Evidence of hypoxic foraging forays by yellow perch ( Perca flavescens ) and potential consequences for prey consumption

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91146/1/FWB_2753_sm_fS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/91146/2/j.1365-2427.2012.02753.x.pd

Establishment of a taxonomic and molecular reference collection to support the identification of species regulated by the Western Australian Prevention List for Introduced Marine Pests

Introduced Marine Pests (IMP, = non-indigenous marine species) prevention, early detection and risk-based management strategies have become the priority for biosecurity operations worldwide, in recognition of the fact that, once established, the effective management of marine pests can rapidly become cost prohibitive or impractical. In Western Australia (WA), biosecurity management is guided by the “Western Australian Prevention List for Introduced Marine Pests” which is a policy tool that details species or genera as being of high risk to the region. This list forms the basis of management efforts to prevent introduction of these species, monitoring efforts to detect them at an early stage, and rapid response should they be detected. It is therefore essential that the species listed can be rapid and confidently identified and discriminated from native species by a range of government and industry stakeholders. Recognising that identification of these species requires very specialist expertise which may be in short supply and not readily accessible in a regulatory environment, and the fact that much publicly available data is not verifiable or suitable for regulatory enforcement, the WA government commissioned the current project to collate a reference collection of these marine pest specimens. In this work, we thus established collaboration with researchers worldwide in order to source representative specimens of the species listed. Our main objective was to build a reference collection of taxonomically vouchered specimens and subsequently to generate species-specific DNA barcodes suited to supporting their future identification. To date, we were able to obtain specimens of 75 species (representative of all but four of the pests listed) which have been identified by experts and placed with the WA Government Department of Fisheries and, where possible, in accessible museums and institutions in Australasia. The reference collection supports the fast and reliable taxonomic and molecular identification of marine pests in WA and constitutes a valuable resource for training of stakeholders with interest in IMP recognition in Australia. The reference collection is also useful in supporting the development of a variety of DNA-based detection strategies such as real-time PCR and metabarcoding of complex environmental samples (e.g. biofouling communities). ThePrevention List is under regular review to ensure its continued relevance and that it remains evidence and risk-based. Similarly, its associated reference collection also remains to some extent a work in progress. In recognition of this fact, this report seeks to provide details of this continually evolving information repository publicly available to the biosecurity management community worldwid

First Finding of the Amphipod \u3ci\u3eEchinogammarus ischnus\u3c/i\u3e and the Mussel \u3ci\u3eDreissena bugensis\u3c/i\u3e in Lake Michigan

The first finding of the amphipod Echinogammarus ischnus and the mussel Dreissena bugensis in Lake Michigan is documented. These two species are widespread and abundant in the lower lakes, but had not yet been reported from Lake Michigan. E. ischnus is generally considered a warmwater form that is typically associated with hard substrates and Dreissena clusters in the nearshore zone. Along the eastern shoreline of Lake Michigan, this species was present at rocky, breakwall habitats along the entire north-south axis of the lake. Although not abundant, this species was also found at soft-bottomed sites as deep as 94 m in the southern basin. The finding of this species in deep offshore waters apparently extends the known habitat range for this species in the Great Lakes, but it is found in deep water areas within its native range (Caspian Sea). D. bugensis was not abundant, but was present in both the southern and northern portions of the lake. Individuals of up to 36 mm in length were collected, indicating that it had probably been present in the lake for 2 or more years. Also presented are depth-defined densities of D. polymorpha at 37 sites in the Straits of Mackinac in 1997, and densities at up to 55 sites in the southern basin in 1992/93 and 1998/99. Mean densities decreased with increased water depth in both regions. Maximum mean density in the Straits in 1997 was 13,700/m2 (≤ 10 m), and maximum density in the southern basin in 1999 was 2,100/m2 (≤ 30 m). Mean densities at the ≤ 30-m interval in the southern basin remained relatively unchanged between 1993 and 1999, but increased from 25/m2 to 1,100/m2 at the 31 to 50 m interval over the same time period. D. polymorpha was rare at sites \u3e 50 m. The presence of E. ischnus and the expected population expansion of D. bugensis will likely contribute to further foodweb changes in the lake

Lake Michigan 110M Zooplankton Time Series 1994-2012

Time series data from zooplankton survey of Lake Michigan collected near Muskegon, MI, via vertical tows by NOAA GLERL researchers. Includes collection date and Julian day. Biomass density data for Daphnia mendotae (D.mendotae), Bythotrephes longimanus (Bythotrephes), and Limnocalanus macrurus (male: LimncalanusM and female: LimncalanusF). "Prior_to_1st_Daphnia_obs" indicates if the observation occurred prior to the first positive observation of D. mendotae each year

R markdown file to generate Appendix S1

R markdown file used to generate Appendix S1 (included in manuscript supplementary materials), which describes model code and details of analysis used in manuscript

Data from: Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the mechanism underlying the B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore highlights the utility of SSMs to enhance inference for species interactions from time series data. In particular, our findings provide evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change

Data from: Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the mechanism underlying the B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore highlights the utility of SSMs to enhance inference for species interactions from time series data. In particular, our findings provide evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change