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Protecting Endangered Species: Practise the Principal Legislative Tools Work?

• David J. Currie

Protecting Endangered Species: Practise the Principal Legislative Tools Work?

• Katherine E. Gibbs,
• David J. Currie

x

• Published: May 2, 2012
• https://doi.org/10.1371/journal.pone.0035730

Figures

Abstract

It is disquisitional to assess the effectiveness of the tools used to protect endangered species. The main tools enabled under the U.S. Endangered Species Act (ESA) to promote species recovery are funding, recovery program development and critical habitat designation. Earlier studies sometimes establish that statistically significant effects of these tools could be detected, only they have not answered the question of whether the furnishings were large enough to be biologically meaningful. Hither, nosotros ask: how much does the recovery status of ESA-listed species improve with the awarding of these tools? We used species' staus reports to Congress from 1988 to 2006 to quantify two measures of recovery for 1179 species. We related these to the amount of federal funding, years with a recovery plan, years with critical habitat designation, the corporeality of peer-reviewed scientific information, and fourth dimension listed. We found that change in recovery condition of listed species was, at best, only very weakly related to any of these tools. Recovery was positively related to the number of years listed, years with a recovery plan, and funding, however, these tools combined explain <13% of the variation in recovery status among species. Earlier studies that reported significant effects of these tools did not focus on event sizes; even so, they are in fact similarly small. One must conclude either that these tools are non very effective in promoting species' recovery, or (as nosotros suspect) that species recovery information are then poor that it is incommunicable to tell whether the tools are constructive or non. It is critically important to appraise the effectiveness of tools used to promote species recovery; it is therefore also critically important to obtain population status data that are acceptable to that job.

Citation: Gibbs KE, Currie DJ (2012) Protecting Endangered Species: Practise the Main Legislative Tools Work? PLoS Ane 7(5): e35730. https://doi.org/10.1371/journal.pone.0035730

Editor: Bernd Schierwater, University of Veterinary Medicine Hanover, Germany

Received: June x, 2011; Accepted: March 23, 2012; Published: May ii, 2012

Copyright: © 2012 Gibbs, Currie. This is an open-access article distributed under the terms of the Creative Eatables Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was funded by grants from the Natural Sciences and Engineering Research Quango of Canada. The funders had no role in written report blueprint, information collection and analysis, conclusion to publish, or preparation of the manuscript.

Competing interests: The authors take declared that no competing interests be.

Introduction

For conservation efforts to succeed, it is disquisitional to evaluate the effectiveness of bachelor conservation tools and to conform management accordingly [one]. The U.Southward. Endangered Species Act (ESA) is i of the oldest and most comprehensive pieces of endangered species legislation and one of the principal mechanisms for preventing species' extinction [2], [three]. The primary tools enabled nether the act that are applicable to all species are protection from take, section seven consultation, funding, recovery plan development and implementation, and disquisitional habitat designation [4]. In that location are other tools such every bit Habitat Conservation Plans, Rubber Harbor Agreements and Candidate Conservation Agreements that are used on a example by instance ground [5].

However, fifty-fifty the primary tools have not been practical equally to all species listed under the Act. This provides a quasi-experimental test of their efficacy: if the tools enabled under the ESA are effective, 1 would expect that, on average, recovery of species listed nether the Deed would be positively related to measures of the degree of implementation of those tools. Here, we ask: how strongly does the evidence back up this prediction?

Our question is not whether whatever species have benefitted from the ESA; this is undoubtedly true: e.g. Aleutian Canadian goose, Robbins' cinquefoil and Kirtland's Warbler [half dozen], [seven]. Rather, nosotros ask whether, on boilerplate, recovery is improved materially in species that take benefitted from the tools enabled under the ESA. Previous studies have concluded that various tools nether the Act are effective, based on pregnant statistical relationships [8], [9], [10]. Nevertheless, whether tools implemented under the ESA have had detectable effects (i.e., statistically significant) is at to the lowest degree partly an result of statistical power. Arguably, the more important question is how large or small those effects have been. Extant work has non addressed this question.

Consider these tools in more detail. Once listed, species are protected from take, which includes harassing, harming, or killing [eleven]. Species also benefit from Section 7 consultation, which states that federal agencies must consult with the Fish and Wildlife Service (FWS) to ensure that their actions do non jeopardize the species [four]. The Fish and Wildlife Services and the National Oceanic Atmospheric Assistants (NOAA) provide funding for a diverseness of purposes involving listed species [12], including habitat acquisition, inquiry, and enforcement. Further, the Act requires that a recovery plan be adult and implemented for every listed species, except when such a program will non promote conservation of the species [11]. The recovery program details the conservation deportment that are necessary for recovery. Critical habitat (CH), defined every bit the specific areas within the geographical area occupied by the species, at the time information technology is listed, essential to the conservation of the species, is designated at the time of listing when judged to be 'prudent and determinable' [11].

Disquisitional habitat designation is the near controversial aspect of the Deed [xiii]. Although required for all species, it is currently but in identify for 43% of U.S. listed species [14]. Critical habitat can be cited as 'undeterminable' or 'non prudent' to avoid designation [15]. In early on 2000, only 10% of species had CH designation. This prompted legal activeness, and a large number of designations were pushed through by court order [16], [17]. The Section of the Interior claimed that the alluvion of CH designations was undermining endangered species conservation by using up funds and that it "does not result in any do good to the species that is non already afforded by the protections" in other aspects of the Act [eighteen]. Federal agencies are already required nether the Human activity to consult with FWS to ensure that their actions practise not adversely modify species habitat to a indicate where it would jeopardize species [xix]. Nevertheless, this protection merely applies to lands currently occupied by the species. Critical habitat designation tin get a pace further and designate areas that are currently unoccupied by the species but deemed necessary for their recovery [20]. This controversy highlights the necessity of studying the consequence of CH designation on species recovery [four].

Earlier studies that take attempted to assess the effectiveness of the ESA yielded conflicting results. Kirkvliet and Langpap [eight] examined the recovery status of 225 listed species and concluded that spending reduced the probability of species doing poorly but was unrelated to the probability of doing well. They establish that having a recovery plan (either in progress or completed) decreased the probability of species being reported as failing and increased the probability of species being stable or increasing. They did not find prove that CH designation promotes species recovery. Taylor et al. [10] considered a larger ready of listed species (North = 1095). Looking separately at single species and multi-species recovery plans, they establish a positive effect of single species recovery plans but no effect of multi-species plans. They argued that species with CH designation were more likely to be increasing and less likely to exist decreasing than species without CH designation. In contrast, Male person and Bean [9], using a similar data set up that included federal funding, concluded that species status was positively related to funding but was non significantly related to CH designation. Miller et al. [21] calculated funding as the amount of money received divided past the corporeality requested in the species recovery program. They found that with increased funding, species status was more probable to be improving. Boersma et al. [22] examined the effectiveness of recovery plans in item and plant that single species plans and those with a variety of authors are related to increased likelihood of species doing well. In each case, the authors focus on whether statistical relationships are detectable, as opposed to how strong those relationships are.

In this report, we examine two measures of species recovery: population status trends (on which near earlier studies take focused) and the number of recovery objectives achieved (amid those listed in the species' recovery plan). We test how much of the inter-specific variation in recovery of ESA-listed species tin can be statistically attributed to how long the species has been listed (i.east, the base protection from beingness listed), how long a recovery programme has been in place, whether and how long critical habitat has been designated, and federal funding. If such tools improve species' recovery, then modify in species status over time and number of recovery objectives achieved should relate reasonably strongly to these variables. Since ane of the main intentions of funding and recovery plan development is to back up research and to increase what is known most a given species, we also wait at the relationship between recovery status and the amount of published peer-reviewed scientific information available on each species. We wait more closely at the effect of CH designation by comparing species' condition before and after designation. We too examination whether the result of CH designation is stronger for species who are specifically threatened past habitat loss.

Not all species take a recovery status trend reported in each recovery report, presumably due to lack of information. We also test whether the availability of status information relates to the amount of peer-reviewed scientific information, funding, time listed, or taxonomic group.

Methods

Recovery condition was assessed for all U.Southward. and articulation U.S./foreign species listed nether the Endangered Species Act prior to 2003 (Dataset S1). Ii measures of species recovery – change in population status over time, and the proportion of recovery objectives achieved past 2006, were extracted from biennial recovery reports to Congress from 1988–2006 [23]. Population status reports rate each species equally decreasing, stable, increasing or unknown, relative to the previous report based on population size estimates as well every bit perceived threats [23]. These assessments are often based on qualitative information and tin can exist based solely on the judgment of a species proficient, but they are the all-time species condition data available for all ESA listed species [22].

Using the population status information, nosotros calculated an index of change in condition over the period 1988–2006 following Male person and Bean [xix]. For a given species, we first assigned a value of −1, 0 or 1 to each status study for declining, stable or increasing, respectively. These values were then summed, resulting in a last species score ranging from −nine to +9. Non all species had a condition study for every biennial period in the data set. For these species, we calculated the proportion of reporting periods for which the population trend was known. Nosotros adjusted the terminal status score by dividing it by the proportion of known reports such that all population trend indices are based finer on an 18 year menstruum. This assumes that missing status data is equal to the average of the observed reports. Our second metric of recovery condition, the recovery objectives achieved, is reported on a scale from ane to 4 representing the percent of recovery objectives that have been achieved, according to the most recent recovery report used in the analysis (2006). We excluded species with multiple listed populations where each population had a dissimilar status; otherwise they were included as one record. Species presumed extinct in the wild or found just in captivity were also excluded.

Yearly funding was obtained from annual expenditure reports to Congress covering 1989–2004 which include all reported federal and state funding [12]. For each species, we calculated hateful yearly funding. Considering different species require dissimilar amounts of funding, we also calculated mean yearly funding received equally a proportion of the hateful yearly estimated cost of recovery given in the recovery plan for each species [14]. Analysis using the proportional funding data is therefore limited to species that have a recovery plan with recovery cost estimates (739 species).

For each species, we recorded the number of years since list, CH designation and recovery plan completion using 2004 every bit the base year [14]. Peer-reviewed scientific information was estimated as the number of studies found from a Spider web of Scientific discipline search conducted in July 2007 of each species' scientific proper name. Nosotros also recorded whether habitat loss was a threat for each species, based on NatureServe [24] and the FWS recovery plans [14]. We separated threats into 3 categories: direct habitat loss (east.g. habitat destroyed for residential development), habitat related threats (east.g. habitat degradation, pollution) and non-habitat related threats (e.g. overharvest, predation or competition from introduced species). If whatever direct habitat loss threats were mentioned, and so it was recorded every bit such regardless of whether other threats were also nowadays. Species were grouped into seven taxonomic groups: amphibians, birds, fish, invertebrates, mammals, plants and reptiles.

Generalized linear models were used to test the relationships between measures of species recovery and the independent variables. Full general linear models were performed for the population status data and the proportion of periods for which a status estimate was available was used as a weighting factor. Proportional odds multinomial logistic models were performed for the recovery objective variable. We use McFadden's pseudo R-square as a measure out of explained variability [25], [26]. We did these analyses for all species combined, and within taxonomic groups. Mean yearly funding and peer-reviewed information were log-transformed, and all variables were standardized (mean = 0, s.d. = 1).

Nosotros did 2 additional tests to focus more explicitly on the effect of CH designation. To determine whether the result of CH designation on condition depends on the caste to which species are jeopardized by habitat-related threats, nosotros compared the effect of CH designation on status for each threat category separately. We did a second analysis using simply species for which CH had been designated. This assay included the 218 species with status information both before and after their CH designation. For these species, we calculated the difference betwixt the average status before and after CH designation. To control for any positive effect of being listed, with or without CH, we too calculated the average alter in condition of species without CH designation.

Results

This study included 1179 species listed earlier 2003, of which plants fabricated upward 61%, invertebrates fourteen%, fish ix%, birds 6%, mammals 5%, reptiles three% and amphibians 2%. Population condition data were bachelor for 1146 species; 33 species were excluded considering they had unknown status in every recovery study. We adjusted population condition scores for a farther 796 species that had at least one unknown status study. Because all 1146 species, the trends in population condition neither improved nor worsened from 1988–2006 (median slope = 0.0). The median status score for all species was −3: i.e., populations by and large declined relative to earlier reports. Recovery objective data were bachelor for 1169 species (all except 10 marine species under NOAA jurisdiction). Over all species, the median recovery objective value is a score of ane which loosely corresponds to 0–25% of the recovery objectives achieved.

Recovery is detectably related to some of the factors expected to promote recovery, but the overall variation explained is modest. In the strongest model, the proportion of recovery objectives achieved was significantly positively related to the number of years listed (p<0.0001; Fig. 1a), amount of peer-reviewed scientific information (p<0.0001; Fig. 1b), funding as a proportion of the corporeality required (p = 0.024), and years with a recovery program (p = 0.005) (Table i). A chiselled variable distinguishing among taxonomic groups was too significant (p = 0.035): birds, mammals and fish have recovered better, on average, than plants, amphibians and invertebrates. The overall model explained 13% of the variation in recovery objectives achieved (i.e., pseudo R² = 0.129).

Figure i. Recovery objectives accomplished as a office of years listed and scientific data.

Scatter plots of recovery objectives achieved and (a) number of years listed and (b) amount of peer-reviewed scientific information. Peer-reviewed scientific information is calculated as the number of Web of Scientific discipline search conducted in July of 2007 of each species' scientific name and is natural logarithm transformed. Lines on the graphs show LOWESS smoothing functions with tension = 0.seven. N = 1169.

https://doi.org/10.1371/journal.pone.0035730.g001

Nosotros observed similar results for the change in population status over time. Status was significantly related to taxon (p = 0.017), years listed (p = 0.029) and proportional funding (p<0.0001; Fig. two; pseudo R² for full model = 0.080). Population status was also related to mean yearly funding, merely less strongly than to proportional funding (Table 1). Peer-reviewed scientific information and mean yearly funding were strongly collinear (r = 0.635, p<0.0001; Fig. 3a); we therefore did not include both variables in our models.

Figure 2. Human relationship betwixt population status and funding.

Scatter plot of species population status score and the proportion of funding requested in species recovery plan that has been received. Proportion of funding received is natural logarithm transformed. Line shows LOWESS smoothing function with tension = 0.7. Northward = 752.

https://doi.org/x.1371/journal.pone.0035730.g002

Effigy 3. Relationships between funding, scientific information and the proportion of known reports.

Besprinkle plots showing the relationship between (a) mean yearly funding and the amount of peer-reviewed scientific information available on a species, (b) mean yearly funding and the proportion of known reports and (c) amount of peer-reviewed scientific data and the proportion of known reports. Peer-reviewed scientific data is calculated as the number of Web of Scientific discipline search conducted in July of 2007 of each species' scientific name. Hateful yearly funding and peer-reviewed scientific information are natural logarithm transformed. Lines on the graphs show LOWESS smoothing functions with tension = 0.7. N = 1169.

https://doi.org/10.1371/periodical.pone.0035730.g003

Within taxonomic groups, pregnant relationships were found for birds, fish, mammals, invertebrates and plants; still, once once again, the effect sizes were quite small-scale. Overall, years listed was the most important variable for all groups and peer-reviewed scientific data and funding were important for nigh groups. The strongest relationships (R²>0.15) were establish for birds, mammals and plants. For birds, population status was significantly positively related to years listed (N = 69; pseudo R² = 0.213). Population condition for mammals was significantly positively related to proportional funding, simply negatively related to disquisitional habitat designation (N = 29; pseudo R² = 0.399). The proportion of recovery objectives attained for plants was significantly positively related for years listed, peer-reviewed information and proportional funding (Northward = 519; pseudo Rⁱⁱ = 0.193).

Species' recovery scores were not significantly related to whether, or how long, CH had been designated. Species with CH designation were not doing better, on boilerplate, than those without. The effect size for CH designation remained small and insignificant when analyzed separately for each threat category (habitat loss versus other threats). There was no difference in the boilerplate status before and after CH designation (median difference = 0.0). This was also the example for the control group of species without CH designation (median departure = 0.0). These results were the same for both measures of recovery.

The proportion of reporting periods for which a species' status was known was positively related to peer-reviewed scientific information (Fig. 3b) and years listed , and information technology varied significantly amid taxonomic groups (p<0.0001 in all cases; R² = 0.127). For all species, the average proportion of reporting periods for which a species' status was known was 0.68; birds and fish had the highest proportions while plants had the lowest.

Word

Earlier studies accept reported statistically detectable associations between the recovery of species listed under the Endangered Species Act and the primary tools enabled under the act. In this study, we prove that: 1) those effects accept non been consistently detectable in earlier piece of work, and two) the outcome sizes are very small. The variation among listed species in ii measures of recovery – the number of recovery objectives achieved and the modify in species status over time – is, at all-time, only weakly related to the chief tools enabled under the Act. The nowadays study considers more species, more indicators of recovery, and more than variables that potentially influence recovery than any before written report, and nosotros still notice just weak effects, or none at all. Results in earlier studies were inconsistent (see Introduction above) probably because, when effect sizes are very small, small differences among data sets (and collinear variables) make parameters estimates highly unstable.

There are two possible interpretations of our data. One must conclude either that the tools provided past the ESA take had only modest impacts on the recovery of ESA-listed species over eighteen years (at best), or that information used to assess recovery are likewise imprecise to show whether the tools accept had a substantial effect or non. Either manner, strong evidence that the tools provided by ESA are working is lacking. To manage recovery of imperiled species, information technology is essential to assess the effectiveness of direction deportment, and to change them to amend outcomes.

The amass evidence (ours, plus earlier studies) regarding the beneficial effects of being listed under the ESA is mixed. The best amidst the weak predictors of recovery in our report is the number of years a species has been listed (Table 1) which implies some do good from protection from take and section seven consultations. Other studies have reported a significant correlation between number of years listed and species status [9], [27]. Taylor et al. [10] found a positive effect of years listed, after bookkeeping for CH designation and recovery plans. In contrast, Ferraro et al. [28] establish a negative event of being listed on species condition. They compared ESA-listed species to a control group of species from the Nature Serve information base and their report was express to 135 vertebrate species. They found that list was only beneficial when combined with high levels of funding. Inconsistent effects probably reflect minor absolute effect size and imprecise data.

The aggregate bear witness well-nigh the furnishings of recovery plans is also mixed. We observed a positive event on recovery objectives achieved, but not on species status trends (Table 1). Other studies take observed positive effects of recovery plans when those plans focused on single species and/or had a diversity of authors, but not for multi-species recovery plans [eight], [ten], [22]. Perhaps the reason we simply see an result of recovery plans in 2 of our four models is that we did not distinguish between single- and multi-species plans.

The effect of funding on ESA-listed species has been examined in many other studies, merely we are the first to examine both absolute funding and funding as a proportion of the estimated amount required for species recovery. Nosotros plant that recovery was more strongly related to proportional funding than to accented funding, but the effect was still modest (Table 1). Male and Bean [9] found that recovery was significantly related to annual FWS+NOAA funding. They exercise not quantify the strength of this human relationship; still, all of the variables included in their study explained only 13% of the variation in species' status, including variables such as "run a risk of extinction" and "recovery potential", then necessarily the consequence of funding was small. Kerkvliet and Langpap [8] found that an additional million dollars in funding decreased the likelihood of a species being listed as extinct by less than 1% and declining past i.3–1.7%, just that it did not increase the probability of being stable or increasing. Kerkvliet and Langpap's [8] study was limited to vertebrate species with no unknown status reports (i.e., 19% of all listed species), which mostly had high funding levels, so their results cannot be practical to listed species in general. Miller et al. [21] looked at funding as a proportion of the corporeality requested in the species recovery plan that had been received and plant that species with college funding were more likely to exist stable or increasing (although, again, they did not specify outcome size).

While the detectable effects of funding on recovery may be modest, the amount of data available on ESA-listed species relates more than strongly to funding, both in terms of peer-reviewed scientific publications and availability of assessments of recovery status. Mean yearly funding and numbers of publications are strongly correlated (Fig. 3a), and there is a positive relationship between the proportion of known status reports and mean yearly funding (Fig. 3b) and peer-reviewed information (Fig. 3c). This is consistent with the notion that a portion of species funding goes towards research which provides more information on species condition. Still, even this relationship accounted for but 12% of the variability in available reports.

The aggregate evidence regarding critical habitat suggests that there is no detectable result. Nosotros institute that species with CH designation are not doing better than those without it. We tested this both with a general linear model and past looking the departure in average status before and afterwards designation. The studies of Male and Edible bean [9] and Kerkvliet and Langpap [8] were also consistent with this conclusion. In contrast, Taylor et al. [10], who reported a positive effect of CH designation, looked at two time periods, 1990–1994 and 1997–2002, and tested whether or not species with CH in each menstruum were more than likely to be increasing and less likely to be decreasing than those without it. Only ii of their four tests were meaning. I explained less than 1% of the variation in condition, the other explaining less than x%. Nosotros conclude that the relationship between species status and CH is, at best, very weak.

Given that habitat loss is cited every bit the main threat to imperiled species in the U.S. [29] 1 would await CH designation to have a strong positive consequence on species condition. However, legal designation of CH does not necessarily mean that habitat is protected on the ground, since CH designation applies only to situations involving federal agencies [20]. Suckling and Taylor [17] provide a number of case studies where CH designation was used to provide effective habitat protection. However, for endangered species more often than not, CH designation that is limited to the deportment of federal agencies is apparently insufficient to promote recovery appreciably.

We suspect that the ESA tools we studied may be more constructive than our written report suggests, but that the species recovery data are grossly inadequate. Species population status data are published in biennial recovery reports to Congress every bit mandated by the Act. If species status data are bachelor at all, they are qualitative and are relative to a previous recovery report. In that location are no standards on how status decisions are made, nor are the reports peer reviewed in any way. Many of the condition assessments are based on the opinion of FWS staff [22]. Despite this, species status reports have been used in well-nigh of the previous assessments of the effectiveness of the ESA [9], [ten]. Due to these limitations we used a second mensurate of species recovery – the number of recovery objectives accomplished. But this measure too has astringent limitations. The recovery objectives outlined in the recovery reports have been criticized as beingness arbitrary and not based on scientific discipline [22], [30].

We take no independent verification of the quality of species condition and recovery objective information. The two recovery metrics that we studied are positively correlated (r = 0.49; run across besides [8], [31]), only for a given recovery objectives achieved score, there is a large corporeality of variation in species population status, especially for the lower scores (Fig. 4). This suggests that the FWS population condition scores are indeed very imprecise indicators of species' recovery condition [four]. Accurate, quantitative information on species status is necessary for assessing the ESA and subsequently improving and strengthening it.

Figure 4. Relationship betwixt population status and recovery objectives achieved.

Besprinkle plot showing the relationship between change in population status over fourth dimension and recovery objectives achieved for ESA listed species. Data comes from biennial FWS recovery reports to Congress. Line shows LOWESS smoothing functions with tension = 0.7. Due north = 1179.

https://doi.org/10.1371/journal.pone.0035730.g004

Another criticism of the ESA is that delays in listing at-risk species results in species not being listed until their situation is already critical [4], [32]. Greenwald et al. [32] found that the average time to listing a candidate species was 11 years. They notation that these delays brand recovery very difficult, and in some cases, incommunicable. Perhaps tools would be more than constructive if species were listed more than quickly.

Despite including more species and more than variables than previous studies, we find that species recovery is, at all-time, but weakly related to the principal tools enabled under the Act. We are non suggesting that the Act should be abandoned; there is no mode to know what would accept been the fate of listed species in the absence of protections offered by the Deed. Nosotros have no direct show to appraise whether the Human action per se is flawed, or the implementation of the Act is flawed (perhaps because of lack of funding), or the data available to assess the implementation are flawed. It is critically important to assess the effectiveness of tools used to promote species recovery; information technology is therefore also critically important to obtain population status data that are adequate to that task.

Supporting Information

Acknowledgments

We thank T. Male person and K. Bean for providing species funding and critical habitat data from 1989–2002. We also thank Marker Schwartz and anonymous reviewers for useful comments on this work.

Writer Contributions

Conceived and designed the experiments: KEG DJC. Analyzed the data: KEG DJC. Wrote the newspaper: KEG DJC.

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Source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0035730

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