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The optimal number of surveys when detectability varies.

ABSTRACT: The survey of plant and animal populations is central to undertaking field ecology. However, detection is imperfect, so the absence of a species cannot be determined with certainty. Methods developed to account for imperfect detectability during surveys do not yet account for stochastic variation in detectability over time or space. When each survey entails a fixed cost that is not spent searching (e.g., time required to travel to the site), stochastic detection rates result in a trade-off between the number of surveys and the length of each survey when surveying a single site. We present a model that addresses this trade-off and use it to determine the number of surveys that: 1) maximizes the expected probability of detection over the entire survey period; and 2) is most likely to achieve a minimally-acceptable probability of detection. We illustrate the applicability of our approach using three practical examples (minimum survey effort protocols, number of frog surveys per season, and number of quadrats per site to detect a plant species) and test our model's predictions using data from experimental plant surveys. We find that when maximizing the expected probability of detection, the optimal survey design is most sensitive to the coefficient of variation in the rate of detection and the ratio of the search budget to the travel cost. When maximizing the likelihood of achieving a particular probability of detection, the optimal survey design is most sensitive to the required probability of detection, the expected number of detections if the budget were spent only on searching, and the expected number of detections that are missed due to travel costs. We find that accounting for stochasticity in detection rates is likely to be particularly important for designing surveys when detection rates are low. Our model provides a framework to do this.

SUBMITTER: Moore AL

PROVIDER: S-EPMC4272285 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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The optimal number of surveys when detectability varies.

Moore Alana L AL McCarthy Michael A MA Parris Kirsten M KM Moore Joslin L JL

PloS one 20141219 12

The survey of plant and animal populations is central to undertaking field ecology. However, detection is imperfect, so the absence of a species cannot be determined with certainty. Methods developed to account for imperfect detectability during surveys do not yet account for stochastic variation in detectability over time or space. When each survey entails a fixed cost that is not spent searching (e.g., time required to travel to the site), stochastic detection rates result in a trade-off betwe ...[more]

PMID: 25526514

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Project description:Invasive species are a cause for concern in natural and economic systems and require both monitoring and management. There is a trade-off between the amount of resources spent on surveying for the species and conducting early management of occupied sites, and the resources that are ultimately spent in delayed management at sites where the species was present but undetected. Previous work addressed this optimal resource allocation problem assuming that surveys continue despite detection until the initially planned survey effort is consumed. However, a more realistic scenario is often that surveys stop after detection (i.e., follow a "removal" sampling design) and then management begins. Such an approach will indicate a different optimal survey design and can be expected to be more efficient. We analyze this case and compare the expected efficiency of invasive species management programs under both survey methods. We also evaluate the impact of mis-specifying the type of sampling approach during the program design phase. We derive analytical expressions that optimize resource allocation between monitoring and management in surveillance programs when surveys stop after detection. We do this under a scenario of unconstrained resources and scenarios where survey budget is constrained. The efficiency of surveillance programs is greater if a "removal survey" design is used, with larger gains obtained when savings from early detection are high, occupancy is high, and survey costs are not much lower than early management costs at a site. Designing a surveillance program disregarding that surveys stop after detection can result in an efficiency loss. Our results help guide the design of future surveillance programs for invasive species. Addressing program design within a decision-theoretic framework can lead to a better use of available resources. We show how species prevalence, its detectability, and the benefits derived from early detection can be considered.

Project description:The persistence of genetic variation in master regulators of gene expression, such as quorum-sensing systems, is hard to explain. Here, we investigated two alternative hypotheses for the prevalence of polymorphic quorum sensing in Gram-positive bacteria, i.e., the use of different signal/receptor pairs ('pherotypes') to regulate the same functions. First, social interactions between pherotypes or 'facultative cheating' may favor rare variants that exploit the signals of others. Second, different pherotypes may increase fitness in different environments. We evaluated these hypotheses in the invertebrate pathogen Bacillus thuringiensis, using three pherotypes expressed in a common genetic background. Facultative cheating could occur in well-mixed host homogenates provided there was minimal cross talk between competing pherotypes. However, facultative cheating did not occur when spatial structure was increased in static cultures or in naturalistic oral infections, where common pherotypes had higher fitness. There was clear support for environment-dependent fitness; pherotypes varied in responsiveness to signals and in mean competitive fitness. Notably, competitive fitness varied with group size. In contrast to typical social evolution models of quorum sensing which predict higher response to signal at larger group size, the pherotype with highest responsiveness to signals performed best in smaller hosts where infections have a lower pathogen group size. In this system, low signal abundance appears to limit fitness in hosts, while the optimal level of response to signals varies in different host environments.IMPORTANCE Quorum sensing describes the ability of microbes to alter gene regulation according to their local population size. Some successful theory suggests that this is a form of cooperation, namely, investment in shared products is only worthwhile if there are sufficient bacteria making the same product. This theory can explain the genetic diversity in these signaling systems in Gram-positive bacteria, such as Bacillus and Staphylococcus sp. The possible advantages gained by rare genotypes (which can exploit the products of their more common neighbors) could explain why different genotypes can coexist. We show that while these social interactions can occur in simple laboratory experiments, they do not occur in naturalistic infections using an invertebrate pathogen, Bacillus thuringiensis Instead, our results suggest that different genotypes are adapted to differently sized hosts. Overall, social models are not easily applied to this system, implying that a different explanation for this form of quorum sensing is required.

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The optimal number of surveys when detectability varies.

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The optimal number of surveys when detectability varies.

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