Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance.

Understanding the movement patterns of an invasive species can be a powerful tool in designing effective management and control strategies. Here, we used a Bayesian multistate model to investigate the movement of two invasive carp species, silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis), using acoustic telemetry. The invaded portions of the Illinois and Des Plaines Rivers, USA, are a high priority management zone in the broader efforts to combat the spread of invasive carps from reaching the Laurentian Great Lakes. Our main objective was to characterize the rates of upstream and downstream movements by carps between river pools that are maintained by navigation lock and dam structures. However, we also aimed to evaluate the efficacy of the available telemetry infrastructure to monitor carp movements through this system. We found that, on a monthly basis, most individuals of both species remained within their current river pools: averaging 76.2% of silver carp and 75.5% of bighead carp. Conversely, a smaller proportion of silver carp, averaging 14.2%, and bighead carp, averaging 13.9%, moved to downstream river pools. Movements towards upstream pools were the least likely for both species, with silver carp at an average of 6.7% and bighead carp at 7.9%. The highest probabilities for upstream movements were for fish originating from the three most downstream river pools, where most of the population recruitment occurs. However, our evaluation of the telemetry array's effectiveness indicated low probability to detect fish in this portion of the river. We provide insights to enhance the placement and use of these monitoring tools, aiming to deepen our comprehension of these species' movement patterns in the system.

Comparing maximum likelihood and Bayesian methods for fitting hidden Markov models to multi-state capture-recapture data of invasive carp in the Illinois River.

BACKGROUND: Hidden Markov Models (HMMs) are often used to model multi-state capture-recapture data in ecology. However, a variety of HMM modeling approaches and software exist, including both maximum likelihood and Bayesian methods. The diversity of these methods obscures the underlying HMM and can exaggerate minor differences in parameterization. METHODS: In this paper, we describe a general framework for modelling multi-state capture-recapture data via HMMs using both maximum likelihood and Bayesian methods. We then apply an HMM to invasive silver carp telemetry data from the Illinois River and compare the results estimated by both methods. RESULTS: Our analysis demonstrates disadvantages of relying on a single approach and highlights insights obtained from implementing both methods together. While both methods often struggled to converge, our results show biologically informative priors for Bayesian methods and initial values for maximum likelihood methods can guide convergence toward realistic solutions. Incorporating prior knowledge of the system can successfully constrain estimation to biologically realistic movement and detection probabilities when dealing with sparse data. CONCLUSIONS: Biologically unrealistic estimates may be a sign of poor model convergence. In contrast, consistent convergence behavior across approaches can increase the credibility of a model. Estimates of movement probabilities can strongly influence the predicted population dynamics of a system. Therefore, thoroughly assessing results from HMMs is important when evaluating potential management strategies, particularly for invasive species.

Nonlinear relationship between Silver Carp density and their eDNA concentration in a large river.

Although environmental DNA (eDNA) is increasingly being used to survey for the presence of rare and/or invasive fishes in aquatic systems, the utility of this technique has been limited by a poor understanding of whether and how eDNA concentrations relate to fish density, especially in rivers. We conducted a field study to systematically test whether the eDNA released by a model invasive fish, Silver Carp (Hypophthalmichthys molitrix), was related to the density of this species in a large river. We quantified fish density throughout the 460 km long Illinois River using hydroacoustic surveys at 23 sites while concurrently collecting 192 surface water samples for eDNA analysis. We found that Silver Carp numerical density and biomass density were positively and non-linearly related to eDNA concentration and detection rate. Both eDNA concentration (copy number) and detection rate increased rapidly as Silver Carp density increased but plateaued at moderate densities. These relationships could prove useful for estimating Silver Carp relative abundance in newly invaded locations where population numbers are low to moderate. Future studies should explore the causes of this nonlinear relationship as it would ultimately benefit aquatic species monitoring and management programs.

Detecting the movement and spawning activity of bigheaded carps with environmental DNA.

Bigheaded carps are invasive fishes threatening to invade the Great Lakes basin and establish spawning populations, and have been monitored using environmental DNA (eDNA). Not only does eDNA hold potential for detecting the presence of species, but may also allow for quantitative comparisons like relative abundance of species across time or space. We examined the relationships among bigheaded carp movement, hydrography, spawning and eDNA on the Wabash River, IN, USA. We found positive relationships between eDNA and movement and eDNA and hydrography. We did not find a relationship between eDNA and spawning activity in the form of drifting eggs. Our first finding demonstrates how eDNA may be used to monitor species abundance, whereas our second finding illustrates the need for additional research into eDNA methodologies. Current applications of eDNA are widespread, but the relatively new technology requires further refinement.