine dataset, including sampling sites along Sardinia and western Italy." assertion.
• BDJ.11.e101464 comment "One of four Italian sea areas covered. Includes important transitional water ecosystems like the Venice Lagoon and numerous coastal sites from Friuli Venezia Giulia to Apulia." assertion.
• BDJ.11.e101464 comment "One of four Italian sea areas covered, including southern Italy and Sicily sampling locations." assertion.
• BDJ.11.e101464 comment "Major pathway for Lessepsian migration of species from the Red Sea and Indo-Pacific into the Mediterranean, contributing to the invasion patterns observed in Italy." assertion.
• 30d8844e-1774-4c63-89c4-4d858f88317d comment "Dataset containing over 12,200 alien and native species occurrence records distributed across 91 marine sites and seven EUNIS habitats (level 2) along the Italian coast. The dataset includes taxonomic information (species, genus, family, order, class, phylum, kingdom), sampling event details (date, location, coordinates), EUNIS habitat classification, and alien/native status for each record. Records were collected from 1985 to 2015 and validated by Italian taxonomic experts for phytoplankton, algae, invertebrates, and fish." assertion.
• 98914415-765c-4650-b272-b16793231e8a comment "Dataset containing over 3,800 alien and native species occurrence records distributed across 23 transitional waters sites and four EUNIS habitats (levels 2 and 3) along the Italian coast. The dataset includes taxonomic information, sampling event details, EUNIS habitat classification, and alien/native status for each record. Transitional ecosystems covered include estuaries, lagoons, and coastal lakes. Records span from 1940 to 2015 and were validated by Italian taxonomic experts." assertion.

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