Did a Shifting Ecological Baseline Mask the Predatory Effect of Striped Bass on Delta Smelt?

Striped Bass, Morone saxatilis, has been an established member of the San Francisco Estuary’s (estuary’s) aquatic community for nearly a century and a half. As a predator, it has the potential to shape community composition through top-down control of lower trophic species, including the endangered Delta Smelt, Hypomesus transpacificus. Invasive predators can be particularly disruptive to native communities because they present novel dangers to naïve populations, but, as a long-established member of the aquatic community, Striped Bass has not previously been considered to limit the Delta Smelt population. Here, we develop an argument that Striped Bass are important to controlling Delta Smelt. We support this argument by reviewing historical data which suggests that declines in Delta Smelt before the current-day monitoring program were driven by the invasion of Striped Bass into the estuary. We describe this phenomenon as the ‘phantom predator’ hypothesis in the context of an analog to the shifting baseline syndrome previously described for marine fisheries. A deeper understanding of how well studied (and rapidly changing) bottom-up drivers of the estuary food web interact with poorly understood (but also rapidly changing) controls at the top of the food web could prove very important to the conservation of other declining native fishes and possible future attempts to re-introduce captive-reared Delta Smelt to the estuary

An easy subexponential bound for online chain partitioning

Bosek and Krawczyk exhibited an online algorithm for partitioning an online poset of width $w$ into $w^{14\lg w}$ chains. We improve this to $w^{6.5 \lg w + 7}$ with a simpler and shorter proof by combining the work of Bosek & Krawczyk with work of Kierstead & Smith on First-Fit chain partitioning of ladder-free posets. We also provide examples illustrating the limits of our approach.Comment: 23 pages, 11 figure

False discovery rate regression: an application to neural synchrony detection in primary visual cortex

Many approaches for multiple testing begin with the assumption that all tests in a given study should be combined into a global false-discovery-rate analysis. But this may be inappropriate for many of today's large-scale screening problems, where auxiliary information about each test is often available, and where a combined analysis can lead to poorly calibrated error rates within different subsets of the experiment. To address this issue, we introduce an approach called false-discovery-rate regression that directly uses this auxiliary information to inform the outcome of each test. The method can be motivated by a two-groups model in which covariates are allowed to influence the local false discovery rate, or equivalently, the posterior probability that a given observation is a signal. This poses many subtle issues at the interface between inference and computation, and we investigate several variations of the overall approach. Simulation evidence suggests that: (1) when covariate effects are present, FDR regression improves power for a fixed false-discovery rate; and (2) when covariate effects are absent, the method is robust, in the sense that it does not lead to inflated error rates. We apply the method to neural recordings from primary visual cortex. The goal is to detect pairs of neurons that exhibit fine-time-scale interactions, in the sense that they fire together more often than expected due to chance. Our method detects roughly 50% more synchronous pairs versus a standard FDR-controlling analysis. The companion R package FDRreg implements all methods described in the paper

Field testing a novel high residence positioning system for monitoring the fine‐scale movements of aquatic organisms

1. Acoustic telemetry is an important tool for studying the behaviour of aquatic organisms in the wild. 2. VEMCO high residence (HR) tags and receivers are a recent introduction in the field of acoustic telemetry and can be paired with existing algorithms (e.g. VEMCO positioning system [VPS]) to obtain high‐resolution two‐dimensional positioning data. 3. Here, we present results of the first documented field test of a VPS composed of HR receivers (hereafter, HR‐VPS). We performed a series of stationary and moving trials with HR tags (mean HR transmission period = 1.5 s) to evaluate the precision, accuracy and temporal capabilities of this positioning technology. In addition, we present a sample of data obtained for five European perch Perca fluviatilis implanted with HR tags (mean HR transmission period = 4 s) to illustrate how this technology can estimate the fine‐scale behaviour of aquatic animals. 4. Accuracy and precision estimates (median [5th–95th percentile]) of HR‐VPS positions for all stationary trials were 5.6 m (4.2–10.8 m) and 0.1 m (0.02–0.07 m), respectively, and depended on the location of tags within the receiver array. In moving tests, tracks generated by HR‐VPS closely mimicked those produced by a handheld GPS held over the tag, but these differed in location by an average of ≈9 m. 5. We found that estimates of animal speed and distance travelled for perch declined when positional data for acoustically tagged perch were thinned to mimic longer transmission periods. These data also revealed a trade‐off between capturing real nonlinear animal movements and the inclusion of positioning error. 6. Our results suggested that HR‐VPS can provide more representative estimates of movement metrics and offer an advancement for studying fine‐scale movements of aquatic organisms, but high‐precision survey techniques may be needed to test these systems