Robustness of potential biological removal to monitoring, environmental, and management uncertainties

Abstract

The potential biological removal (PBR) formula used to determine a reference point for human-caused mortality of marine mammals in the United States has been shown to be robust to several sources of uncertainty. This study investigates the consequences of the quality of monitoring on PBR performance. It also explores stochastic and demographic uncertainty, catastrophic events, sublethal effects of interactions with fishing gear, and the situation of a marine mammal population subject to bycatch in two fisheries, only one of which is managed. Results are presented for two pinniped and two cetacean life histories. Bias in abundance estimates and whether there is a linear relationship between abundance estimates and true abundance most influence conservation performance. Catastrophic events and trends in natural mortality have larger effects than environmental stochasticity. Managing only one of two fisheries with significant bycatch leads, as expected, to a lower probability of achieving conservation management goals, and better outcomes would be achieved if bycatch in all fisheries were managed. The results are qualitatively the same for the four life histories, but estimates of the probability of population recovery differ.

Precautionary Principle or Evidence-Based Conservation? Assessing the Information Content of Threat Data for the Yangtze Finless Porpoise

“…Predicted sustainable offtake rates differ between our population models by an order of ∼10 due to differences in model structure and aims: whereas logistic modeling only considers demographic and ecological parameters (e.g., point estimates of N) and does not explicitly consider uncertainty, PBR uses N min and incorporates a precautionary recovery factor to identify whether sustainable removal thresholds have been exceeded in post-depletion populations (Robards et al, 2009). Conservation target-setting using the PBR approach can be affected by some sources of data uncertainty (e.g., bias in abundance estimates, catastrophic events, trends in natural mortality; Punt et al, 2020), but there is no evidence that these constitute significant concerns in this system. However, as PBR is a conservative management technique, higher removal rates might still be sustainable in the longer-term than predicted in our model.…”

Evaluating Strategies for Managing Anthropogenic Mortality on Marine Mammals: An R Implementation With the Package RLA

“…It is also possible to use the age-disaggregated simulator pellatomlinson_rla() with the PBR control rule with function pbr_nouveau() as in e.g. Brandon et al (2017) or Punt et al (2020a). This allows conditioning on species-or population-specific survival and fecundity data in the population dynamics model for increased realism, but relying on minimal data (abundance estimates only) to design a precautionary MSE.…”

“…Wade (1998) determined in a MSE designed for the US MMPA the default value F r = 0.5 for populations that are depleted, threatened, or of unknown status. The F r value can be increased up to 1.0 when populations are well studied and biases in the estimation of N min and other parameters are thought to be negligible (Punt et al, 2020a). The different values used in Punt, 2016), implemented in the function pellatomlinson_pbr().…”

“…Implicit in this context is the acceptance of the MMPA CO: "a population will remain at, or recover to, its maximum net productivity level MNPL (typically 50% of the populations carrying capacity), with 95% probability, within a 100-year period" (Wade, 1998). PBR has been extensively tested (Wade, 1998;Punt et al, 2020a) and its robustness is well established. Yet, MSE is entirely dependent on the CO: if the latter change, a new MSE needs to be carried out.…”

An increase in detection rates of the critically endangered Baltic Proper harbor porpoise in Swedish waters in recent years

“…The annual rate of increase for the Morro Bay stock of harbor porpoises has been estimated to 9.6% (95% credible interval [CI] 6.2–13.0%) for the years 1991–2012, after bycatch was mostly eliminated (Forney, Moore, Barlow, Carretta, & Benson, 2020). Additionally, management using the PBR method assumes a possible annual increase rate of 4% across all cetacean species (Punt et al, 2020; Wade, 1998). In the absence of any additional anthropogenic stressors above the current baseline, the Baltic Proper population of harbor porpoises has been estimated to be capable of an annual growth rate of 2.3% ( SD 6.4%) (Cervin, Harkonen, & Harding, 2020); similar to the rate observed in this study.…”