Considerations for management strategy evaluation for small pelagic fishes

Management strategy evaluation (MSE) is the state-of-the-art approach for testing and comparing management strategies in a way that accounts for multiple sources of uncertainty (e.g. monitoring, estimation, and implementation). Management strategy evaluation can help identify management strategies that are robust to uncertainty about the life history of the target species and its relationship to other species in the food web. Small pelagic fish (e.g. anchovy, herring and sardine) fulfil an important ecological role in marine food webs and present challenges to the use of MSE and other simulation-based evaluation approaches. This is due to considerable stochastic variation in their ecology and life history, which leads to substantial observation and process uncertainty. Here, we summarize the current state of MSE for small pelagic fishes worldwide. We leverage expert input from ecologists and modellers to draw attention to sources of process and observation uncertainty for small pelagic species, providing examples from geographical regions where these species are ecologically, economically and culturally important. Temporal variation in recruitment and other life-history rates, spatial structure and movement, and species interactions are key considerations for small pelagic fishes. We discuss tools for building these into the MSE process, with examples from existing fisheries. We argue that model complexity should be informed by management priorities and whether ecosystem information will be used to generate dynamics or to inform reference points. We recommend that our list of considerations be used in the initial phases of the MSE process for small pelagic fishes or to build complexity on existing single-species models.publishedVersio

Below- and above-ground biomass, structure and patterns in ancient lowland coppices

Ancient coppice woods are areas that reflect long-term human influence and contain high species biodiversity. In this type of forest we aimed to: (i) analyze the below- and above ground biomass of stools and estimate the age of largest stool; (ii) define a “zone of interference” for coppices; (iii) describe and classify variability in the shape and size of coppice stools; (iv) define the specific characteristics of the spatial distribution of stems and stools. The study was conducted in the Podyjí National Park, Czech Republic, where two old oak coppice stands were fully stem mapped: Lipina (3.90 ha) and Šobes (2.37 ha). Cores were processed using TimeTable and PAST4. Below- and above-ground biomass of the largest stools was computed using the data from terrestrial laser scanner. Tree zones of influence were analyzed with V-Late landscape analysis tools using Shape Index. The pair correlation function and L function were used to describe the spatial patterns of trees with DBH ≥ 7 cm, and the null model of Complete Spatial Randomness and Matérn cluster process were tested. For a modeled old stool, we estimated a ratio of 2:1 for above/below ground volume with no reduction of below ground biomass regarding the hollow roots. The age of the largest stool was estimated 825 ± 145 (SE) years. An “Inner Zone of Influence” was defined, with a total area covering 323 m2 ha-1. The median area of this zone in both plots was 0.40 m2 for all trees, 0.23 m2 for singles and 0.87 m2 for stools. The Matérn cluster process was successfully fitted to our empirical data. In this model, the mean cluster radius ranged between 1.9 to 2.1 m and mean number of points per cluster was 1.7 and 1.9. The most prevalent characteristics of these ancient oak coppices were their compact shape and clustered spatial distribution up to 10 m

Evaluating signals of oil spill impacts, climate, and species interactions in Pacific herring and Pacific salmon populations in Prince William Sound and Copper River, Alaska

<div><p>The <i>Exxon Valdez</i> oil spill occurred in March 1989 in Prince William Sound, Alaska, and was one of the worst environmental disasters on record in the United States. Despite long-term data collection over the nearly three decades since the spill, tremendous uncertainty remains as to how significantly the spill affected fishery resources. Pacific herring (<i>Clupea pallasii</i>) and some wild Pacific salmon populations (<i>Oncorhynchus spp</i>.) in Prince William Sound declined in the early 1990s, and have not returned to the population sizes observed in the 1980s. Discerning if, or how much of, this decline resulted from the oil spill has been difficult because a number of other physical and ecological drivers are confounded temporally with the spill; some of these drivers include environmental variability or changing climate regimes, increased production of hatchery salmon in the region, and increases in populations of potential predators. Using data pre- and post-spill, we applied time-series methods to evaluate support for whether and how herring and salmon productivity has been affected by each of five drivers: (1) density dependence, (2) the EVOS event, (3) changing environmental conditions, (4) interspecific competition on juvenile fish, and (5) predation and competition from adult fish or, in the case of herring, humpback whales. Our results showed support for intraspecific density-dependent effects in herring, sockeye, and Chinook salmon, with little overall support for an oil spill effect. Of the salmon species, the largest driver was the negative impact of adult pink salmon returns on sockeye salmon productivity. Herring productivity was most strongly affected by changing environmental conditions; specifically, freshwater discharge into the Gulf of Alaska was linked to a series of recruitment failures—before, during, and after EVOS. These results highlight the need to better understand long terms impacts of pink salmon on food webs, as well as the interactions between nearshore species and freshwater inputs, particularly as they relate to climate change and increasing water temperatures.</p></div

Time series of total run and escapement (or spawning biomass, herring).

<p>Total population size and escapement (salmon, in numbers of fish) or total population biomass and spawning stock biomass (spawning herring, in metric tons) for the six populations and four species in our analysis. Harvest for each population can be interpreted as the difference between total (black) and spawning (grey) lines. Red vertical lines are used to indicate 1989 (corresponding to the year of the EVOS event).</p

Gulf of Alaska freshwater discharge (Royer 1982, IMS 2016) as a driver of Pacific herring productivity.

<p>Shown are (a) the total freshwater discharge (m³ s^-1) and (b) log of observed age-3 recruits per spawning biomass (mt)—log(recruits/SSB)—in grey circles, and the model predicted log(recruits/SSB) using freshwater discharge as a covariate (R² = 0.55). High discharge events correspond to reduced productivity (fewer recruits to the population as three year olds). For historical reference, the discharge time series starting in 1931 is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172898#pone.0172898.s002" target="_blank">S2 Fig</a>. R = millions of mature and immature age-3 herring, SSB = spawning stock biomass in metric tons.</p