Colonization dynamics of the invasive predatory cladoceran, Bythotrephes longimanus, inferred from sediment records

Abstract

Despite the central role of colonization to invasion biology, little is known about the early dynamics of founder populations because this time period is often unobserved and short-lived. This study documents with high resolution the early population ecology of an invading freshwater zooplankton, Bythotrephes longimanus (Cladocera : Cercopagidae), by measuring accumulation rates of its caudal spine in sediments. Using dated ( 210 Pb and 137 Cs) sediment cores from four spatially distinct sites in Island Lake Reservoir (Minnesota, USA), we describe its first presence, early distribution, growth trajectory, and early impacts on prey. The sediment record shows that B. longimanus first appeared and was widely distributed in the lake in 1982 (6 2 yr, standard deviation), 8 yr before its first detection in the water, making it one of the earliest documented invasions in North America and suggesting that ecosystems may serve as dispersal hubs for years prior to detection. Logistic growth models describing spine accumulation rates show that B. longimanus required about two decades to achieve an annual equilibrium (K). Prolonged buildup to K may owe to several factors, including accumulation of a sufficiently large bank of resting eggs, the obligate overwintering life stage. Early exponential growth was incongruent with the presence of a lag phase. Post invasion, Daphnia mendotae became proportionally the most abundant daphniid in the lake, but the timing of the switch in prey species composition coincided more with the proliferation of B. longimanus density and its attainment of K than with its arrival to the lake.

Conventional versus real‐time quantitative PCR for rare species detection

“…Imperfect detection through either false positive or false negative results impedes these efforts, particularly with respect to rapid response to NIS incursions (Zhan & MacIsaac, 2015). However, detecting these species is challenging either because of their small population size and/or geographicallyconstrained distribution (Branstrator, Beranek, Brown, Hembre, & Engstrom, 2017;Robertson et al, 2017;Simberloff et al, 2013;vander Zanden, 2010).…”

Detecting species at low densities: a new theoretical framework and an empirical test on an invasive zooplankton

“… and Branstrator et al. ) could circumvent the challenge of detecting a highly seasonal nonnative species.…”

“…, Branstrator et al. ). In the case of the well‐monitored Lake Mendota, Wisconsin, USA, Bythotrephes persisted and avoided detection for perhaps a decade or more prior to erupting to high densities (>150 individuals/m 3 ) in fall of 2009 that drove a large decline in lake water clarity (Walsh et al.…”

“…Reports of Bythotrephes adverse effects have been accumulating since its detection in the Laurentian Great Lakes , Kerfoot et al 2016, Walsh et al 2016a) but its detection has proven challenging, often occurring well after Bythotrephes establishment and population growth ❖ www.esajournals.org (Walsh et al 2016b, Branstrator et al 2017). In the case of the well-monitored Lake Mendota, Wisconsin, USA, Bythotrephes persisted and avoided detection for perhaps a decade or more prior to erupting to high densities (>150 individuals/m 3 ) in fall of 2009 that drove a large decline in lake water clarity (Walsh et al 2016a, b).…”

“…Branstrator and his colleagues have shown this to be the case in Island Lake, Minnesota, USA. Sediment cores have revealed that Island Lake could have been the earliest invaded lake inland of the Laurentian Great Lakes in North America, with Bythotrephes establishing as early as 1982 (the first year of its detection in the Laurentian Great Lakes) prior to its detection in 1990 (Branstrator et al 2017). Here, we suggest that Bythotrephes may be more likely to persist undetected due to the necessity to use specialized equipment for detection (e.g., a relatively large zooplankton net, which is not easily available to citizens) and highly seasonal population dynamics.…”