In its evolving effort to meet Congress’s directive that determinations under the federal Endangered Species Act should be informed by the “best available scientific and commercial data” the U.S. Fish and Wildlife Service uses Species Status Assessments “to deliver foundational science” to support its decisions. While this process does not typically garner much attention beyond that of the agency, the recent proposal to list longfin smelt as endangered has highlighted the SSA’s importance and brought to light some assessment elements that can be improved.
By way of background, the Service intends the Assessments to provide “focused, repeatable, and rigorous scientific assessment” that results in “improved and more transparent and defensible decision making, and clearer and more concise documents.” The Service overhauled its guidance on the preparation of Species Status Assessments (SSAs) in 2015 and 2016, issuing a Species Status Assessment Framework (Framework). The Framework instructs SSA “teams” to analyze information in three iterative assessment “stages” – species’ needs, current species’ condition, and future species’ condition – to produce “a scientifically rigorous characterization of species status that focuses on the likelihood that the species will sustain populations within its ecological settings along with key uncertainties in that characterization.”
The Service late last year released The Species Status Assessment for the San Francisco Bay-Delta Distinct Population Segment of the Longfin Smelt (LFS SSA). At the same time, the Service proposed to list the longfin smelt as endangered. While the LFS SSA follows the Framework’s guidance in certain respects, it does not do so in others. Deficiencies in the LFS SSA, some resulting from failure to adhere to the Framework and others exposing gaps in the Framework, have highlighted the need for the Service to update the Framework.
Based on close reading of the Longfin Smelt Species Status Assessment, we have identified four ways in which the Service should update its Framework. The Service needs to:
· Make explicit the expectation that agency staff will include in each SSA a conceptual ecological model(s) developed consistent with best practices in conservation planning. Models should describe environmental drivers acting on the target species and its habitat, ecological factors that affect the species’ population size and distribution, and potential management actions that can be expected to contribute to its recovery.
· Instruct agency staff to identify a range of alternative probable future scenarios that reflects the reasonably foreseeable range of environmental conditions and conservation efforts that are anticipated to influence the target species’ population dynamics and the extent and condition of its habitat
· Recognize and elaborate on the range of available tools and methods to model and assess the current condition and predict future condition of the targeted species’ population(s)
· Require an independent scientific (peer) review of each SSA, incorporate best practices with respect to that review, and in the final SSA respond to all expert input and feedback presented in the review
In many respects, the Framework at the time of its updating reflected best practices in conservation biology. In the Framework, the Service explains that an SSA “is in essence a biological risk assessment to aid decision makers who must use the best available scientific information to make policy-guided decisions.” The Service’s commitment to the concept of a biological risk assessment and to identifying and disclosing key uncertainties in the assessment represented substantive progress toward use of the best available scientific information in agency decision-making.
The Service organized the LFS SSA consistent with the broad guidance in the Framework to cover the species’ needs, current condition, and future condition. The Service also drew on the principles of resiliency, representation, and redundancy to describe the status and future trajectory of longfin smelt numbers. That said, in important respects, the LFS SSA does not track the Framework. Other shortcomings of the final LFS SSA provide grounds for the Service to re-visit and update the Framework in ways that can be expected to improve the quality of future SSAs.
Conceptual Ecological Models
The Framework highlights the value of a conceptual ecological model as part of an SSA. In fact, the Service includes generic conceptual models in the Framework and explains their value, for example, stating “[e]xplicit logic chains developed with the help of conceptual or quantitative modeling will aid in identifying gaps in knowledge and will support an explicit assessment of how various sources of uncertainty might affect a decision through sensitivity analyses,” and “[m]odels can be useful for projecting the future status of the species.”
In a subsequent article published in the Service’s peer-reviewed journal on fish and wildlife, Department of the Interior staff involved in the development of the Framework state “conceptual models (expressed as influence diagrams) are useful for illustrating life history or graphically relating environmental factors to a species/condition.” Perhaps because the Framework does not expressly endorse the inclusion of a conceptual ecological model in every SSA, the Service failed to include a longfin smelt model in the body of the LFS SSA.
By way of comparison, a contemporaneous SSA for the grizzly bear in the lower 48 states makes excellent use of conceptual models, including a conceptual model of causes and effects of environmental factors that may influence the species’ resiliency. Considering the failure of Service staff to consistently incorporate conceptual ecological models into SSAs, it would be prudent for the Service to update the Framework to clarify not only that conceptual models are useful as elements in the SSA process, but that they should be included in each SSA.
Alternative Probable Future Scenarios
In the Framework, the Service emphasizes the need to describe the predicted future condition of the species that is the subject of an SSA. Such predictions are accompanied by uncertainties, often substantial uncertainties, even in circumstances where robust data exist regarding historical and current population size and distribution, habitat and essential resource conditions, and limiting environmental factors that act on the target species.
The Service instructs its staff preparing SSAs to forecast the target species’ response “to probable future scenarios of environmental conditions and conservation efforts.” In other words, the Framework directs Service staff to assess reasonably foreseeable ranges of environmental conditions and conservation efforts, thereby describing alternative probable future species outcomes. To put a finer point on it, the Framework states an SSA “should include a range of plausible and likely future scenarios for anthropogenic and natural factors that will result in a range in the species response.”
While the grizzly bear SSA, mentioned above, includes a range of alternative future scenarios, including a range of possible conservation efforts to improve future conditions, the LFS SSA does not assess the future effects of conservation efforts on longfin smelt at all. For this reason, an updated Framework should instruct Service staff to identify a range of alternative probable future scenarios that reflects the reasonably foreseeable range of environmental conditions and conservation efforts anticipated to influence the species’ population dynamics.
Current and Future Conditions
One aspect of the SSA that is inherently challenging is the characterization of current and projected future abundance and distribution of the target species population or populations. This is the case because for many species available demographic data are limited.
For longfin smelt even a rough estimate of the census population size is lacking. In the longfin smelt SSA, the Service erred by using abundance-index values, drawn from available pelagic fish survey data rather from targeted monitoring, as surrogates for census population size estimates in conducting a population viability analysis.
The error was twofold. The survey data relied upon by the SSA team do not reflect species population dynamics and the team failed to report the overwhelming uncertainty that accompanied the analysis when reporting its results. While population viability analyses can be useful tools for projecting species persistence over time, absent reliable demographic data they generate estimates of future persistence times that are illusory. Where sufficient data are lacking, the Service is obliged to use other methods to characterize future conditions. This is explained plainly in the Framework:
The metrics for future species’ condition are related to abundance, distribution, and diversity (geographic and genetic), which are core autecological parameters (meaning they measure the relationships between an individual species and its environment). The numerical resolution and spatial and temporal scale of the metrics will depend on data availability and the information needed by the decision maker. Judgment will be required by the assessment team as to what resolution can be supported reliably.
The Service organized the LFS SSA consistent with the broad guidance in the Framework to cover the species’ needs, current condition, and future condition. The Service also drew on the principles of resiliency, representation, and redundancy to describe the status and future trajectory of longfin smelt numbers. That said, in important respects, the LFS SSA does not track the Framework. Other shortcomings of the final LFS SSA provide grounds for the Service to re-visit and update the Framework in ways that can be expected to improve the quality of future SSAs.
Independent Scientific Peer Review
The SSA Framework does not specify that SSAs should be subject to peer review or set out peer-review procedures that should be utilized to maximize the value of such reviews. The Service commendably veered from the Framework to undertake peer review of the LFS SSA. Unfortunately, the Framework provides no guidance on best review practices and the Service appears to have failed to engage such practices with the longfin smelt assessment – see a nine-step protocol for independent scientific reviews under the ESA.
For example, the Service did not disclose the identity of the reviewers. Furthermore, it appears the agency staff involved in preparation of the LFS SSA were also involved in the selection of reviewers.
Best practice is for a third party neutral to administer the review, including development of a task statement and a process for selecting reviewers. It is also essential for the Service to ensure that the reviewers have the time and resources necessary to complete the review and that the agency considered and explicitly respond to substantive comments received in the review. Incorporation of these peer review best practices into the Framework could be expected to improve the quality and reliability of future SSAs.
Conclusion
The Species Status Assessment Framework skillfully administrated has the potential to assist the Service in meeting its obligations in implementing the federal Endangered Species Act and to improve the quality and uniformity of agency decision-making in doing so. To do so, the Framework must be updated to address scientific advances and conform to prevailing best conservation practices. As guidance, it can and is intended to be updated as necessary. Given the deficiencies identified, the time is ripe to update the SSA Framework.
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