For Peer Review 16 17 9 Environmental Science and Policy Department, George Mason University, 4400 University 18 Dr

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1 TITLE: 2 Tracking Species Recovery Status to Improve Endangered Species Act Decisions 3 4 AUTHORS NAME, AFFILIATION, AND EMAIL: 5 Ya-Wei Li, [email protected] 1 6 Brenda Molano-Flores, [email protected] 2 7 Olivia Davis, [email protected] 3 8 Maximilian L. Allen, [email protected] 2 9 Mark A. Davis, [email protected] 2 10 Jean M. Mengelkoch, [email protected] 2 11 Joseph J. Parkos III, [email protected] 4 12 Anthony Paul Porreca, [email protected] 4 13 Auriel M.V. Fournier, [email protected] 5 14 Alison P. Stodola, [email protected] 2 15 Jeremy Tiemann, [email protected] Peer 2 Review 16 Jason Bried, [email protected] 2 17 Paul B. Marcum, [email protected] 2 18 Connie J. Carroll-Cunningham, [email protected] 2 19 Eric D. Janssen, [email protected] 2 20 Eric F. Ulaszek, [email protected] 2 21 Susan McIntyre, [email protected] 2 22 Suneeti Jog, [email protected] 2 23 Edward P. F. Price, [email protected] 2 24 Julie Nieset, [email protected] 2 25 Tara Beveroth, [email protected] 2 26 Alexander Di Giovanni, [email protected] 6 27 Ryan J. Askren, [email protected] 6 28 Luke J. Malanchuk, [email protected] 6 29 Jared F. Duquette, [email protected] 7 30 Michael Joseph Dreslik, [email protected] 2 31 Thomas C. McElrath, [email protected] 2 32 John B. Taft, [email protected] 2 33 Kirk Stodola, [email protected] 2 34 Jacob Malcom, [email protected] 8,9 35 Andrew Carter, [email protected] 8,9 36 Megan Evansen, [email protected] 8 37 Leah Gerber, [email protected] 3 38 39 40 1 Environmental Policy Innovation Center, 700 K Street, NW, Washington, D.C. 20001 41 42 2 Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana- 43 Champaign, 1816 South Oak St., Champaign IL 61820 44 45 3 Arizona State University, Center for Biology and Society, PO Box 873301, Tempe, AZ 85287 46

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1 4 Kaskaskia Biological Station, Illinois Natural History Survey, Prairie Research Institute, 2 University of Illinois at Urbana-Champaign, 1235 CR 1000 N Sullivan, IL 61951 3 4 5 Forbes Biological Station–Bellrose Waterfowl Research Center, Illinois Natural History 5 Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Havana, IL 6 62644 7 8 6 University of Illinois at Urbana-Champaign, Department of Natural Resources and 9 Environmental Sciences and Illinois Natural History Survey, Urbana, IL 61801 10 11 7 Michigan Department of Natural Resources, Wildlife Division, P.O. Box 30444, Lansing, MI 12 48909 13 14 8 Center for Conservation Innovation, Defenders of Wildlife, 1130 17th Street, NW, Washington, 15 D.C. 20036 For Peer Review 16 17 9 Environmental Science and Policy Department, George Mason University, 4400 University 18 Dr. Fairfax, VA 22030 19 20 SHORT RUNNING TITLE: 21 Tracking Endangered Species Status 22 23 KEYWORDS: 24 Endangered Species Act, monitoring, extinction, recovery, species classification 25 26 TYPE OF ARTICLE: 27 Policy Perspectives 28 29 NUMBER OF WORDS: 30 Abstract – 186 31 Manuscript – 2,981 32 33 NUMBER OF REFERENCES: 34 30 35 36 NUMBER OF FIGURES AND TABLES: 37 3 38 39 CONTACT INFORMATION FOR CORRESPONDENCES: 40 Ya-Wei Li 41 Environmental Policy Innovation Center, 700 K Street, NW, Washington, D.C. 20001 42 [email protected]

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1 ABSTRACT 2 3 The U.S. Endangered Species Act (ESA) protects over 2,000 species, but no concise, 4 standardized metrics exist for assessing changes in species recovery status. Tracking these 5 changes is crucial to understanding species status, adjusting conservation strategies, and 6 assessing the performance of the ESA. We helped develop and test novel metrics that track 7 changes in recovery status using six components. ESA 5-year status reviews provided all of the 8 information used to apply the recovery metrics. When we analyzed the reviews, we observed 9 several key challenges to species recovery. First, the reviews lack a standardized format and 10 clear documentation. Second, despite having been listed for decades, many species still lack 11 basic information about their biology and threats. Third, many species have continued to decline 12 after listing. Fourth, many species currently have no path to recovery. Applying the recovery 13 metrics allowed us to gain these and other insights about ESA implementation. We urge the U.S. 14 Fish and Wildlife Service to adopt the metrics as part of future status reviews in order to inform 15 public discourse on improvingFor conservation Peer policy Review and to systematically track the recovery 16 progress of all ESA species. 17

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1 Introduction 2 To effectively conserve imperiled species, accurate information of a species’ conservation status 3 must be readily available to inform management decisions (IUCN Standards and Petitions 4 Committee, 2019; Bayraktarov et al., 2021). Under the U.S. Endangered Species Act (ESA), no 5 concise, standardized metrics exist for assessing changes in species recovery status (Malcom et 6 al. 2016). Instead, the changes are often evident only when a species’ ESA legal classification 7 changes (i.e., uplisted, downlisted, or delisted). For most ESA-listed species, however, these 8 reclassifications are very rare or nonexistent, making it impossible for them to capture subtle but 9 important changes in recovery progress (USFWS, 2018). For example, a species may require 20 10 years for recovery and delisting from the ESA. During this time, the species may be progressing 11 toward recovery but not enough to trigger a reclassification. Tracking this progress is crucial to 12 understanding species status, adjusting conservation strategies based on this status, and assessing 13 the performance of the ESA. 14 15 The ESA requires the U.S.For Fish and Peer Wildlife Service Review (USFWS) or the National Marine Fisheries 16 Service (NMFS; hereafter “the Services”) to review the status of every listed species with a 17 recovery plan every 5 years. In theory, these reviews should be able to identify changes in 18 recovery status that fall short of reclassification. In practice, the contents of the reviews are 19 rarely standardized, complicating attempts to objectively track status changes or to compare the 20 status of multiple species. For example, no standardized guidelines exist for assessing population 21 reductions or changes in species extinction risk, as seen in other conservation assessments such 22 as the IUCN Red List (IUCN Standards and Petitions Committee, 2019). Further, even if all 5- 23 year reviews were to adopt standardized content, it is impractical to read the reviews for the over 24 1,660 U.S. listed species every 5 years to identify recovery trends (e.g., improving, stable, or 25 declining). 26 27 One solution is for the Services, as part of every 5-year review, to specify species status changes 28 in a concise, standardized manner. This information would allow the agencies to track changes 29 more reliably and to efficiently compare changes across hundreds of species, similar to how a 30 stock index allows for rapid comparison across hundreds of companies. When this species status 31 information is combined with data on species funding, habitat and threat assessments, local and 32 regional administrative variation, and conservation interventions, a fuller picture emerges with 33 greater resolution of the factors affecting species improvement or decline. 34 35 To examine the feasibility this approach, we worked with the USFWS to develop and test novel 36 metrics to track changes in species recovery status. These metrics are designed to concisely 37 reflect the most important information in a 5-year review about how a species’ status has 38 changed since the prior review. Over 75 biologists from five organizations representing 39 government, academia, and nonprofit groups tested the metrics on 50 ESA-listed species: 4 fish, 40 6 herpetofauna, 6 mammals, 8 birds, 4 insects, 1 arachnid, 5 crustacean, and 16 vascular plants 41 (Figure 1). Species were not selected randomly, but rather for taxonomic and geographic 42 diversity, and for recentness of a 5-year review to ensure that our testing covered a variety of 43 species and used updated information. This effort represents the largest number of scientists to 44 have evaluated the recovery status of a group of ESA-listed species using the same metrics. The 45 USFWS is currently considering whether and how to adopt the metrics. 46

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1 In this paper, we summarize the results of our assessment of the metrics and describe major 2 challenges to recovery that we identified during testing and offer recommendations to address 3 them. These challenges and recommendations, based on the 50 test species and our combined 4 experience, apply broadly to a large number of other ESA species. We urge federal agencies to 5 consider these recommendations as part of their efforts to conserve species and restore the role of 6 science (Executive Order No. 13,990, 2021). 7 8 The Recovery Metrics 9 At the outset of our project, the USFWS identified three criteria for evaluating the success of the 10 metrics: 1) metrics capture the critical components of tracking species recovery progress; 2) 11 metrics generate consistent results irrespective of the person applying them; and 3) USFWS 12 biologists can apply the metrics easily and without a significant time commitment. Thus, the 13 metrics must strike a balance between comprehensiveness, reliability, and concision. Based on 14 these criteria, we developed six components to assess changes in species recovery status: 15 1. Species’ current levelsFor of resiliency, Peer redundancy, Review and representation (“3Rs”) (Shaffer & 16 Stein, 2000; Figure 2). 17 2. Changes in the species’ 3Rs since its prior ESA status review. 18 3. Anticipated future changes in the species’ 3Rs. 19 4. Changes in threats to the species since its prior ESA status review. 20 5. Extent to which conservation measures for the species have been implemented and 21 proven effective. 22 6. Progress of the species’ recovery planning efforts, including the number of downlisting / 23 delisting criteria that have been achieved. 24 25 For each component, reviewers selected from several possible responses. For example, for 26 species current levels of 3Rs, the options are “high,” “medium,” “low,” “very low/none,” or 27 “unknown.” Reviewers followed written instructions for applying the metrics that explain each 28 component and the possible responses. Reviewers also indicated the confidence in their 29 assessment qualitatively, similar to qualitative assessments of uncertainty in other environmental 30 contexts (for example, Mastrandrea et al., 2010 and NPS, 2019; but see Morgan 2014). Because 31 5-year reviews do not currently address uncertainty in an organized way, the approach we tested 32 reflects a major improvement over current practice. A completed scorecard example is provided 33 in the online Supporting Information 1. 34 35 The six components are complementary, as each assesses a different aspect of species recovery 36 status. For many species, far more is known about threats than about the 3Rs. In those cases, 37 information on changes in threats may offer better insights for conservation intervention than 38 information on changes in the 3Rs. 39 40 Feedback from the testing allowed the USFWS to adjust the metrics to improve their 41 performance, such that all three criteria for project success were met. First, the metrics captured 42 enough of the factors needed to assess changes in recovery status. Although more factors could 43 have been added, the USFWS had determined that the benefits of doing so were limited for the 44 agency’s purposes. The amount of information gained would not justify the time required to 45 obtain it. 46

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1 Second, the metrics were able to generate consistent results when applied to species with an 2 adequate 5-year review. For the 3R scores, statistical analyses were conducted to determine the 3 extent to which results for each species varied among the reviewers. Specifically, the 3R results 4 were converted to ordinal numbers ranging in 0.5 increments from a minimum of -1.0 5 (representing the most decline in the 3Rs) to a maximum of 1.0 (representing the most 6 improvement in the 3Rs), with 0.0 representing no change. The scores for each species were then 7 analyzed to determine 1) the standard deviation of scores for each of the 3Rs and 2) the 8 differences between the USFWS lead biologist scores for each of the 3Rs and the scores of all 9 other participants (Figure 3; Supporting Information 2). If there were significant differences 10 between the scores of these two groups, that was one indication of the recovery metrics 11 generating inconsistent results. The main cause of variance was the amount and quality of 12 information in a 5-year review. Reviews with limited information or ambiguous language are 13 subject to multiple interpretations, thus leading to higher variance. 14 15 Third, most reviewers didFor not indicate Peer that the metricsReview were too complicated or time consuming 16 to apply. The time required was closely tied to the amount and structure of information in a 5- 17 year review. Among the USFWS reviewers who tracked the duration of this assignment (n=25), 18 88% finished in 60 minutes or less. The metrics performed well enough that the USFWS could 19 begin applying them as part of 5-year reviews. 20 21 The metrics could also be adapted to species that are candidates for ESA listing, as components 22 1-5 of the metrics are not specific to the ESA. In particular, the 3Rs apply as much to non-listed 23 species as to listed species. States and conservation organizations could apply these factors to 24 non-listed species to document in a standardized manner how much conservation has been 25 achieved. The results can better inform ESA decisions on whether to list those species. 26 27 Challenges and Recommendations to Address Them 28 When we applied the metrics to the 50 test species, we identified several key challenges that we 29 have also observed with many other ESA species reviews. 30 31 1. Lack of standardized format and clear documentation of 5-year reviews creates 32 difficulty in comparing progress among species and risks the loss of institutional 33 knowledge. 34 35 The reviews we evaluated varied greatly in detail and substance, with some lacking a 36 comprehensive discussion of the species biology, threats, and effectiveness of conservation 37 measures. A possible explanation is that no checklist or questionnaire exists to remind authors of 38 5-year reviews to provide all of this information. Information-lacking reviews can impede the 39 public’s ability to understand the reviews. Further, information not documented in reviews can 40 contribute to loss of institutional knowledge from turnover of USFWS staff who have unique 41 knowledge of species. 42 43 The USFWS should adopt data management systems that allow biologists to efficiently input, 44 organize, and update this knowledge. This recommendation will provide many long-term 45 benefits such as higher quality 5-year reviews and streamlining the process for writing the 46 reviews, recovery plans, and other ESA documents. For example, if the USFWS were to adopt

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1 an online database that allows its biologists and external partners to easily submit updates about 2 a species in a structured manner, then the process of drafting 5-year reviews would be much 3 faster and easier (Malcom, 2020). 4 5 2. Despite having been listed for decades, many species still lack basic information 6 about their biology, response to threats, and effectiveness of conservation measures. 7 8 One barrier to effective conservation is inadequate information about how best to conserve a 9 species. Among the 50 species, many lacked adequate information about their occurrences, life 10 history characteristics, population genetics, responses to threats, and/or effectiveness of 11 conservation measures. This contributed to a high rate (31% of the 4,969 confidence scores) of 12 “low confidence” or “unknown” scores. An example comes from the Winkler cactus 13 (Pediocactus winkleri), which 9 participants assessed, generating 72 scores for past and future 14 changes in the 3Rs. Of those 72 scores, 58% were “unknown,” which aligns with statements in 15 the species’ 5-year reviewFor about the Peer “lack of knowledge Review about long-term population trends and 16 recruitment rates,” despite the species having been listed since 1998 (USFWS, 2019a). Data 17 deficiencies can also arise when data are collected but never published. 18 19 To address these problems, major investments in applied research and dissemination of the 20 results are crucial. Because the USFWS no longer has a biological research arm, the need has 21 never been stronger for research partnerships among the Services, state wildlife agencies, and the 22 public. In the context of plant conservation, for example, scientists have already proposed 23 strategies for partnerships across multiple types of institutions (Havens et al., 2014; Heywood, 24 2017). The time is overdue for a robust dialogue on how the Services can encourage their 25 external partners to contribute to practical research. One approach is for the agencies to set 26 standards for the type of data they seek from partners. A related approach is to collaborate on 27 multi-species monitoring strategies to address the growing number of species for which 28 biological data are needed to inform recovery actions (DeWan & Zipkin, 2010). 29 30 3. Although many ESA species have made meaningful conservation progress, many 31 others have continued to decline after listing and face a dismal outlook unless they 32 receive far more resources and attention. 33 34 Many conservationists assume that ESA listing automatically leads to a suite of conservation 35 measures that move a species closer to recovery, and that delisting means a species is now 36 “conserved” or no longer requires active management (Scott et al., 2005). This assumption does 37 not reflect the limitations in funding, regulatory protections, political support, and other factors 38 needed for recovery. Among the 50 test species, the mean score for current status of the 3Rs was 39 -0.20 (SD = 0.38) and for future status was -0.32 (SD = 0.43). Negative mean scores represent 40 declines, but are consistent with the findings that 52% of U.S. listed species are in long-term 41 decline (Evans et al., 2016) and that among the 54 non-plant ESA-listed species in Florida over 42 which the USFWS has primary jurisdiction, 28 had declines in demographic and threat statuses 43 (Malcom, 2016). Thus, although the ESA has many successes, it also must deal with the large 44 number of listed species that continue to decline and the likelihood that the number of new 45 listings will vastly outpace the number of recoveries. 46

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1 For many declining species, years of inadequate ESA funding has led to missed opportunities to 2 stabilize and improve species status (Gerber, 2016). Exacerbating this problem is the inadequacy 3 of legal protections, limitations to voluntary conservation on private lands, inconsistency of 4 sociopolitical support, and other barriers to recovery. For example, the 5-year review for the 5 endangered Diamond tryonia snail (Pseudotryonia adamantina) explains that “regulatory 6 mechanisms to manage aquifers…are inadequate to protect the Diamond tryonia against future 7 habitat loss or degradation” (USFWS, 2019b). The mean 3Rs scores for the current (-0.70) and 8 future (-0.74) status of the species underscore its dire condition. 9 10 Although increased funding for on-the-ground recovery actions is imperative, opportunities also 11 exist for the Services and state wildlife agencies to allocate funds to benefit a far greater number 12 of species, especially those facing very high extinction risks. Currently, approximately 80% of 13 federal and state funding goes to 5% of ESA-listed species (Evans et al., 2016). Plants are one of 14 several groups that are particularly underfunded relative to other ESA-listed taxa (Negrón‐Ortiz, 15 2014), even though they representFor 56%Peer of US-listed Review species. Further, a study of 1,125 listed 16 species found that 271 species (24%) were in a state of “injurious neglect,” defined as species 17 that are both in decline and for which recovery efforts are underfunded (Gerber, 2016). A more 18 strategic method of allocating limited recovery funding would result in more effective 19 conservation and likely more species recovered from the ESA (Gerber et al., 2018). The recovery 20 metrics can track species response to funding and allow adjustment of funding levels based on 21 that response. 22 23 4. Prioritizing extinction prevention or stabilization for certain species. 24 25 About 38% of the 50 species we reviewed appear to currently have no path to full recovery and 26 delisting under the ESA, in line with a larger assessment that found delisting is not considered 27 possible for approximately 26% of the 1,173 species with recovery plans (Neel et al., 2012). In 28 fact, many of the Hawaiian plants and invertebrates in the study have struggled to meet 29 extinction prevention goals, much less downlisting goals. For example, the St. John Kaala 30 (Phyllostegia kaalaensis) is a Hawaiian flowering plant that is now extinct in the wild and for 31 which all outplanted specimens have died (USFWS, 2019c). Further, the most recent USFWS 32 status assessment for the northern riffleshell mussel (Epioblasma torulosa rangiana) states that it 33 is "doubtful that [the two delisting criteria] could be met" (USFWS, 2019d). The assessment for 34 the eastern indigo snake (Drymarchon couperi) anticipates that even under the most optimistic 35 “conservation-focused” future scenario for the species, its 3Rs are expected to continue declining 36 and island populations are expected to become extirpated due to sea level rise and urbanization 37 (USFWS, 2019e). The ring pink mussel (Obovaria retusa) may already be functionally extinct, 38 as only two specimens have been found in the last 15 years (USFWS, 2019f). For these and other 39 species we evaluated, threats such as climate change, disease, invasive species, urbanization, and 40 large-scale water withdrawal may have already foreclosed all known paths to recovery. As a 41 result, these species may require listing indefinitely (Doremus & Pagel, 2001). 42 43 This is not to suggest, however, that listing these species was pointless. In fact, prior studies 44 indicate that hundreds of species may have gone extinct if they had not been listed (Taylor et al., 45 2005). The inability to delist certain species, however, does suggest at least three policy 46 responses.

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1 2 One is the need to identify conservation milestones using more achievable goals such as 3 extinction prevention or stabilization (HPPRCC, 2011). The metrics we tested could help fill this 4 gap by tracking how the 3Rs change every 5 years, irrespective of whether the changes are 5 significant enough to warrant downlisting or delisting. 6 7 A second response is the need to prevent highly imperiled species from declining any further and 8 to conserve at-risk species before they decline to the point where recovery becomes extremely 9 difficult or improbable. In the past, the USFWS has allocated some of its recovery funds to 10 projects designed specifically to prevent extinction, but the agency has not been adequately 11 funded in recent years to resurrect this program. If adopted, the recovery metrics would help 12 measure the conservation benefits of the program. As for the large number of at-risk species, 13 funding to implement State Wildlife Action Plans and local conservation efforts is essential 14 because the federal government has not assumed the authority to manage most of those species. 15 For Peer Review 16 A third response is the possibility for the Services to develop new ESA regulatory approaches 17 that reward landowners and businesses for helping populations reach their conservation goals, 18 even if the entire species still has no path to delisting. For example, for threatened species, the 19 USFWS can issue special rules that relax the ESA’s regulatory prohibitions only for populations 20 that are improving or have met their recovery targets (USFWS, 2006). The recovery metrics can 21 help identify these populations. 22 23 Closing 24 If adopted, the recovery metrics will expand the foundational knowledge needed to understand 25 changes in species status and to make better ESA decisions. To perform effectively, the metrics 26 require adequate and organized information in 5-year reviews. Our testing revealed opportunities 27 for the USFWS to improve the quality and consistency of those reviews and underscored other 28 related challenges to species recovery. 29 30 Acknowledgments and Data 31 We thank Eric M. Schauber and Christopher A. Taylor for INHS institutional support and 32 species assessment respectively. 33 34 References 35 Bayraktarov, E., Ehmke, G., Tulloch, A.I.T., Chauvenet, A.L., Avery-Gomm, S., McRae, L., 36 Wintle, B.A., O'Connor, J., Driessen, J., Watmuff, J., Nguyen, H.A., Garnett, S.T., Woinarski, J., 37 Barnes, M., Morgain, R., Guru, S., & Possingham, H.P. (2021). A threatened species index for 38 Australian birds. Conservation Science and Practice, 3(2), e322. 39 https://doi.org/10.1111/csp2.322 40 41 DeWan, A.A. & Zipkin, E.F. (2010). An integrated sampling and analysis approach for improved 42 biodiversity monitoring. Environmental Management. 45, 1223–1230. 43 https://doi.org/10.1007/s00267-010-9457-7 44

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1 Doremus, H., & Pagel, J. E. (2001). Why Listing may be forever: Perspectives on Delisting 2 under the U.S. Endangered Species Act. Conservation Biology, 15(5), 1258–1268. 3 https://doi.org/10.1111/j.1523-1739.2001.00178.x 4 5 Evans, D. M., Che-Castaldo, J. P., Crouse, D., Davis, F. W., Epanchin-Niell, R., Flather, C. H., 6 Frohlich, R.K., Goble, D.D., Li, Y-W., Male, T.D., Master, L.L., Moskwik, M.P., Neel, M.C., 7 Noon, B.R., Parmesan, C., Schwartz, M.W., Scott, J.M., & Williams, B.K. (2016). Species 8 recovery in the United States: Increasing the Effectiveness of the Endangered Species Act. Issues 9 in Ecology. 20, 1–28. Retrieved from https://www.esa.org/esa/wp- 10 content/uploads/2016/01/Issue20.pdf 11 12 Exec. Order No. 13990, 86 C.F.R. 7037 (2021). 13 14 Gerber, L. R. (2016). Conservation triage or injurious neglect in endangered species recovery. 15 Proceedings of the NationalFor Academy Peer of Sciences, Review 113(13), 3563–3566. 16 https://doi.org/10.1073/pnas.1525085113 17 18 Gerber, L. R., Runge, M. C., Maloney, R. F., Iacona, G. D., Drew, C. A., Avery-Gomm, S., 19 Brazill-Boast, J., Crouse, D., Epanchin-Niell, R.S., Hall, S.B., Maguire, L.A., Male, T., Morgan, 20 D., Newman, J., Possingham, H.P., Rumpff, L., Weiss, K.C.B., Wilson, R.S., & Zablan, M.A. 21 (2018). Endangered species recovery: A resource allocation problem. Science, 362, 284–286. 22 https://doi.org/10.1126/science.aat8434 23 24 Havens, K., Kramer, A. T., & Guerrant, E.O. (2014). Getting plant conservation right (or not): 25 the case of the United States. International Journal of Plant Sciences, 175, 3–10. 26 https://doi.org/10.1086/674103 27 28 [HPPRCC] Hawai`i and Pacific Plants Recovery Coordinating Committee. (2011). 29 Revised recovery objective guidelines. Unpublished. 8 pp. 30 31 Heywood, V. H. (2017). Plant conservation in the Anthropocene – challenges and future 32 prospects. Plant Diversity, 39, 314–330. https://doi.org/10.1016/j.pld.2017.10.004 33 34 IUCN Standards and Petitions Committee. (2019). Guidelines for using the IUCN Red List 35 categories and criteria. Version 14. Prepared by the IUCN SSC Standards and Petitions 36 Committee. Retreived from http://www.iucnredlist.org/documents/RedListGuidelines.pdf 37 38 Malcom, J.W., Webber, W.M., & Li Y-W. (2016). A simple, sufficient, and consistent method to 39 score the status of threats and demography of imperiled species. PeerJ, 4:e2230. 40 https://doi.org/10.7717/peerj.2230 41 42 Malcom, J.W. (2020). Online Recovery Plans for Threatened and Endangered Species. Report to 43 Department of Defense Legacy Resource Management Program. 44 45 Mastrandrea, M.D., Field, C.B., Stocker, T.F., Edenhofer, O., Ebi, K.L., Frame, D.J., Held, H., 46 Kriegler, E., Mach, K.J., Matschoss, P.R., Plattner, G.K., Yohe, G.W., & Zwiers, F.W. (2010).

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1 Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment 2 of Uncertainties. Intergovernmental Panel on Climate Change (IPCC). 3 4 Morgan, M. G. (2014). Use (and abuse) of expert elicitation in support of decision making for 5 public policy. PNAS 111, 7176–7184. doi:10.1073/pnas.1319946111. 6 7 [NPS] National Park Service. (2019). Natural resource condition assessment: Golden Gate 8 National Recreation Area. Natural Resource Report NPS/GOGA/NRR—2019/2031. National 9 Park Service, Fort Collins, Colorado. Retrieved from 10 https://www.nps.gov/orgs/1439/nrca_goga.htm 11 12 Neel, M. C., Leidner, A. K., Haines, A., Goble, D. D., & Scott, J. M. (2012). By the Numbers: 13 How is Recovery Defined by the US Endangered Species Act? BioScience, 62(7), 646–657. 14 https://doi.org/10.1525/bio.2012.62.7.7 15 For Peer Review 16 Negron-Ortiz, V. (2014). Pattern of expenditures for plant conservation under the Endangered 17 Species Act. Biological Conservation 171:36-43. https://doi.org/10.1016/j.biocon.2014.01.018 18 19 Scott, J.M., Goble, D.D., Wiens, J.A., Wilcove, D.S., Bean, M., & Male, T. (2005). Recovery of 20 imperiled species under the Endangered Species Act: The need for a new approach. Frontiers in 21 Ecology and the Environment 3(7):383–389. https://doi.org/10.2307/3868588 22 23 Shaffer M. L., & Stein M. A. (2000). Safeguarding our precious heritage. In: B.A. Stein, L.S. 24 Kutner, & J.S. Adams (Eds.), Precious Heritage: The Status of Biodiversity in the United States 25 (pp. 301-321). Oxford University Press. 26 27 Taylor, M.F., Suckling, K.F., & Rachlinski, J.J. (2005). The effectiveness of the Endangered 28 Species Act: a quantitative analysis. BioScience, 55(4), 360–367. https://doi.org/10.1641/0006- 29 3568(2005)055[0360:TEOTES]2.0.CO;2 30 31 [USFWS] U.S. Fish and Wildlife Service. (2016). USFWS Species Status Assessment 32 Framework: an integrated analytical framework for conservation. Version 3.4 dated August 33 2016. https://www.fws.gov/endangered/improving_ESA/pdf/SSA%20Framework%20v3.4- 34 8_10_2016.pdf 35 36 [USFWS] U.S. Fish and Wildlife Service. (2018). Report to Congress on the Recovery of 37 Threatened and Endangered Species Fiscal Years 2015-2016. 38 https://www.fws.gov/endangered/esa-library/pdf/Recovery-Report-FY2015-2016.pdf 39 40 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2006). Reclassification of the Gila Trout 41 (Oncorhynchus gilae) From Endangered to Threatened; Special Rule for Gila Trout in New 42 Mexico and Arizona, 71 Fed. Reg. 40,657 (July 18, 2006). 43 44 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019a). 5-Year Review for Winkler Cactus 45 (Pediocactus winkleri) and San Rafael Cactus (Pediocactus despainii). 46

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1 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019b). 5-Year Review for Diamond 2 Tryonia 3(Pseudotryonia adamantina). 4 5 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019c). 5-Year Review for Phyllostegia 6 kaalaensis (no common name). 7 8 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019d). 5-Year Review for Northern 9 Riffleshell (Epioblasma torulosa rangiana). 10 11 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019e). 5-Year Review for Eastern indigo 12 snake (Drymarchon corais couperi). 13 14 [USFWS] U.S. Fish and Wildlife Service (USFWS). (2019f). 5-Year Review for Ring Pink 15 (Obovaria retusa). For Peer Review

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8% For Peer Review 16% fish 32% birds herpetofauna mammals insects arachnid 12% crustacean vascular plants

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SUPPORTING INFORMATION 1

Example of completed recovery metrics for the slickspot peppergrass.

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SUPPORTING INFORMATION 2

Below are the scores for past change and future change in the 3Rs, based on the first round of testing with 50 species using the initial version of the recovery metrics. Here is an explanation of each column: • No. of 3R scores – This specifies the total number of 3R scores for the species, providing you with the sample size. The number of scores can vary within a species and among species because not every person assigned to a species provided scores. • 3R scores (mean) – This specifies the mean of all the 3R scores for the species. • 3R scores (SD) – This specifies the standard deviation for all the 3R scores for the species. • Overlap in scores between lead biologist and all others (%) – This specifies the difference in the scores between the FWS lead biologist for a species and all the other study participants for that species. Following the convention described in the table below, a “0-0.5 diff.” means that the two sets of scoresFor were Peeridentical (0 difference)Review or very similar (only 0.5 units apart). The same interpretation applies for “1 diff.” and “1.5-2 diff.” For example, for the Austin blind salamander, 97% of the 37 scores provided for the past change in the 3Rs were identical or very similar to the lead biologist’s score.

Qualitative score from Numeric equivalent for test results statistical analysis

Decline -1.0

Some decline -0.5

No change 0

Some improvement 0.5

Improvement 1.0

Unknown N/A

No. of 3R 3R scores Overlap in scores between lead scores biologist and all others (%)

Mean SD 0-0.5 diff. 1 diff. 1.5-2 diff. Salamander, Austin blind Past change 37 -0.27 0.31 97% 3% 0% Future change 37 -0.47 0.32 100% 0% 0% Salamander, Barton Springs Past change 26 0.19 0.6 82% 6% 12% Future change 26 -0.35 0.59 78% 22% 0% Umbel, Huachuca water Past change 37 -0.61 0.25 100% 0% 0% Future change 34 -0.55 0.41 100% 0% 0% Cactus, Kuenzler hedgehog Past change 31 0.33 0.34 93% 4% 4% Future change 30 -0.04 0.47 81% 12% 8% Beetle, American burying Past change 37 0.14 0.41 67% 33% 0% Future change 35 -0.34 0.61 68% 3% 29% Pronghorn, Sonoran Past change 32 0.01 0.19 100% 0% 0% Future change 10 0.04 0.07 100% 0% 0%

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Rattlesnake, New Mexican ridge-nosed Past change 30 -0.33 0.43 85% 15% 0% Future change 30 -0.56 0.34 88% 12% 0% Tryonia, Diamond Past change 27 -0.7 0.25 100% 0% 0% Future change 35 -0.74 0.26 100% 0% 0% Eider, Steller's Past change 30 -0.28 0.35 91% 9% 0% Future change 32 -0.36 0.35 89% 11% 0% Bear, Polar Past change 40 -0.28 0.39 89% 11% 0% Future change 42 -0.46 0.44 74% 21% 5% Salamander, frosted flatwoods Past change 30 -0.91 0.17 100% 0% 0% Future change 32 -0.73 0.53 0% 18% 82% Spider, Spruce fir moss Past change 8 -0.06 0.21 78% 22% 0% Future change 19 -0.3 0.34 93% 7% 0% Hawk, Puerto Rican broad- winged PastFor change Peer33 -0.27Review 0.45 83% 14% 3% Future change 30 -0.3 0.6 58% 0% 42% Ring pink (mussel) Past change 30 -0.56 0.46 50% 50% 0% Future change 26 -0.66 0.37 86% 14% 0% Quillwort, Louisiana Past change 27 0.07 0.26 90% 10% 0% Future change 20 -0.22 0.4 N/A N/A N/A Darter, yellowcheek Past change 27 -0.31 0.53 50% 21% 29% Future change 26 -0.24 0.45 75% 17% 8% Darter, relict Past change 32 0.37 0.25 96% 4% 0% Future change 31 0.21 0.35 100% 0% 0% Spurge, Telephus Past change 27 0.03 0.41 74% 26% 0% Future change 29 -0.07 0.47 56% 32% 12% Mouse, Anastasia Island beach Past change 35 -0.24 0.29 100% 0% 0% Future change 35 -0.27 0.28 100% 0% 0% Snake, eastern indigo Past change 26 -0.31 0.48 82% 18% 0% Future change 31 -0.73 0.4 81% 19% 0% Orchid, eastern prairie fringed Past change 29 0.02 0.53 65% 30% 5% Future change 27 -0.08 0.49 72% 17% 11% skipperling, Poweshiek Past change 23 -0.85 0.23 N/A N/A N/A Future change 12 -0.93 0.13 N/A N/A N/A Butterfly, Karner blue Past change 29 -0.47 0.34 92% 8% 0% Future change 27 -0.52 0.27 100% 0% 0% Riffleshell, northern Past change 27 -0.39 0.43 78% 22% 0% Future change 29 -0.32 0.46 80% 20% 0% Lousewort, Furbish Past change 36 -0.4 0.42 78% 13% 9% Future change 40 -0.74 0.27 97% 3% 0% Tiger beetle, Puritan Past change 34 0.12 0.39 87% 10% 3% Future change 28 -0.14 0.44 82% 18% 0% Snail, Chittenango ovate amber Past change 29 -0.29 0.44 80% 20% 0% Future change 27 -0.37 0.56 N/A N/A N/A sage-grouse, Gunnison Past change 31 -0.15 0.34 96% 4% 0% Future change 35 -0.44 0.4 74% 26% 0% Cactus, Winkler Past change 15 0.2 0.3 90% 10% 0%

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Future change 15 -0.46 0.46 N/A N/A N/A Mouse, Preble's meadow jumping Past change 8 0 0 100% 0% 0% Future change 4 0 0 N/A N/A N/A elepaio, Oahu Past change 32 -0.33 0.41 68% 32% 0% Future change 27 -0.44 0.4 83% 17% 0% Duck, Hawaiian (=koloa) Past change 34 -0.28 0.43 90% 10% 0% Future change 29 -0.39 0.53 68% 20% 12% Coot, Hawaiian Past change 35 0.02 0.32 84% 16% 0% Future change 30 -0.26 0.36 88% 12% 0% gallinule, Hawaiian common Past change 36 -0.08 0.32 94% 6% 0% Future change 34 -0.29 0.36 90% 10% 0% Daisy, Willamette Past change 31 0.05 0.64 59% 19% 22% Future change 21 -0.18 0.62 71% 6% 24% Haha PastFor change Peer34 -0.06Review 0.55 77% 10% 13% Future change 26 -0.37 0.6 59% 41% 0% Lo'ulu Past change 27 -0.22 0.54 78% 22% 0% Future change 28 -0.1 0.54 75% 25% 0% Phyllostegia kaalaensis Past change 43 -0.53 0.51 59% 41% 0% Future change 43 -0.55 0.5 59% 41% 0% Kadua parvula Past change 36 -0.04 0.5 75% 25% 0% Future change 30 -0.13 0.5 81% 19% 0% Akoko Past change 31 -0.84 0.3 74% 4% 22% Future change 35 -0.66 0.44 97% 3% 0% Snails, Oahu tree Past change 30 -0.6 0.39 85% 12% 4% Future change 32 -0.66 0.36 86% 14% 0% Oha Past change 30 0.14 0.33 88% 12% 0% Future change 25 0.14 0.39 67% 33% 0% Frog, mountain yellow-legged Past change 36 -0.38 0.43 88% 13% 0% Future change 35 -0.26 0.5 65% 23% 13% Plover, western snowy Past change 35 0.18 0.47 78% 22% 0% Future change 32 0.09 0.41 87% 13% 0% Sucker, Lost River Past change 39 -0.43 0.45 71% 26% 3% Future change 36 -0.3 0.61 44% 28% 28% Sucker, shortnose Past change 35 -0.43 0.46 68% 32% 0% Future change 33 -0.34 0.57 55% 17% 28% Spineflower, Howell's Past change 28 0.25 0.29 95% 5% 0% Future change 17 0 0.28 73% 27% 0% Grass, Eureka Dune Past change 32 0.05 0.45 74% 17% 9% Future change 32 -0.13 0.49 57% 32% 11% Mountain beaver, Point Arena Past change 33 -0.02 0.24 90% 10% 0% Future change 34 -0.3 0.4 93% 7% 0% Sheep, Sierra Nevada bighorn Past change 33 0.28 0.48 91% 4% 4% Future change 33 0.18 0.53 61% 17% 22%