Inferring the absence of an incipient population during a rapid response for an invasive species

Successful eradication of invasives is facilitated by early detection and prompt onset of control. However, realizing or verifying that a colonization has occurred is difficult for cryptic species especially at low population densities. Responding to the capture or unconfirmed sighting of a cryptic invasive species, and the associated effort to determine if it indicates an incipient (small, localized) population or merely a lone colonizer, is costly and cannot continue indefinitely. However, insufficient detection effort risks erroneously concluding the species is not present, allowing the population to increase in size and expand its range. Evidence for an incipient population requires detection of ≥1 individual; its absence, on the other hand, must be inferred probabilistically. We use an actual rapid response incident and species-specific detection estimates tied to a known density to calculate the amount of effort (with non-sequential detections) necessary to assert, with a pre-defined confidence, that invasive brown treesnakes are absent from the search area under a wide range of hypothetical population densities. We illustrate that the amount of effort necessary to declare that a species is absent is substantial and increases with decreased individual detection probability, decreased density, and increased level of desired confidence about its absence. Such survey investment would be justified where the cost savings due to early detection are large. Our Poisson-based model application will allow managers to make informed decisions about how long to continue detection efforts, should no additional detections occur, and suggests that effort to do so is significantly higher than previously thought. While our model application informs how long to search to infer absence of an incipient population of brown treesnakes, the approach is sufficiently general to apply to other invasive species if density-dependent detection estimates are known or reliable surrogate estimates are available.

入侵物种的成功根除，有赖于早期发现与及时启动防控措施。然而，对于隐蔽物种（cryptic species）而言，尤其是当其种群密度极低时，人们往往难以察觉或证实其已完成定殖。针对捕获或未确认目击到的隐蔽入侵物种开展响应，并投入相关资源以判断其是否代表初始种群（incipient population，小型、局域性种群），抑或仅为单个扩散个体，此类工作成本高昂且无法无限持续。然而，若监测排查投入不足，则可能错误判定该物种并未存在，进而使其种群得以扩大规模、扩散分布范围。证实存在初始种群需要至少检测到1个个体；反之，若未检测到个体，则需通过概率方法推断该物种并不存在。本研究依托一起真实的快速响应事件，以及与已知种群密度挂钩的物种专属监测估算模型，计算出在一系列假想种群密度下，若要以预设置信水平判定某一搜索区域内无入侵性棕树蛇（brown treesnakes）存在，所需投入的排查工作量（采用非连续监测模式）。研究表明，判定某物种不存在所需的排查工作量十分可观，且随个体检测概率降低、种群密度下降以及对物种不存在的置信要求提升而增加。若早期发现防控可带来可观的成本节约，此类监测投入便具备合理性。本研究应用基于泊松分布的模型（Poisson-based model），可为管理人员在未检测到额外个体时，如何确定继续开展监测的时长提供科学决策依据，同时表明此类监测工作量远高于此前的认知水平。尽管本模型的应用场景聚焦于推断棕树蛇初始种群不存在所需的排查时长，但其方法具备足够的普适性：若已知依赖种群密度的监测估算数据，或可获取可靠的替代估算值，即可将其推广至其他入侵物种的防控监测中。