Reproducibility crisis and gravitation towards a consensus in ocean acidification research

[ad_1]

  • Schooler, J. Unpublished results hide the decline effect. Nature 470, 437 (2011).

    Article 
    CAS 

    Google Scholar     

  • Fang, F. C. & Casadevall, A. Competitive science: is competition ruining science? Infect. Immun. 83, 1229–1233 (2015).

    Article 
    CAS 

    Google Scholar     

  • Clements, J. C., Sundin, J., Clark, T. D. & Jutfelt, F. Meta-analysis reveals an extreme ‘decline effect’ in the impacts of ocean acidification on fish behavior. PLoS Biol. 20, e3001511 (2022).

    Article 
    CAS 

    Google Scholar     

  • Gattuso, J. P., Frankignoulle, M., Bourge, I., Romaine, S. & Buddemeier, R. W. Effect of calcium carbonate saturation of seawater on coral calcification. Glob. Planet. Change 18, 37–46 (1998).

    Article 

    Google Scholar     

  • Riebesell, U. et al. Reduced calcification of marine plankton in response to increased atmospheric CO2. Nature 407, 364–367 (2000).

    Article 
    CAS 

    Google Scholar     

  • Zondervan, I., Zeebe, R. E., Rost, B. & Riebesell, U. Decreasing marine biogenic calcification: a negative feedback on rising atmospheric (p_{{mathrm{co}}_2}). Glob. Biogeochem. Cycles 15, 507–516 (2001).

    Article 
    CAS 

    Google Scholar     

  • Feely, R. A. et al. Impact of anthropogenic CO2 on the CaCO3 system in the oceans. Science 305, 362–366 (2004).

    Article 
    CAS 

    Google Scholar     

  • Orr, J. C. et al. Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437, 681–686 (2005).

    Article 
    CAS 

    Google Scholar     

  • Leung, J. Y. S., Zhang, S. & Connell, S. D. Is ocean acidification really a threat to marine calcifiers? A systematic review and meta-analysis of 980+ studies spanning two decades. Small 18, 2107407 (2022).

    Article 
    CAS 

    Google Scholar     

  • Leung, J. Y. S. et al. Calcifiers can adjust shell building at the nanoscale to resist ocean acidification. Small 16, 2003186 (2020).

    Article 
    CAS 

    Google Scholar     

  • Cornwall, C. E. et al. Resistance of corals and coralline algae to ocean acidification: physiological control of calcification under natural pH variability. Proc. R. Soc. B 285, 20181168 (2018).

    Article 

    Google Scholar     

  • Rajan, K. C., Meng, Y., Yu, Z., Roberts, S. B. & Vengatesen, T. Oyster biomineralization under ocean acidification: from genes to shell. Glob. Change Biol. 27, 3779–3797 (2021).

    Article 

    Google Scholar     

  • Liu, Y., Eagle, R. A., Aciego, S. M., Gilmore, R. E. & Ries, J. B. A coastal coccolithophore maintains pH homeostasis and switches carbon sources in response to ocean acidification. Nat. Commun. 9, 2857 (2018).

    Article 

    Google Scholar     

  • Wahl, M. et al. Macroalgae may mitigate ocean acidification effects on mussel calcification by increasing pH and its fluctuations. Limnol. Oceanogr. 63, 3–21 (2018).

    Article 
    CAS 

    Google Scholar     

  • Lau, J., Schmid, C. H. & Chalmers, T. C. Cumulative meta-analysis of clinical trials builds evidence for exemplary medical care. J. Clin. Epidemiol. 48, 45–57 (1995).

    Article 
    CAS 

    Google Scholar     

  • Pietschnig, J., Voracek, M. & Formann, A. K. Mozart effect—Shmozart effect: a meta-analysis. Intelligence 38, 314–323 (2010).

    Article 

    Google Scholar     

  • Pietschnig, J., Penke, L., Wicherts, J. M., Zeiler, M. & Voracek, M. Meta-analysis of associations between human brain volume and intelligence differences: how strong are they and what do they mean? Neurosci. Biobehav. Rev. 57, 411–432 (2015).

    Article 

    Google Scholar     

  • Connell, S. D. et al. How ocean acidification can benefit calcifiers. Curr. Biol. 27, R95–R96 (2017).

    Article 
    CAS 

    Google Scholar     

  • Goldenberg, S. U. et al. Ecological complexity buffers the impacts of future climate on marine consumers. Nat. Clim. Change 8, 229–233 (2018).

    Article 

    Google Scholar     

  • Leung, J. Y. S. et al. How calorie-rich food could help marine calcifiers in a CO2-rich future. Proc. R. Soc. B 286, 20190757 (2019).

    Article 
    CAS 

    Google Scholar     

  • Cornwall, C. E. et al. Understanding coralline algal responses to ocean acidification: meta-analysis and synthesis. Glob. Change Biol. 28, 362–374 (2022).

    Article 
    CAS 

    Google Scholar     

  • Cornwall, C. E. & Hurd, C. L. Experimental design in ocean acidification research: problems and solutions. ICES J. Mar. Sci. 73, 572–581 (2015).

    Article 

    Google Scholar     

  • Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl Acad. Sci. USA 118, e2015265118 (2021).

    Article 
    CAS 

    Google Scholar     

  • Mlinarić, A., Horvat, M. & Smolčić, V. S. Dealing with the positive publication bias: why you should really publish your negative results. Biochem. Med. 27, 030201 (2017).

    Article 

    Google Scholar     

  • Browman, H. I. Applying organized scepticism to ocean acidification research. ICES J. Mar. Sci. 73, 529–536 (2016).

    Article 

    Google Scholar     

  • Leung, J. Y. S., Harvey, B. P. & Russell, B. D. Editorial: fitness of marine calcifiers in the future acidifying ocean. Front. Mar. Sci. 8, 752635 (2021).

    Article 

    Google Scholar     

  • McPherson, M., Smith-Lovin, L. & Cook, J. M. Birds of a feather: homophily in social networks. Annu. Rev. Socio 27, 415–444 (2001).

    Article 

    Google Scholar     

  • Norberg, J., Blenckner, T., Cornell, S. E., Petchey, O. L. & Hillebrand, H. Failures to disagree are essential for environmental science to effectively influence policy development. Ecol. Lett. 25, 1075–1093 (2022).

    Article 

    Google Scholar     

  • Kahneman, D. & Klein, G. Conditions for intuitive expertise: a failure to disagree. Am. Psychol. 64, 515–526 (2009).

    Article 

    Google Scholar     

  • Chamberlain, S. A., Bronstein, J. L. & Rudgers, J. A. How context dependent are species interactions? Ecol. Lett. 17, 881–890 (2014).

    Article 

    Google Scholar     

  • Shanteau, J. How much information does an expert use? Is it relevant? Acta Psychol. 81, 75–86 (1992).

    Article 

    Google Scholar     

  • Protzko, J. et al. 2020. High replicability of newly-discovered social–behavioral findings is achievable. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/n2a9x (2020).

  • Amaral, O. B. & Neves, K. Reproducibility: expect less of the scientific paper. Nature 597, 329–331 (2021).

    Article 
    CAS 

    Google Scholar     

    • [ad_2]

    Source link

    Enabling pathways for sustainable livelihoods in planned relocation

    [ad_1]

    Our research approach consisted of four steps: (1) selection of outcome and causal conditions; (2) selection of relevant case studies; (3) data collection and coding of case study characteristics; and (4) comparative analysis using fsQCA.

    Selection of outcome and causal conditions

    We first drew on relevant literature to understand how past studies have measured outcomes and causal conditions in planned relocations. While there is no consensus about which conceptual framework is most applicable for assessing hazard-related relocation outcomes, a range of approaches were identified in the literature from diverse disciplinary perspectives (Supplementary Section 3). Each conceptual framework has advantages and disadvantages, as most were developed for other purposes. Some frameworks are better suited to assess outcomes at the level of a whole community, such as livability, whereas others are more tailored to individual scales, such as well-being. Some frameworks miss key dimensions specific to hazard-related relocation outcomes, such as cultural aspects, governance or exposure reduction. Many of these frameworks were developed to understand outcomes in analogous development resettlement, forced migration or disaster recovery contexts and have limited applicability for climate or hazard-related planned relocation cases. Here, we selected the SLA27 to understand how access to various assets changes as a result of relocation22. SLA is well suited as an outcome measure because it: (1) can be used at the community scale, (2) enables comparison across cases with different baselines and (3) allows for multidimensional consideration of human needs (natural, social, financial, human and physical, with the addition of cultural dimensions to make SLA+19,28).

    For causal conditions, we reviewed literature to identify diverse planning, hazard, community stakeholder and governance factors that past research suggests impact relocation outcomes (Supplementary Section 4). In considering these factors, we narrowed our focus to a subset that met three criteria: (1) suggested to be important for sustainable livelihood outcomes specifically, (2) consistently measurable across these 14 cases and (3) viable areas for possible planning intervention. Table 1 in Supplementary Section 4 provides details regarding factor selection.

    Case selection

    Until recently, a global database of hazard-related planned relocation cases did not exist, constituting an obstacle to comparative research. In this analysis, we draw from a new database of planned relocation cases initiated after 1970 published by the Platform on Disaster Displacement and the Kaldor Center in 202114. While we were revising this manuscript, a mapping of success typologies in managed retreat programmes was published9, providing another compilation of cases for future comparative analyses.

    From the global database, we selected planned relocation cases that met certain selection criteria. Case selection involves trade-offs between more cases for increased sample and fewer cases to ensure consistency across cases and meaningful comparisons. Our case criteria were: (1) the physical relocation has already occurred (‘completed’ in the database), (2) relocation from one site of origin to one destination (‘type A’ in this database14), (3) one of the identified natural hazards was floods (including in the context of riverine settings, coastal erosion and tsunamis) and (4) adequate documentation. When this search was conducted in January 2021, the database included 73 cases identified from the initial mapping of English language literature that met these first three conditions. (Note that after a June 2021 review of Spanish, French and Portuguese literature, the database now has 14 additional cases meeting criteria (1) to (3) for a total of 87 cases.) However, most (81%) of these original 73 cases did not meet the criterion of adequate documentation, which were as follows: (1) at least one piece of evidence for nearly all six SLA+ suboutcome conditions and five relocation planning decision factors and (2) at least one article using a consistent data collection method of interviews with key stakeholders. We recognize that the adequate documentation criterion may have biased selection towards cases in the developed and English-speaking world and cases that were more well-known and thus more well-resourced, which constitutes a limitation to this research. We ultimately selected the 14 cases of planned relocation that met these criteria, varying in completion year between 1981 and 2016.

    Data collection and coding of causal and outcome conditions per case

    To gain in-depth knowledge of all 14 selected planned relocations, the coding team (E.R.B. and A.B.) conducted case study literature reviews through: document identification, data extraction by theme, content analysis and calibration and narrative synthesis.

    Document identification

    In January–March 2021, we identified diverse documents—including academic articles, white papers, government planning materials and media articles—through systematic searches on Google Scholar, Google and Google News. We used these search engines, rather than Scopus or Web of Science because we wanted to capture evidence and develop case knowledge about relocation outcomes and planning factors from documents produced by government actors (for example, US Army Corps of Engineers), the media (for example, radio shows and local newspapers) and community members (for example, blogs and YouTube videos) in addition to academic researchers (for example, peer-reviewed papers and unpublished theses). To identify relevant and diverse documents, we used search terms ‘Village/Community of origin, Country’ and ‘Relocation’ or ‘Resettlement’ or ‘Retreat’ and considered the top 25 results in each search engine. We scanned each document and selected only those where the discussion of the relocation case was substantive; documents containing one to two sentences about the case were not included. All documents referenced for case descriptions and calibration decisions are listed in Table 1 of Supplementary Section 1.

    Data extraction by theme

    Using the qualitative data analysis tool NVivo (QSR International), the coding team then systematically extracted all relevant data per relocation case, which were categorized into themes pertaining to background context, planning decision factors and outcomes. For background, we considered evidence about the hazard(s) involved, the process duration (years of relocation decision initiation and completion of the physical move), the locations origin and destination site and additional geographic and socioeconomic context. For relocation planning decisions, we considered evidence about community engagement, distance, scale, speed and transfer dynamics (see Table 1 for definitions). For outcomes, we considered evidence about relocated people’s change in access to assets required for SLA+, including physical, economic, natural, human, social and cultural categories (see Table 1 for definitions, aligned with the SLA+ assets adapted from previous studies19,27,28). To ensure robustness, we used NVivo’s percentage agreement calculator and found an average of 84% agreement for the extraction of relevant outcome and causal conditions across the two members of the coder team.

    For some cases, information about all outcome and causal conditions was not available in the reviewed documents. If we were unsure about a specific calibration decision or if less information was available, we contacted the authors of reviewed documents for further information and verification. We triangulated with Google Earth to verify the distances between origin and destination sites and used these estimates if there was a discrepancy. While some cases have experienced multiple relocations over time, we considered only the distance between the most recent origin and destination sites.

    Content analysis and calibration

    Next, we undertook a content analysis of the available data for each relocation decision factor and outcome category. For each of the six outcome categories, we made evaluative judgments of negative or positive valence of the evidence following the approach of refs. 19,28. For example, we coded increased access to electricity through the installation of solar panels in the destination site as a positive physical outcome, while we coded a decrease in access to health centres as a negative human outcome. On the basis of theoretically informed and predetermined calibration criteria (Table 1 of Supplementary Section 2), we aggregated available evidence and assigned each case a score per outcome category and relocation planning decision factor. Cases had differing quantities of evidence for each category, which we accounted for through a six-point scoring system based on percentages of available evidence (discussed below). To ensure robustness, two members of the research team undertook the coding procedure for each case independently. Then, both team members collectively reviewed each case, allowing for a consensus interpretation through ‘negotiated agreement’ to establish intercoder reliability57.

    Narrative synthesis

    After coding all the outcome and relocation planning conditions, we then summarized our coding into narratives for each of the 14 cases. Supplementary Section 1 contains information on all cases, including a short description, replication evidence for calibration of causal and outcome conditions and a list of references for each case, while Supplementary Section 2 summarizes the calibration approaches used for causal and outcome conditions and descriptive statistics across cases.

    Assessing causality through fsQCA

    To determine what pathways lead to more positive or negative livelihood outcomes, we compared patterns across 14 cases using fsQCA. This involved multiple steps: calibration, assess necessity and sufficiency, robustness tests and case verification. All analyses were conducted using fs/QCA V.3.0 software58.

    The fsQCA is a comparative-case analytic method developed by refs. 38,59 on the basis of principles of Boolean algebra and fuzzy-set theory. It examines set memberships of cases (determined from qualitative and quantitative data) to identify if conditions are necessary or sufficient for explaining outcomes. While there are many relevant approaches in the universe of analytical techniques, including principal component analysis and cluster analysis39,60, among others, fsQCA had several critical advantages for this analysis. First, it “both bridge[s] and transcend[s] the qualitative–quantitative divide”61: as for case study approaches, the method retains in-depth case complexity but like large-sample statistical approaches, it enables some degree of generalizability through robust comparisons. Second, it is ideal for medium sample sizes, which are usually defined as being between 10 and 50 cases38. Third, it allows for complex causality where multiple conditions act in combination to influence an outcome. Fourth, this approach identifies multiple pathways to the same outcome that coexist (‘equifinality’), addressing concerns about local context dependence. Finally, in contrast to the earlier qualitative comparative analysis variant that requires ‘crisp’ condition and outcome scores (binary 0 or 1), the more recent fsQCA approach allows for nuanced scoring along a ‘fuzzy’ scale (range from 0 to 1). The fsQCA applications are increasing rapidly62, including recent papers examining post-typhoon relocations18 and shelter projects49 in the Philippines, post-tsunami recovery in India63 and post-hurricane recovery in New Orleans64. The fsQCA has also been used41,42,65 for meta-analysis when questions are about configurations of case study literature (as in this study) rather than effect size66. Qualitative comparative analysis is a useful method when quantitative meta-analysis falls short, such as when interventions are complex and when there is heterogeneity between cases that cannot be explained through statistical methods. In such circumstances, fsQCA can “replace standard fall back on narrative synthesis and usefully suggest ways in which a combination of characteristics are associated with improved outcomes” (p.13)40.

    Calibration

    To apply this method, we first undertook a process known as calibration: we converted the raw case data into set membership scores ranging from 0 to 1 using predefined criteria for both outcomes and relocation planning factors (Table 1 of Supplementary Section 2). For livelihood outcomes, each case was assigned a score for all six asset categories along a fuzzy-set six-point scale. As explained in Table 1 of Supplementary Section 2, we considered all the available evidence for each suboutcome category and assigned scores of 0, 0.2, 0.4, 0.6, 0.8 or 1 on the basis of per cent of available evidence indicating positive or negative outcomes. For relocation planning factors with quantitative data (scale, speed and distance), we used the standard approach to direct calibration using the fs/QCA 3.0 software function ‘calibrate’ which uses log-odds59. The remaining two factors were calibrated indirectly using six-point scales based on case knowledge. Community engagement measured the frequency and inclusivity of involvement of relocating community members at three stages of the process: initiation, site selection and site development. Transfer dynamics measured the level and quality of synchronicity of transfer dynamics at three stages of the process: decision, during move and destination. Table 1 of Supplementary Section 2 provides further details on calibration approaches.

    Assess necessity and sufficiency

    We then assessed the necessity and sufficiency of conditions in explaining outcomes. In fsQCA, necessary and sufficient relationships can be defined in terms of set relations. Necessary relationships occur when a condition is observed in (nearly) all cases with the outcome; this implies that the set of cases with the outcome is a subset of the cases with the condition. Sufficient relationships occur when the outcome is observed if the condition, or combination of conditions, is present; in other words, these cases are a subset of cases with the outcome. Both necessity and sufficiency analyses use two measures commonly used to assess a QCA: consistency and coverage. Consistency measures the strength of the relationship between condition and outcome or the degree to which one set is a perfect subset of another. Values range from 0 to 1 and, while there are no universally defined standards, a value of 0.9 is the generally accepted cutoff point for reliable analysis of necessity67 and 0.8 for sufficiency68. Coverage, by contrast, measures how well a subset condition explains an outcome, again with values ranging from 0 to 1. A highly consistent condition with low coverage has low empirical importance. Consistency is related to predictability and somewhat analogous to a correlation coefficient, whereas coverage is related to relevance and somewhat analogous to an R2 value, although the QCA community cautions against such comparisons.

    Following ref. 38, we first undertook an analysis of the necessity of each individual condition (Table 3 and Tables 3 and 4 of Supplementary Section 2). We tested for both the presence and absence of each condition in explaining cases with more positive livelihood outcomes and, as a robustness check, also tested for more negative livelihood outcomes. Since no conditions were necessary for either positive or negative outcomes, we followed standard practice and next analysed the sufficiency of combinations of conditions.

    To analyse sufficiency, we used fs/QCA software to generate a ‘truth table’ of all possible combinations of causal conditions (Table 5 of Supplementary Section 2). Each row represents a possible combination of conditions; since our analysis has five conditions, there are 25 or 32 possible rows. Each case is assigned to its corresponding row, while some rows are not represented by real cases and are called ‘logical remainders’. The higher the number of conditions included in an analysis, the higher the number of rows and therefore also logical remainders. Analyses with many conditions and few cases face challenges with limited diversity and validity of results, making the ideal ratio four to five conditions for 12–16 cases, as in our analysis69. Following a procedure known as minimization, which is the logical simplification of set relations among conditions and the outcome, the truth table rows are assessed for sufficient combinations of conditions.

    The fsQCA software generates three types of solutions (complex, parsimonious and intermediate) representing different treatments of remainders as counterfactuals; see Table 6 of Supplementary Section 2. We follow commonly accepted practice68 and focus on the intermediate solution based on theoretically informed assumptions about the connections between the presence or absence of conditions and the outcome. In this analysis, the intermediate solution assumes that the presence of community engagement and absence of distance are associated with better outcomes and gives preference to these factors when there were tied prime implicants but no assumptions are made for speed, scale or transfer dynamics given the absence of consensus in the theoretical literature.

    Robustness tests

    Next, we conducted a series of robustness tests, including changes in consistency thresholds, calibration approaches and removal of cases41,70. Given that this analysis includes 14 cases, we only considered a frequency threshold of one case per row68. We also undertook additional robustness tests with differing approaches to calibration of the outcome condition. In the primary analysis, we used the unweighted mean to provide a holistic measure of outcomes across all six SLA+ categories. However, recognizing that this averaging approach may lessen the influence of extremes and has the tendency to bring cases to the 0.5 threshold score, we also considered alternative weighting approaches through robustness tests. We considered: (1) all minimum outcomes (cases calibrated to the lowest score of the six SLA+ categories), (2) all maximum outcomes (each case calibrated to the highest score of the six SLA+ categories) and (3) a combination of minimum and maximum outcomes (cases with on average negative outcomes calibrated to the lowest score, while cases with on average positive outcomes calibrated to the highest score). Table 7 of Supplementary Section 2 includes results of all robustness tests.

    Case verification

    Finally, we examined each pathway to ascertain if it challenges or refines existing insights from individual cases and broader literature. We qualitatively compared across case studies to better understand these pathways and identify future research directions.

    Limitations

    Our analysis is limited by the availability of data in documents summarizing these relocation cases. Our coding is designed to capture information about outcomes and planning decisions in these documents, which may be distorted by biases of the authors and entities that published the studies and by pernicious or misleading socioeconomic forces such as colonialism.

    There are also challenges arising from the heterogeneity of sources, including the range of years of case completion and document publication. Each publication reflects circumstances at the time when each was written, which vary by document and may not reflect the status of the case at present. Thus, the passage of time is a compounding factor, as the assessment of outcomes may vary widely depending on whether the assessment in each document took place one year or one decade after the completion of the physical move. Supplementary Section 1 includes a table with dates of each publication considered per case to capture this variation. To ameliorate biases, future research efforts should monitor and evaluate relocation outcomes longitudinally over time.

    Additionally, the measurement of each construct has limitations and results should be interpreted accordingly. For example, we measured speed as the duration of time between initiation and the physical move of most people but this fails to capture how the construction of physical infrastructure and services may have lagged behind or proceeded the movement of people. Similarly, we measured scale as number of households but other proxies for this construct could be the spatial size of the lots and homes. Additionally, the way factors such as speed and distance are perceived varies across cultural contexts—what is considered ‘slow’ in Australia may be considered ‘fast’ in Vanuatu, for example. Future research considering alternative measurements for each construct is needed.

    Further, our analysis is limited by the focus on the community scale; relocating communities are not homogenous and both relocation planning decisions and outcomes may vary for people of different ages, genders, abilities, relationship to land, status as renters or owners and status as long-term residents or newcomers, among other axes of diversity11,28,71,72. Further research is needed to better understand relocation outcomes for individuals with differing intersectional identities.

    Finally, we acknowledge that there are limitations to the types of insights generated from the analysis of a medium sample of 14 cases, from relying on search engines for document identification, from using fsQCA for a configurational meta-analysis and from our scoring approaches. Additional research methods, including both larger sample statistical meta-analyses and in-depth single case studies, are needed to verify and extend these findings about pathways towards more sustainable livelihood outcomes in planned relocations.

    [ad_2]

    Source link

    Understanding and overcoming climate obstruction

    [ad_1]

    Climate Obstruction: How Denial, Delay and Inaction are Heating the Planet

    • Kristoffer Ekberg,
    • Bernhard Forchtner,
    • Martin Hultman &
    • Kirsti M. Jylhä

    ROUTLEDGE: 2022. 156 pp. £16.99

    Climate change denialism hinders climate action. Researchers have repeatedly attempted to understand and thus influence the phenomenon, but despite these efforts, progress has been slow. Climate Obstruction: How Denial, Delay and Inaction are Heating the Planet seeks to bring together the basic information on climate denialism so far and to answer the question, “why have we […] not taken appropriate measures to avert the unfolding climate crisis which is itself part of a much broader ecological crisis?” (p. 2) The authors point out that the main actors behind climate change and the obstruction of climate action, the fossil fuel companies, have largely continued to do business as usual. However, in addition to vested economic interests, climate denialism more broadly is about complicated political and cultural interests, ideologies, social structures and the sentiments of ordinary citizens.

    Most climate denialism is not denial at all, but organized and casual questioning of the causal relationship between human activity and climate change. Therefore, this book introduces the concept of ‘climate obstruction’ to replace or at least to add to the existing debates on climate denialism and climate scepticism. Since denialism is too simplistic and scepticism enjoys a scientific aura, the authors suggest that climate obstruction could serve as an umbrella term integrating a wide range of obstructionist strategies on the one hand and research by different scholars and fields on the other. The concept also poses “the question of who obstructs”, thus emphasizing “agency” (p. 5). Against this backdrop, this concise book explores the topic in an introduction, four substantive chapters and conclusions.

    The introduction begins by first presenting the conditions under which societies can and could have acted decisively on climate change, using the COVID-19 pandemic as an example, followed by the argument that the public do generally understand climate science. To address their question and to unite scholars, the authors present a typology of three distinct but overlapping types of obstruction as a theoretical tool to identify and describe the phenomena in question, based on the existing research. The primary type of obstruction refers to the denial of scientific evidence of anthropogenic climate change, and deliberate and overt actions to undermine climate policy. The secondary type of obstruction is that the science is tacitly accepted, but vested interests lead to inaction and delay of climate action. The tertiary type refers to unintentional obstructionism that takes place for certain cultures, hierarchies and values that encourages citizens to continue to live their life as they have been. All contribute to the same outcome, which is a “lack of taking urgently needed steps” (p. 13).

    In chapter 2, the authors proceed to dissect the long social history of fossil fuels and the foundations of climate obstruction. The introduction and the control of fossil fuels has led to the accumulation of “wealth and geopolitical power [to] a small portion of the world’s population” (p. 22). This has led to the rise of economic and political interests, but beyond this, cultural signifiers of the industrial, modern era, such as cars sold to the public as vehicles of liberation and “private car ownership”, are seen as a “human right” (ibid). And in the wake of reports such as Limits to Growth (D. H. Meadows et al., 1972), conflict emerged between industrial society and the global environmental movement, giving impetus to climate obstructionism. An essential public-opinion-formation strategy has been to create doubt about scientific findings concerning climate change.

    Fossil fuel companies have for many years funded their own scientific projects that they have used to manipulate the causal link between global warming and human activity. The anti-communist and anti-government sentiments of some prominent patriotic scientists have been harnessed to bring credibility to their case. At the same time, the lobbying sector, think-tanks and public relations (PR) agencies have been used to spread the manufactured doubt about climate change and science, to create desirability for (green) growth and consumerism, and to resist climate action. These are the strategies of the organized climate obstruction “machinery” (p. 53), the subject of chapter 3. Current strategies include, for example, constant advertising, the production of pseudo-scientific reports and the creation of fake grassroot movements with the aim “to create and enhance existing conflicts in society” (p. 54). These strategies have contributed to the distrust of science and even conspiracy theories. The ongoing contentious debate over fuel price could be seen as an example and a consequence.

    The climate obstruction machinery has been instrumental in fomenting social conflict and creating mistrust of science, and chapters 4 and 5 describe how the far right is exploiting this situation and how, for example, the sentiments of ordinary citizens are affected by these measures. A key unifying factor between the far right and the basic psychology of denialism is the authoritarian attitude. According to the authors, the conventional wisdom of essential hierarchies between ethnic, national and/or racial groups resonates well with such eco-fascist explanations of environmental problems such as overpopulation. These ideas also extend to resistance to globalism and cosmopolitanism, as these phenomena threaten the borders of the national homeland. Moreover, the culture of traditional masculinity and the idea of “the little guy” (p. 85) whose job is at risk are effective parts of the appealing imagery that is used by the national populists to resist environmentalism. Finally, the most mundane, tertiary obstruction, which manifests as inaction due to “attitude-behaviour gaps” (p. 96), leads the authors to conclude that “voluntary behavioural changes alone do not provide sufficient means to address the climate crisis, and [how] individual action is enabled and constrained by various structural and institutional conditions” (p. 95). The conclusion chapter presents the truly outstanding feature of the book: it says something concrete about how to proceed from here. Its prescription for “overcoming obstruction” (p. 123) can be considered as a rare feature in the academic literature and is a good place to end.

    The two minor shortcomings of the book are its emphasis on certain ideas and identities behind climate obstruction and its inability to bridge the structural and psychological explanations. This is evident when people’s ideas about the good life and their masculine and/or nationalist identities are seen as the primary explanation for their attitudes. As a result, people’s concerns about the structural changes brought about by the green transition — for example, concerns about low-skilled industrial jobs — are downplayed as irrelevant and merely populist rhetoric. Despite these shortcomings, Climate Obstruction: How Denial, Delay and Inaction are Heating the Planet achieves its goal of explaining the reasons for climate obstruction and delivers its message in a concise but very comprehensive manner.

    [ad_2]

    Source link

    Author Correction: Extreme sea levels at different global warming levels

    [ad_1]

    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

    Reprints and Permissions

    [ad_2]

    Source link

    Invasive interactions | Nature Climate Change

    [ad_1]

    J. Alex Baecher from the University of Florida, USA, and colleagues from the United States utilized a simple experimental system to understand the roles of abiotic and biotic factors on niche selection. Their experimental design involved manipulation of water availability and the presence or absence of native arboreal tree frog species, Hyla cinerea and H. squirella, and a harmful invasive tree frog species (Osteopilus septentrionalis).

    [ad_2]

    Source link

    Prudential regulation tools | Nature Climate Change

    [ad_1]

    Diego Hidalgo-Oñate from Jaume I University, Spain, and co-authors conducted a systematic review of what climate-related prudential regulation tools currently exist and how they could help manage climate risk in banking. The authors first describe the overall landscape of the literature, including its evolution and geographic distribution. They then identify the tools that are the most cited, including disclosure requirements, climate-related stress testing, differentiated capital requirements, targeted refinancing lines and green finance guides. The authors also point out that there are gaps that could promote future research, including a green bubble, double materiality, interactions between policies, compound risks, small and medium enterprise banking, and bank governance.

    [ad_2]

    Source link

    Mountain rivers warming | Nature Climate Change

    [ad_1]

    Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
    the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
    Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
    and JavaScript.

    [ad_2]

    Source link

    Melting uncertainties | Nature Climate Change

    [ad_1]

    The melting of polar ice sheets is the biggest potential contributor to global sea-level rise, but quantifying this risk is made difficult by the many sources of uncertainty that affect the evolution of ice sheets. Besides a lack of data and process understanding of ice-sheet dynamics, the climatological forcing to drive ice-sheet models is also a key source of uncertainty.

    [ad_2]

    Source link

    Searching for connections | Nature Climate Change

    [ad_1]

    Research on organism responses to climate change needs to incorporate biological interactions, which requires consideration of the trade-offs between scale and resolution.

    It is becoming clear — with the passing of time and the ongoing progression of the climate crisis — that expectations of organism responses to climate change are not always realized. Part of this can be related to the incorporation of limited physical factors into models that predict these responses (for example, focusing on temperature but missing precipitation), or focus on the magnitude but not the timing of these factors. Part of this can be related to questions of scale (for example, whether studies consider the macroclimate versus the microclimate, or are conducted at the species, population or individual level), or the unclear role plasticity and adaptation will play, or the difficulty in factoring co-occurring impacts, such as habitat loss and pollution, into climate change projections.


    Credit: Eugene Mymrin/Moment/Getty

    However, in addition to abiotic and environmental factors, ecologists’ ability to accurately describe the future impacts of climate change may also be hindered by difficulties in incorporating the role of biotic interactions into projections, which can change not just the magnitude but also the direction of impact.

    This issue of Nature Climate Change features original research, reviews and opinions that touch on the importance of incorporating biotic connectivity into climate change ecology.

    In one of two original research papers, Lesley Alton and Vanessa Kellermann show that species–species interactions can largely alter the costs of warming (see also the accompanying News & Views article by Mathieu Videlier), while in the second, Ewa Merz and colleagues reveal a negative impact of warming on network interactions and a shift in the trophic control of food webs (see also the accompanying Research Briefing). These two studies involve vastly different experimental systems and questions; Alton and Kellermann’s study investigates the metabolic cost for three Drosophila (fruit fly) species under controlled laboratory conditions, while Merz and colleagues utilize long-term monthly sampled plankton community datasets taken from Swiss lakes. Together, the works show how biotic interactions can both influence climate change outcomes and be broadly impacted by change.

    The need for further research in the field is highlighted by two opinion pieces. Oswald Schmitz and colleagues’ Perspective article calls for the consideration of animals into plans for nature-based solutions, and argues that ignoring the functionally interdependent relationships between primary producers (such as trees) and animals will lead to misestimations of carbon sequestration potentials. In a separate Comment, Charlie Lowen suggests that overcoming the difficulties associated with understanding ecosystem-level change could be facilitated by the use of model ecosystems, such as lakes, which represent semi-discrete, repeated environments with clear boundaries that have well-defined and easy-to-sample food webs.

    These opinion pieces underscore an issue that is well understood in the field: although it is clear that biotic interactions need to be considered as part of the understanding of climate change responses of organisms, it is also clear that doing so is an objectively difficult task.

    Long-term data tracking of species–species interactions is largely absent, and collecting these data is painstakingly complex, particularly at timescales relevant to climate change. Lab experiments and the study of ‘smaller scale’ ecosystems (for example, bromeliads or microbial communities) can help with both of these issues, especially as new technology develops, but it has to be acknowledged that a search for connections will generally come as a trade-off between resolution and scale.

    While global or large-scale studies can provide important information about overall patterns, smaller-scale work is needed to improve the accuracy of projections, something that is becoming increasingly important as climate change impacts intensify. The same can be said about the understanding of the other missing pieces of the puzzle that drive species shifts and survival under change, such as plasticity and adaptation, and microclimate impacts. Such work has wide-ranging implications and is urgently needed to aid management and conservation efforts.

    [ad_2]

    Source link

    Representation of adaptation in quantitative climate assessments

    [ad_1]

    We acknowledge support from the European Union’s Horizon 2020 research and innovation programme NAVIGATE under grant agreement no. 821124. N.v.M. acknowledges funding from the German Federal Ministry of Education and Research (grant agreement no. 01LN1711A). F.P. acknowledges funding through the CHIPS project, part of AXIS, an ERA-NET initiated by JPI Climate, funded by FORMAS (Sweden), DLR/BMBF (Germany, grant agreement no. 01LS1904A), AEI (Spain) and ANR (France), with co-funding by the European Union (grant agreement no. 776608).

    [ad_2]

    Source link

    Author Correction: Climate-mediated shifts in temperature fluctuations promote extinction risk

    [ad_1]

    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

    Reprints and Permissions

    [ad_2]

    Source link

    Trophic rewilding can expand natural climate solutions

    [ad_1]

  • Hallegatte, S. & Mach, K. J. Make climate-change assessments more relevant. Nature 534, 613–615 (2016).

    Article 
    CAS 

    Google Scholar     

  • Rogelj, J. et al. Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature 534, 631–639 (2016).

    Article 
    CAS 

    Google Scholar     

  • Teske, S. Achieving the Paris Climate Agreement Goals: Global and Regional Renewable Energy Scenarios with Non-Energy GHG Pathways for +1.5 °C and +2 °C (Springer Open, 2019).

  • Fuss, S. et al. Moving toward net-zero emissions requires new alliances for carbon dioxide removal. One Earth 3, 145–149 (2020).

    Article 

    Google Scholar     

  • Fargione, J. et al. Natural climate solutions for the United States. Sci. Adv. 4, eaat1869 (2018).

    Article 

    Google Scholar     

  • Griscom, B. et al. Natural climate solutions. Proc. Natl Acad. Sci. USA 114, 11645–11650 (2017).

    Article 
    CAS 

    Google Scholar     

  • Hoegh-Guldberg, O. et al. The Ocean as a Solution to Climate Change: Five Opportunities for Action (World Resources Institute, 2019).

  • Seddon, N. et al. Getting the message right on nature-based solutions to climate change. Glob. Change Biol. 27, 1518–1546 (2021).

    Article 

    Google Scholar     

  • Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).

    Article 

    Google Scholar     

  • Girardin, A. J. et al. Nature-based solutions can help cool the planet—if we act now. Nature 593, 191–194 (2021).

    Article 
    CAS 

    Google Scholar     

  • Seddon, N. et al. Understanding the value and limits of nature-based solutions to climate change and other global challenges. Phil. Trans. R. Soc. B 375, 20190120 (2020).

    Article 

    Google Scholar     

  • Miles, L. et al. Nature-Based Solutions for Climate Change Mitigation (United Nations Environment Program and International Union for Conservation of Nature, 2021).

  • Di Sacco, A. et al. Ten golden rules for reforestation to optimize carbon sequestration, biodiversity recovery and livelihood benefits. Glob. Change Biol. 27, 1328–1348 (2021).

    Article 

    Google Scholar     

  • Sarira, T. V. et al. Co-benefits of forest carbon projects in Southeast Asia. Nat. Sustain. 5, 393–396 (2022).

    Article 

    Google Scholar     

  • Mori, A. S. Advancing nature-based approaches to address the biodiversity and climate emergency. Ecol. Lett. 23, 1729–1732 (2020).

    Article 

    Google Scholar     

  • Jackson, R. N. et al. The ecology of soil carbon: pools, vulnerabilities and biotic and abiotic controls. Annu. Rev. Ecol. Evol. Syst. 48, 419–445 (2017).

    Article 

    Google Scholar     

  • Keenan, T. F. & Williams, C. A. The terrestrial carbon sink. Annu. Rev. Environ. Resour. 43, 219–243 (2018).

    Article 

    Google Scholar     

  • Brodie, J. F. & Gibbs, H. K. Bushmeat hunting as climate threat. Science 326, 364–365 (2005).

    Article 

    Google Scholar     

  • Schmitz, O. J. et al. Animating the carbon cycle. Ecosystems 7, 344–359 (2014).

    Article 

    Google Scholar     

  • Smith, F. A., Lyons, S. K., Wagner, P. J. & Elliott, S. M. The importance of considering animal body mass in IPCC greenhouse inventories and the underappreciated role of wild herbivores. Glob. Change Biol. 21, 3880–3888 (2015).

    Article 

    Google Scholar     

  • Mahli, Y. et al. Megafauna and ecosystem function from the Pleistocene to the Anthropocene. Proc. Natl Acad. Sci. USA 113, 838–846 (2016).

    Article 

    Google Scholar     

  • Cromsigt, J. P. et al. Trophic rewilding as a climate change mitigation strategy? Phil. Trans. R. Soc. B 373, 20170440 (2018).

    Article 

    Google Scholar     

  • Schmitz, O. J. et al. Animals and the zoogeochemistry of the carbon cycle. Science 362, eaar3213 (2018).

    Article 

    Google Scholar     

  • Sandom, C. J. et al. Trophic rewilding presents regionally specific opportunities for mitigating climate change. Phil. Trans. R. Soc. B 375, 20190125 (2020).

    Article 
    CAS 

    Google Scholar     

  • Schmitz, O. J. & Leroux, S. J. Food webs and ecosystems: linking species interactions to the carbon cycle. Annu. Rev. Ecol. Evol. Syst. 51, 272–295 (2020).

    Article 

    Google Scholar     

  • Sobral, M. et al. Mammal diversity influences the carbon cycle through trophic interactions in the Amazon. Nat. Ecol. Evol. 1, 1670–1676 (2017).

    Article 

    Google Scholar     

  • Osuri, A. M. et al. Contrasting effects of defaunation on aboveground carbon storage across the global tropics. Nat. Commun. 7, 11351 (2016).

    Article 
    CAS 

    Google Scholar     

  • Culot, L. et al. Synergistic effects of seed disperser and predator loss on recruitment success and long-term consequences for carbon stocks in tropical rainforests. Sci. Rep. 7, 7662 (2017).

    Article 

    Google Scholar     

  • Jung, M. et al. Areas of global importance for conserving terrestrial biodiversity, carbon and water. Nat. Ecol. Evol. 5, 1499–1509 (2021).

    Article 

    Google Scholar     

  • Pörtner, H. O. et al. IPBES–IPCC co-sponsored workshop report on biodiversity and climate change. Zenodo https://doi.org/10.5281/zenodo.4782538 (2021).

  • Nelson, E. et al. Efficiency of incentives to jointly increase carbon sequestration and species conservation on a landscape. Proc. Natl Acad. Sci. USA 105, 9471–9476 (2008).

    Article 
    CAS 

    Google Scholar     

  • Strassbourg, B. B. N. et al. Global congruence of carbon storage and biodiversity in terrestrial ecosystems. Conserv. Lett. 3, 98–105 (2010).

    Article 

    Google Scholar     

  • Thomas, C. D. et al. Reconciling biodiversity and carbon conservation. Ecol. Lett. 16, 39–47 (2013).

    Article 

    Google Scholar     

  • Seddon, N. et al. Grounding nature-based solutions in sound biodiversity science. Nat. Clim. Change 9, 84–87 (2019).

    Article 

    Google Scholar     

  • Schmitz, O. J., Post, E., Burns, C. E. & Johnston, K. M. Ecosystem responses to global climate change: moving beyond color-mapping. BioScience 53, 1199–1205 (2003).

    Article 

    Google Scholar     

  • Soulé‚ M. E., Estes, J. A., Berger, J. & Martinez del Rio, C. Ecological effectiveness: conservation goals for interactive species. Conserv. Biol. 17, 1238–1250 (2003).

    Article 

    Google Scholar     

  • Jarvie, S. & Svenning, J.-C. Using species distribution modelling to determine opportunities for trophic rewilding under future scenarios of climate change. Phil. Trans. R. Soc. B 373, 20170446 (2018).

    Article 

    Google Scholar     

  • Svenning, J.-C. et al. Science for a wilder Anthropocene: synthesis and future directions for trophic rewilding research. Proc. Natl Acad. Sci. USA 113, 898–906 (2016).

    Article 
    CAS 

    Google Scholar     

  • Bakker, E. S. & Svenning, J.-C. Trophic rewilding: impact on ecosystems under global change. Phil. Trans. R. Soc. B 373, 20170432 (2018).

    Article 

    Google Scholar     

  • Smith, F. A. et al. Exploring the influence of ancient and historic megaherbivore extirpations on the global methane budget. Proc. Natl Acad. Sci. USA 113, 874–879 (2016).

    Article 
    CAS 

    Google Scholar     

  • Enquist, B. et al. The megabiota are disproportionately important for biosphere functioning. Nat. Commun. 11, 699 (2020).

    Article 
    CAS 

    Google Scholar     

  • Hyvarinen, O. et al. Megaherbivore impacts on ecosystem and Earth system functioning: the current state of the science. Ecography 44, 1579–1594 (2021).

    Article 

    Google Scholar     

  • Løvschal, M. et al. Fencing bodes a rapid collapse of the unique Greater Mara ecosystem. Sci. Rep. 7, 41450 (2017).

    Article 

    Google Scholar     

  • Veldhuis, M. P. et al. Cross-boundary human impacts compromise the Serengeti–Mara ecosystem. Science 363, 1424–1428 (2019).

    Article 
    CAS 

    Google Scholar     

  • Donlan, C. J. et al. Pleistocene rewilding: an optimistic agenda for twenty-first century conservation. Am. Nat. 168, 660–681 (2006).

    Article 

    Google Scholar     

  • Vynne, C. et al. An ecoregion-based approach to restoring the world’s intact mammal assemblages. Ecography 2022, e06098 (2022).

    Article 

    Google Scholar     

  • Holdo, R. M. et al. A disease-mediated trophic cascade in the Serengeti and its implications for ecosystem C. PLoS Biol. 7, e1000210 (2009).

    Article 

    Google Scholar     

  • Karp, A. T., Faith, J. T., Marlon, J. R. & Staver, A. C. Global response of fire activity to late Quaternary grazer extinctions. Science 374, 1145–1148 (2021).

    Article 
    CAS 

    Google Scholar     

  • Johnson, C. N. et al. Can trophic rewilding reduce the impact of fire in a more flammable world? Phil. Trans. R. Soc. B 373, 20170443 (2018).

    Article 

    Google Scholar     

  • Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).

    Article 
    CAS 

    Google Scholar     

  • Nauer, P. A., Hutley, L. B. & Arndt, S. K. Termite mounds mitigate half of termite methane emissions. Proc. Natl Acad. Sci. USA 115, 13306–13311 (2018).

    Article 
    CAS 

    Google Scholar     

  • Bianchi, D. et al. Estimating global biomass and biogeochemical cycling of marine fish with and without fishing. Sci. Adv. 17, eabd7554 (2021).

    Article 

    Google Scholar     

  • Chapin, F. S. III et al. Reconciling carbon-cycle concepts, terminology, and methods. Ecosystems 9, 1041–1050 (2006).

    Article 
    CAS 

    Google Scholar     

  • Wilmers, C. C. et al. Do trophic cascades affect the storage and flux of atmospheric carbon? An analysis of sea otters and kelp forests. Front. Ecol. Environ. 10, 409–415 (2012).

    Article 

    Google Scholar     

  • Wilmers, C. C. & Schmitz, O. J. Effects of gray wolf‐induced trophic cascades on ecosystem carbon cycling. Ecosphere 7, e01501 (2016).

    Article 

    Google Scholar     

  • Atwood, T. B. et al. Predators shape sedimentary organic carbon storage in a coral reef ecosystem. Front. Ecol. Evol. 6, 110 (2018).

    Article 

    Google Scholar     

  • Saba, G. K. et al. Toward a better understanding of fish-based contribution to ocean carbon flux. Limnol. Oceanogr. 66, 1639–1644 (2021).

    Article 
    CAS 

    Google Scholar     

  • Berzaghi, F. et al. Financing conservation by valuing carbon services produced by wild animals. Proc. Natl Acad. Sci. USA 119, e2120426119 (2022).

    Article 
    CAS 

    Google Scholar     

  • Sanderson, E. W. et al. The ecological future of North American bison: conceiving long-term, large-scale conservation of wildlife. Conserv. Biol. 22, 252–266 (2008).

    Article 

    Google Scholar     

  • Lavery, T. J. et al. Iron defecation by sperm whales stimulates carbon export in the Southern Ocean. Proc. R. Soc. B. 277, 3527–3531 (2010).

    Article 

    Google Scholar     

  • Dufort, A. et al. Recovery of carbon benefits by overharvested baleen whale populations is threatened by climate change. Proc. R. Soc. B. 289, 20220375 (2022).

    Article 

    Google Scholar     

  • Nummi, P., Vehkaoja, M., Pumpanen, J. & Ojala, A. Beavers affect carbon biogeochemistry: both short-term and long-term processes are involved. Mamm. Rev. 48, 298–311 (2018).

    Article 

    Google Scholar     

  • Wohl, E. Legacy effects of loss of beavers in the continental United States. Environ. Res. Lett. 16, 025010 (2021).

    Article 

    Google Scholar     

  • Strauss, J. et al. Circum-Arctic map of the Yedoma permafrost domain. Front. Earth Sci. 9, 758360 (2021).

    Article 

    Google Scholar     

  • Macias-Fauria, M. et al. Pleistocene Arctic megafaunal ecological engineering as a natural climate solution? Phil. Trans. R. Soc. B 375, 20190122 (2020).

    Article 
    CAS 

    Google Scholar     

  • Beer, C. et al. Protection of permafrost soils from thawing by increasing herbivore density. Sci. Rep. 10, 4170 (2020).

    Article 
    CAS 

    Google Scholar     

  • Olofsson, J. & Post, E. Effects of large herbivores on tundra vegetation in a changing climate, and implications for rewilding. Phil. Trans. R. Soc. B 373, 20170437 (2018).

    Article 

    Google Scholar     

  • Lara, M. J. et al. Peak season carbon exchange shifts from a sink to a source following 50+ years of herbivore exclusion in an Arctic tundra ecosystem. J. Ecol. 105, 122–131 (2017).

    Article 
    CAS 

    Google Scholar     

  • Tacutu, R. et al. Human ageing genomic resources: new and updated databases. Nucleic Acids Res. 46, D1083–D1090 (2018).

    Article 
    CAS 

    Google Scholar     

  • Coverdale, T. C. et al. Indirect human impacts reverse centuries of carbon sequestration and saltmarsh accretion. PLoS ONE 9, 393296 (2014).

    Article 

    Google Scholar     

  • Brodie, J. How monkeys sequester carbon. Trends Ecol. Evol. 31, 414 (2016).

    Article 

    Google Scholar     

  • Kristensen, J. A., Svenning, J.-C., Georgiou, K. & Mahli, Y. Can large herbivores stabilize ecosystem carbon? Trends Ecol. Evol. 37, 117–128 (2022).

    Article 
    CAS 

    Google Scholar     

  • Pellegrini, A. F. A., Pringle, R. M., Govender, N. & Hedin, L. O. Woody plant biomass and carbon exchange depend on elephant–fire interactions across a productivity gradient in African savanna. J. Ecol. 105, 111–121 (2017).

    Article 
    CAS 

    Google Scholar     

  • Davies, A. B. & Asner, G. P. Elephants limit aboveground carbon gains in African savannas. Glob. Change Biol. 25, 1368–1382 (2019).

    Article 

    Google Scholar     

  • Berzaghi, F. et al. Carbon stocks in central African forests enhanced by elephant disturbance. Nat. Geosci. 12, 725–729 (2017).

    Article 

    Google Scholar     

  • Bakker, E. S. et al. Combining paleo-data and modern exclosure experiments to assess the impact of megafauna extinctions on woody vegetation. Proc. Natl Acad. Sci. USA 113, 847–855 (2016).

    Article 
    CAS 

    Google Scholar     

  • Mahli, Y. et al. The role of large wild animals in climate change mitigation and adaptation. Curr. Biol. 32, R181–R196 (2022).

    Article 

    Google Scholar     

  • Berzaghi, F. et al. Assessing the role of megafauna in tropical forest ecosystems and biogeochemical cycles—the potential of vegetation models. Ecography 41, 1934–1954 (2018).

    Article 

    Google Scholar     

  • Ylänne, H., Olofsson, J., Oksanen, L. & Stark, S. Consequences of grazer-induced vegetation transitions on ecosystem carbon storage in the tundra. Funct. Ecol. 32, 1091–1102 (2017).

    Article 

    Google Scholar     

  • Hedberg, C. P., Lyons, S. K. & Smith, F. A. The hidden legacy of megafaunal extinction: loss of functional diversity and resilience over the late Quaternary at Hall’s Cave. Glob. Ecol. 31, 294–307 (2022).

    Article 

    Google Scholar     

  • Leroux, S. J., Hawlena, D. & Schmitz, O. J. Predation risk, stoichiometric plasticity and ecosystem elemental cycling. Proc. R. Soc. Lond. B 279, 4183–4191 (2012).


    Google Scholar     

  • Ren, L. et al. Biota-mediated carbon cycling—a synthesis of biotic interaction controls on blue carbon. Ecol. Lett. 25, 521–540 (2021).

    Article 

    Google Scholar     

  • Leroux, S. J. & Schmitz, O. J. Predator-driven elemental cycling: the predation and risk effects on ecosystem elemental cycling. Ecol. Evol. 5, 4976–4988 (2016).

    Article 

    Google Scholar     

  • Schmitz, O. J. et al. Predator community composition is linked to soil carbon retention across a human land use gradient. Ecology 98, 1256–1265 (2017).

    Article 

    Google Scholar     

  • Clauss, M. et al. Review: comparative methane production in mammalian herbivores. Animal 14, s113–s123 (2020).

    Article 
    CAS 

    Google Scholar     

  • Sitters, J. et al. Negative effects of cattle on soil carbon and nutrient pools reversed by megaherbivores. Nat. Sustain. 3, 360–366 (2020).

    Article 

    Google Scholar     

  • Temmink, R. J. M. et al. Recovering wetland biogeomorphic feedbacks to restore the world’s biotic carbon hotspots. Science 376, eabn1479 (2022).

    Article 
    CAS 

    Google Scholar     

  • Sayre, R. G. et al. An assessment of the representation of ecosystems in global protected areas using new maps of world climate regions and world ecosystems. Glob. Ecol. Conserv. 21, e00860 (2020).

    Article 

    Google Scholar     

  • Sayre, R. G. et al. A three-dimensional mapping of the ocean based on environmental data. Oceanography 30, 90–103 (2017).

    Article 

    Google Scholar     

  • Sala, E. & Knowlton, N. Global marine biodiversity trends. Annu. Rev. Environ. Res. 31, 93–122 (2006).

    Article 

    Google Scholar     

  • Dulal, H. B., Shah, K. U. & Sapkota, U. Reducing emissions from deforestation and forest degradation (REDD) projects: lessons for future policy design and implementation. Int. J. Sustain. Dev. World 19, 116–129 (2012).


    Google Scholar     

  • Venter, O. & Koh, L.-P. Reducing emissions from deforestation and forest degradation (REDD+): game changer or just another quick fix? Ann. NY Acad. Sci. 1249, 137–150 (2012).

    Article 

    Google Scholar     

  • Plumptre, A. J. et al. Where might we find ecologically intact communities. Front. Glob. Change 4, 626635 (2021).

    Article 

    Google Scholar     

  • Bauer, S. & Hoye, B. J. Migratory animals couple biodiversity and ecosystem functioning worldwide. Science 344, 1242552 (2014).

    Article 
    CAS 

    Google Scholar     

  • Tucker, M. A. et al. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).

    Article 
    CAS 

    Google Scholar     

  • Ledger, S. E. H. et al. Wildlife Comeback in Europe: Opportunities and Challenges for Species Recovery (Rewilding Europe, 2022).

  • Natura 2000. European Commission https://ec.europa.eu/environment/nature/natura2000/index_en.htm (2008).

  • Andronic, C. et al. The Challenge of Land Abandonment after 2020 and Options for Mitigating Measures (Federal Institute of Agricultural Economics, Rural and Mountain Research, 2021).

  • Duarte, C. M. et al. Rebuilding marine life. Nature 580, 39–51 (2020).

    Article 
    CAS 

    Google Scholar     

  • Fløjgaard, C. et al. Exploring a natural baseline for large-herbivore biomass in ecological restoration. J. Appl. Ecol. 59, 18–24 (2022).

    Article 

    Google Scholar     

  • Takacs, D. Whose voices count in biodiversity conservation? Ecological democracy in biodiversity offsetting, REDD+, and rewilding. J. Environ. Policy Plan. 22, 43–58 (2020).

    Article 

    Google Scholar     

  • Carter, N. H. & Linnell, J. D. C. Co-adaptation is key to coexisting with large carnivores. Trends Ecol. Evol. 31, 575–587 (2016).

    Article 

    Google Scholar     

  • von Hohenberg, B. C. & Hager, A. Wolf attacks predict far-right voting. Proc. Natl Acad. Sci. USA 119, e2202224119 (2022).

    Article 
    CAS 

    Google Scholar     

  • Yona, L., Cashore, B. & Schmitz, O. J. Integrating policy and ecology systems to achieve path dependent climate solutions. Environ. Sci. Policy 98, 54–60 (2019).

    Article 

    Google Scholar     

  • 2019 Climate Action Summit. United Nations https://www.un.org/en/climatechange/2019-climate-action-summit (2019).

  • IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability (eds Pörtner, H.-O. et al.) (Cambridge Univ. Press, 2022).

  • UN Convention on Biological Diversity First Draft of the Post-2020 Global Biodiversity Framework (UN 2021); https://www.cbd.int/doc/c/abb5/591f/2e46096d3f0330b08ce87a45/wg2020-03-03-en.pdf

  • Fricke, E. C., Ordonez, A., Rogers, H. S. & Svenning, J.-C. The effects of defaunation on plants’ capacity to track climate change. Science 375, 210–214 (2022).

    Article 
    CAS 

    Google Scholar     

  • Sala, E. et al. Protecting the global ocean for biodiversity, food and climate. Nature 592, 397–402 (2021).

    Article 
    CAS 

    Google Scholar     

  • Hicks, C. C. et al. Harnessing global fisheries to tackle micronutrient deficiencies. Nature 574, 95–98 (2019).

    Article 
    CAS 

    Google Scholar     

  • Tigchelaar, M. et al. The vital role of blue foods in the global food system. Glob. Food Sec. 33, 100637 (2022).

    Article 

    Google Scholar     

  • A High Ambition Coalition on Biodiversity beyond National Jurisdiction, Protecting the Ocean: Time for Action (European Commission, 2022); https://oceans-and-fisheries.ec.europa.eu/ocean/international-ocean-governance/protecting-ocean-time-action_en

  • White, C. & Costello, C. Close the high seas to fishing? PLoS Biol. 12, e1001826 (2014).

    Article 

    Google Scholar     

  • Cook-Patton, S. C. et al. Protect, manage and then restore lands for climate mitigation. Nat. Clim. Change 11, 1027–1034 (2021).

    Article 

    Google Scholar     

  • Adoption of the Paris Agreement FCCC/CP/2015/L.9/Rev.1 (UNFCCC, 2015).

  • Krause, T. & Nielsen, M. R. Not seeing the forest for the trees: the oversight of defaunation in REDD+ and global forest governance. Forests 10, 344 (2019).

    Article 

    Google Scholar     

  • Fauset, S. et al. Hyperdominance in Amazonian forest carbon cycling. Nat. Commun. 6, 6857 (2015).

    Article 
    CAS 

    Google Scholar     

  • Berzaghi, F. et al. Value wild animals’ carbon services to fill the biodiversity financing gap. Nat. Clim. Change 12, 598–601 (2022).

    Article 

    Google Scholar     

  • Jung, M. Habitatmapping. GitHub https://github.com/Martin-Jung/Habitatmapping (2020).

    • [ad_2]

    Source link

    Biogenic factors explain soil carbon in paired urban and natural ecosystems worldwide

    [ad_1]

  • Chien, S.-C. & Krumins, J. A. Natural versus urban global soil organic carbon stocks: a meta-analysis. Sci. Total Environ. 807, 150999 (2022).

    Article 
    CAS 

    Google Scholar     

  • Sun, Y., Xie, S. & Zhao, S. Valuing urban green spaces in mitigating climate change: a city‐wide estimate of aboveground carbon stored in urban green spaces of China’s Capital. Glob. Change Biol. 25, 1717–1732 (2019).

    Article 

    Google Scholar     

  • Bossio, D. et al. The role of soil carbon in natural climate solutions. Nat. Sustain. 3, 391–398 (2020).

    Article 

    Google Scholar     

  • Cambou, A. et al. Estimation of soil organic carbon stocks of two cities, New York City and Paris. Sci. Total Environ. 644, 452–464 (2018).

    Article 
    CAS 

    Google Scholar     

  • Epp Schmidt, D. J. et al. Urbanization erodes ectomycorrhizal fungal diversity and may cause microbial communities to converge. Nat. Ecol. Evol. 1, 0123 (2017).

    Article 

    Google Scholar     

  • Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).

    Article 
    CAS 

    Google Scholar     

  • García-Palacios, P. et al. Evidence for large microbial-mediated losses of soil carbon under anthropogenic warming. Nat. Rev. Earth Environ. 2, 507–517 (2021).

    Article 

    Google Scholar     

  • Pouyat, R., Groffman, P., Yesilonis, I. & Hernandez, L. Soil carbon pools and fluxes in urban ecosystems. Environ. Pollut. 116, S107–S118 (2002).

    Article 
    CAS 

    Google Scholar     

  • Edmondson, J. L. et al. Urban tree effects on soil organic carbon. PLoS ONE 9, e101872 (2014).

    Article 

    Google Scholar     

  • Weissert, L., Salmond, J. & Schwendenmann, L. Variability of soil organic carbon stocks and soil CO2 efflux across urban land use and soil cover types. Geoderma 271, 80–90 (2016).

    Article 
    CAS 

    Google Scholar     

  • Georgiou, K. et al. Global stocks and capacity of mineral-associated soil organic carbon. Nat. Commun. 13, 3797 (2022).

    Article 
    CAS 

    Google Scholar     

  • Cotrufo, M. F. & Lavallee, J. M. Soil organic matter formation, persistence, and functioning: a synthesis of current understanding to inform its conservation and regeneration. Adv. Agron. 172, 1–66 (2022).

    Article 

    Google Scholar     

  • Kleber, M. et al. Mineral–organic associations: formation, properties, and relevance in soil environments. Adv. Agron. 130, 1–140 (2015).

    Article 

    Google Scholar     

  • Cotrufo, M. F., Ranalli, M. G., Haddix, M. L., Six, J. & Lugato, E. Soil carbon storage informed by particulate and mineral-associated organic matter. Nat. Geosci. 12, 989–994 (2019).

    Article 
    CAS 

    Google Scholar     

  • Plaza, C. et al. Ecosystem productivity has a stronger influence than soil age on surface soil carbon storage across global biomes. Commun. Earth Environ. 3, 233 (2022).

    Article 

    Google Scholar     

  • Hengl, T. et al. SoilGrids250m: global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).

    Article 

    Google Scholar     

  • IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).

  • Scharenbroch, B., Day, S., Trammell, T. & Pouyat, R. in Urban Soils (eds Lal, R. & Stewart, B. A.) Ch. 6 (CRC Press, 2017).

  • Crowther, T. W. et al. Sensitivity of global soil carbon stocks to combined nutrient enrichment. Ecol. Lett. 22, 936–945 (2019).

    Article 
    CAS 

    Google Scholar     

  • Delgado-Baquerizo, M. et al. The influence of soil age on ecosystem structure and function across biomes. Nat. Commun. 11, 4721 (2020).

    Article 
    CAS 

    Google Scholar     

  • Frostegård, Å., Bååth, E. & Tunlio, A. Shifts in the structure of soil microbial communities in limed forests as revealed by phospholipid fatty acid analysis. Soil Biol. Biochem. 25, 723–730 (1993).

    Article 

    Google Scholar     

  • Qin, S. et al. Temperature sensitivity of SOM decomposition governed by aggregate protection and microbial communities. Sci. Adv. 5, eaau1218 (2019).

    Article 
    CAS 

    Google Scholar     

  • Delgado-Baquerizo, M. et al. Global homogenization of the structure and function in the soil microbiome of urban greenspaces. Sci. Adv. 7, eabg5809 (2021).

    Article 
    CAS 

    Google Scholar     

  • Mundim, K. C., Baraldi, S., Machado, H. G. & Vieira, F. M. Temperature coefficient (Q10) and its applications in biological systems: beyond the Arrhenius theory. Ecol. Model. 431, 109127 (2020).

    Article 

    Google Scholar     

  • Wang, C. et al. The temperature sensitivity of soil: microbial biodiversity, growth, and carbon mineralization. ISME J. 15, 2738–2747 (2021).

    Article 
    CAS 

    Google Scholar     

  • Harris, D., Horwáth, W. R. & van Kessel, C. Acid fumigation of soils to remove carbonates prior to total organic carbon or carbon‐13 isotopic analysis. Soil Sci. Soc. Am. J. 65, 1853–1856 (2001).

    Article 
    CAS 

    Google Scholar     

  • Sokol, N. W. & Bradford, M. A. Microbial formation of stable soil carbon is more efficient from belowground than aboveground input. Nat. Geosci. 12, 46–53 (2019).

    Article 
    CAS 

    Google Scholar     

  • Fick, S. & Hijmans, R. WorldClim 2: nouvelles surfaces climatiques de résolution spatiale de 1 km pour les zones terrestres mondiales. Int. J. Climatol. 37, 4302–4315 (2017).

    Article 

    Google Scholar     

  • Lembrechts, J. J. et al. Global maps of soil temperature. Glob. Change Biol. 28, 3110–3144 (2021).

    Article 

    Google Scholar     

  • Vermote, E., Justice, C., Claverie, M. & Franch, B. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sens. Environ. 185, 46–56 (2016).

    Article 

    Google Scholar     

  • Zhang, L. et al. Direct and indirect impacts of urbanization on vegetation growth across the world’s cities. Sci. Adv. 8, eabo0095 (2022).

    Article 

    Google Scholar     

  • Richards, D. R. & Belcher, R. N. Global changes in urban vegetation cover. Remote Sens. 12, 23 (2019).

    Article 

    Google Scholar     

  • Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012).

    Article 
    CAS 

    Google Scholar     

  • Frostegård, Å., Tunlid, A. & Bååth, E. Use and misuse of PLFA measurements in soils. Soil Biol. Biochem. 43, 1621–1625 (2011).

    Article 

    Google Scholar     

  • Shi, B. et al. Temporal changes in the spatial variability of soil respiration in a meadow steppe: the role of abiotic and biotic factors. Agric. Meteorol. 287, 107958 (2020).

    Article 

    Google Scholar     

  • Dacal, M., Bradford, M. A., Plaza, C., Maestre, F. T. & García-Palacios, P. Soil microbial respiration adapts to ambient temperature in global drylands. Nat. Ecol. Evol. 3, 232–238 (2019).

    Article 

    Google Scholar     

  • Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109, 21390–21395 (2012).

    Article 
    CAS 

    Google Scholar     

  • Fierer, N. et al. Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science 342, 621–624 (2013).

    Article 
    CAS 

    Google Scholar     

  • Meyer, F. et al. The metagenomics RAST server–a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9, 386 (2008).

    Article 
    CAS 

    Google Scholar     

  • Oksanen, J. et al. Package ‘vegan’: community ecology. R package version 2.2-0 (2014); http://CRAN.Rproject.org/package=vegan

  • R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2013); http://www.R-project.org/

  • Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article 

    Google Scholar     

  • Kunzetsova, A., Brockhoff, P. & Christensen, R. lmerTest package: tests in linear mixed effect models. J. Stat. Softw. 82, 1–26 (2017).


    Google Scholar     

  • Menard, S. Applied Logistic Regression Analysis 2nd edn (SAGE Publications, 2001).

  • Schermelleh-Engel, K., Moosbrugger, H. & Müller, H. Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol. Res. 8, 23–74 (2003).


    Google Scholar     

  • Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Contr. 19, 716–723 (1974).

    Article 

    Google Scholar     

  • Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).

    Article 
    CAS 

    Google Scholar     

  • Feng, Y. et al. Temperature thresholds drive the global distribution of soil fungal decomposers. Glob. Change Biol. 28, 2779–2789 (2022).

    Article 

    Google Scholar     

  • Fong, Y., Huang, Y., Gilbert, P. B. & Permar, S. R. chngpt: threshold regression model estimation and inference. BMC Bioinformatics 18, 454 (2017).

    Article 

    Google Scholar     

    • [ad_2]

    Source link

    Defence against the rising seas

    [ad_1]

    Nature Climate Change, Published online: 23 March 2023; doi:10.1038/s41558-023-01645-0

    The rate of sea-level rise varies around the world, as do local infrastructure and standards for defending against the risks of flooding. Now research indicates that coastal communities can also have very different times left to act before defences fall short of those standards.

    [ad_2]

    Source link

    Soils worldwide suffer from the combined effects of multiple global change factors

    [ad_1]

    Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

    This is a summary of: Rillig, M. C. et al. Increasing the number of stressors reduces soil ecosystem services worldwide. Nat. Clim. Change https://doi.org/10.1038/s41558-023-01627-2 (2023).

    [ad_2]

    Source link

    Strong climate action is worth it

    [ad_1]

    An immediate and rapid reduction in global emissions is required for many reasons. Integrated research supports the economic case for strong near-term climate action, even before accounting for expected negative impacts on biodiversity, health and tipping points.

    Their work calculates the relative benefits and costs of climate mitigation and climate impacts in three integrated assessment models. These models have traditionally focused on mitigation when simulating future climatic and economic trajectories but multi-model studies of the detailed economic impacts along these pathways remain limited. To bridge this gap, the researchers analyse these factors together to calculate the economically optimal emissions reductions and resulting global temperature trajectories for each model. The damage functions in the models, which relate the gross domestic product (GDP) to temperature and sea-level rise, account for impacts on agriculture, forestry, fisheries, floods, road infrastructure, energy supply and demand, and labour productivity. From a range of recent studies, the researchers collected evidence on each impact channel and calculated the combined effect on the economy in one computable general equilibrium model. By repeating this exercise for different climatic and socioeconomic scenarios and assumptions, the researchers derive region-specific damage functions, which can be implemented into integrated assessment models.

    [ad_2]

    Source link

    Risk of isolation increases the expected burden from sea-level rise

    [ad_1]

  • Hauer, M. E., Evans, J. M. & Mishra, D. R. Millions projected to be at risk from sea-level rise in the continental United States. Nat. Clim. Change 6, 691–695 (2016).

  • Nicholls, R. J. et al. Sea-level rise and its possible impacts given a ‘beyond 4 °C world’ in the twenty-first century. Philos. Trans. R. Soc. A 369, 161–181 (2011).

    Article 

    Google Scholar     

  • Herreros-Cantis, P., Olivotto, V., Grabowski, Z. J. & McPhearson, T. Shifting landscapes of coastal flood risk: environmental (in)justice of urban change, sea level rise, and differential vulnerability in New York City. Urban Transform. 2, 9 (2020).

  • Oppenheimer, M. et al. in Special Report on the Ocean and Cryosphere in a Changing Climate (ed. Pörtner, H.-O. & Roberts, D. C.) Ch. 4 (IPCC, 2019).

  • Jasour, Z. Y., Reilly, A. C., Tonn, G. L. & Ferreira, C. M. Roadway flooding as a bellwether for household retreat in rural, coastal regions vulnerable to sea-level rise. Clim. Risk Manag. 36, 100425 (2022).

  • Jacobs, J. M., Cattaneo, L. R., Sweet, W. & Mansfield, T. Recent and future outlooks for nuisance flooding impacts on roadways on the U.S. East Coast. Transp. Res. Rec. 2672, 1–10 (2018).

  • Hummel, M. A., Tcheukam Siwe, A., Chow, A., Stacey, M. T. & Madanat, S. M. Interacting infrastructure disruptions due to environmental events and long‐term climate change. Earth’s Future 8, e2020EF001652 (2020).

  • Hauer, M., Mueller, V. & Sheriff, G. US commuting delays from tidal flooding worsen with sea level rise. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-861767/v1 (2021).

  • Wrathall, D. J. et al. Meeting the looming policy challenge of sea-level change and human migration. Nat. Clim. Change 9, 898–901 (2019).

    Article 

    Google Scholar     

  • Sun, J., Chow, A. C. H. & Madanat, S. M. Equity concerns in transportation infrastructure protection against sea level rise. Transp. Policy 100, 81–88 (2021).

    Article 

    Google Scholar     

  • Pregnolato, M., Ford, A., Glenis, V., Wilkinson, S. & Dawson, R. Impact of climate change on disruption to urban transport networks from pluvial flooding. J. Infrastruct. Dev. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000372 (2017).

  • Hauer, M., Mueller, V., Sheriff, G. & Zhong, Q. More than a nuisance: measuring how sea level rise delays commuters in Miami, FL. Environ. Res. Lett. 16, 064041 (2021).

    Article 

    Google Scholar     

  • Logan, T. M. & Guikema, S. D. Reframing resilience: equitable access to essential services. Risk Anal. 40, 1538–1553 (2020).

    Article 

    Google Scholar     

  • Anderson, M., Kiddle, D. & Logan, T. The underestimated role of the transportation network: improving disaster and community resilience. Transp. Res. Part D 106, 103218 (2022).

  • Sanderson, D., Cox, D., Barbosa, A. & Bolte, J. Modeling regional and local resilience of infrastructure networks following disruptions from natural hazards. J. Infrastruct. Syst. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000694 (2022).

  • Gold, A. C., Brown, C. M., Thompson, S. P. & Piehler, M. F. Inundation of stormwater infrastructure is common and increases risk of flooding in coastal urban areas along the US Atlantic coast. Earth’s Future 10, e2021EF002139 (2022).

  • Bosserelle, A. L., Morgan, L. K. & Hughes, M. W. Groundwater rise and associated flooding in coastal settlements due to sea‐level rise: a review of processes and methods. Earth’s Future 10, e2021EF002580 (2022).

  • Plane, E., Hill, K. & May, C. A rapid assessment method to identify potential groundwater flooding hotspots as sea levels rise in coastal cities. Water 11, 2228 (2019).

    Article 
    CAS 

    Google Scholar     

  • Knott, J. F., Daniel, J. S., Jacobs, J. M. & Kirshen, P. Adaptation planning to mitigate coastal-road pavement damage from groundwater rise caused by sea-level rise. Transp. Res. Rec. 2672, 11–22 (2018).

    Article 

    Google Scholar     

  • Knott, J. F., Elshaer, M., Daniel, J. S., Jacobs, J. M. & Kirshen, P. Assessing the effects of rising groundwater from sea level rise on the service life of pavements in coastal road infrastructure. Transp. Res. Rec. 2639, 1–10 (2017).

  • Matini, N., Qiao, Y. & Sias, J. E. Development of time–depth–damage functions for flooded flexible pavements. J. Transp. Eng. B https://doi.org/10.1061/JPEODX.0000352 (2022).

  • Allen, T. R. et al. Linking water infrastructure, public health, and sea level rise: integrated assessment of flood resilience in coastal cities. Public Works Manag. Policy 24, 110–139 (2019).

    Article 

    Google Scholar     

  • Dempsey, N., Bramley, G., Power, S. & Brown, C. The social dimension of sustainable development: defining urban social sustainability. Sust. Dev. 19, 289–300 (2011).

    Article 

    Google Scholar     

  • Geurs, K. T. & van Wee, B. Accessibility evaluation of land-use and transport strategies: review and research directions. J. Transp. Geogr. 12, 127–140 (2004).

    Article 

    Google Scholar     

  • Sweet, W. V. et al. Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines (NOAA, 2022); https://oceanservice.noaa.gov/hazards/sealevelrise/noaa-nos-techrpt01-global-regional-SLR-scenarios-US.pdf

  • Howden, M. & Jacobs, K. L. in The US National Climate Assessment: Innovations in Science and Engagement (eds Jacobs, K. et al.) 157–171 (Springer International, 2016).

  • Mach, K. J. et al. Managed retreat through voluntary buyouts of flood-prone properties. Sci. Adv. 5, eaax8995 (2019).

    Article 

    Google Scholar     

  • Thiele, B. The human right to adequate housing: a tool for promoting and protecting individual and community health. Am. J. Public Health 92, 712–715 (2002).

    Article 

    Google Scholar     

  • Siders, A. R. Social justice implications of US managed retreat buyout programs. Clim. Change 152, 239–257 (2019).

    Article 

    Google Scholar     

  • Stephens, S. A., Bell, R. G. & Lawrence, J. Developing signals to trigger adaptation to sea-level rise. Environ. Res. Lett. 13, 104004 (2018).

    Article 

    Google Scholar     

  • Haasnoot, M., Kwakkel, J. H., Walker, W. E. & ter Maat, J. Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world. Glob. Environ. Change 23, 485–498 (2013).

    Article 

    Google Scholar     

  • Haasnoot, M., Lawrence, J. & Magnan, A. K. Pathways to coastal retreat. Science 372, 1287–1290 (2021).

    Article 
    CAS 

    Google Scholar     

  • Brovelli, M. A., Minghini, M., Molinari, M. & Mooney, P. Towards an automated comparison of OpenStreetMap with authoritative road datasets. Trans. GIS 21, 191–206 (2017).

    Article 

    Google Scholar     

  • El-Ashmawy, K. L. A. Testing the positional accuracy of OpenStreetMap data for mapping applications. Geod. Cartogr. 42, 25–30 (2016).

    Article 

    Google Scholar     

  • Neis, P. & Zielstra, D. Recent developments and future trends in volunteered geographic information research: the case of OpenStreetMap. Future Internet 6, 76–106 (2014).

    Article 

    Google Scholar     

  • Boeing, G. OSMnx: new methods for acquiring, constructing, analyzing, and visualizing complex street networks. Comput. Environ. Urban Syst. 65, 126–139 (2017).

    Article 

    Google Scholar     

  • Manson, S., Schroeder, J., Van Riper, D., Kugler, T. & Ruggles, S. IPUMS National Historical Geographic Information System: Version 16.0 (IPUMS, 2021).

  • 2020 TIGER/Line Shapefiles (machine-readable datafiles) (US Census Bureau, 2020).

  • Homeland Infrastructure Foundation-Level Data https://hifld-geoplatform.opendata.arcgis.com/ (HIFLD, 2021).

  • Pregnolato, M., Ford, A., Wilkinson, S. M. & Dawson, R. J. The impact of flooding on road transport: a depth-disruption function. Transp. Res. Part D 55, 67–81 (2017).

    Article 

    Google Scholar     

  • Logan, T. M. et al. Evaluating urban accessibility: leveraging open-source data and analytics to overcome existing limitations. Environ. Plan. B 46, 897–913 (2019).


    Google Scholar     

  • Hauer, M. E. Migration induced by sea-level rise could reshape the US population landscape. Nat. Clim. Change 7, 321–325 (2017).

  • LEHD Origin–Destination Employment Statistics Data (2002–2019) (US Census Bureau, 2022).

  • Siri, E., Siri, S. & Sacone, S. Network performance evaluation under disruptive events through a progressive traffic assignment model. IFAC-PapersOnLine 53, 15017–15022 (2020).

    Article 

    Google Scholar     

    • [ad_2]

    Source link

    Copyright No Harm Co 2020. All Rights Reserved
    Privacy Settings
    We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
    Youtube
    Consent to display content from Youtube
    Vimeo
    Consent to display content from Vimeo
    Google Maps
    Consent to display content from Google
    Save