Proceedings of the PICES/CoML/IPRC Workshop on Impact of Climate Variability on Observation and Prediction of Ecosystem and Biodiversity Changes in the North Pacific

Table of Contents [pdf, 0.09 Mb] Section I - Presentations and Discussions at Plenary Sessions Introduction and Overview of Workshop Objectives [pdf, 0.07 Mb] Plenary Session Presentations [pdf, 2.23 Mb] Reports of the Breakout Group Discussions [pdf, 0.43 Mb] Closing Plenary Discussion and Recommendations [pdf, 0.11 Mb] Section II - Extended Abstracts of Individual Presentations at Breakout Group Sessions Breakout Group 1: Physical/Chemical Oceanography and Climate [pdf, 6.14 Mb] Breakout Group 2: Phytoplankton, Zooplankton, Micronekton and Benthos [pdf, 28.14 Mb] Breakout Group 3: Fish, Squid, Crabs and Shrimps [pdf, 4.30 Mb] Breakout Group 4: Highly Migratory Fishes, Seabirds and Marine Mammals [pdf, 6.27 Mb] Appendix 1. Workshop agenda [pdf, 0.15 Mb] Appendix 2. List of participants [pdf, 0.13 Mb] (Document pdf contains 216 pages)

Prediction, Chaos and Ecological Perspective.

As defined, the modeling procedure is quite broad. For example, the chosen compartments may contain a single organism, a population of organisms, or an ensemble of populations. A population compartment, in turn, could be homogeneous or possess structure in size or age. Likewise, the mathematical statements may be deterministic or probabilistic in nature, linear or nonlinear, autonomous or able to possess memory. Examples of all types appear in the literature. In practice, however, ecosystem modelers have focused upon particular types of model constructions. Most analyses seem to treat compartments which are nonsegregated (populations or trophic levels) and homogeneous. The accompanying mathematics is, for the most part, deterministic and autonomous. Despite the enormous effort which has gone into such ecosystem modeling, there remains a paucity of models which meets the rigorous &! validation criteria which might be applied to a model of a mechanical system. Most ecosystem models are short on prediction ability. Even some classical examples, such as the Lotka-Volterra predator-prey scheme, have not spawned validated examples.

The classification and prediction of macroinvertebrate communities in British rivers

This article describes the progress of the River Communities Project which commenced in 1977. This project aimed to develop a sensitive and practical system for river site classification using macroinvertebrates as an objective means of appraising the status of British rivers. The relationship between physical and chemical features of sites and their biological communities were examined. Sampling was undertaken on 41 British rivers. Ordination techniques were used to analyze data and the sites were classified into 16 groups using multiple discrimination analysis. The potential for using the environmental data to predict to which group a site belonged and the fauna likely to be present was investigated.

Mathematical models for the prediction of temperature distributions resulting from the discharge of heated water into large bodies of water

Mathematical models for heated water outfalls were developed for three flow regions. Near the source, the subsurface discharge into a stratified ambient water issuing from a row of buoyant jets was solved with the jet interference included in the analysis. The analysis of the flow zone close to and at intermediate distances from a surface buoyant jet was developed for the two-dimensional and axisymmetric cases. Far away from the source, a passive dispersion model was solved for a two dimensional situation taking into consideration the effects of shear current and vertical changes in diffusivity. A significant result from the surface buoyant jet analysis is the ability to predict the onset and location of an internal hydraulic jump. Prediction can be made simply from the knowledge of the source Froude number and a dimensionless surface exchange coefficient. Parametric computer programs of the above models are also developed as a part of this study. This report was submitted in fulfillment of Contract No. 14-12-570 under the sponsorship of the Federal Water Quality Administration.

Prediction and confirmation of seasonal migration of Pacific sardine (Sardinops sagax) in the California Current Ecosystem

During the last century, the population of Pacific sardine (Sardinops sagax) in the California Current Ecosystem has exhibited large fluctuations in abundance and migration behavior. From approximately 1900 to 1940, the abundance of sardine reached 3.6 million metric tons and the “northern stock” migrated from offshore of California in the spring to the coastal areas near Oregon, Washington, and Vancouver Island in the summer. In the 1940s, the sardine stock collapsed and the few remaining sardine schools concentrated in the coastal region off southern California, year-round, for the next 50 years. The stock gradually recovered in the late 1980s and resumed its seasonal migration between regions off southern California and Canada. Recently, a model was developed which predicts the potential habitat for the northern stock of Pacific sardine and its seasonal dynamics. The habitat predictions were successfully validated using data from sardine surveys using the daily egg production method; scientific trawl surveys off the Columbia River mouth; and commercial sardine landings off Oregon, Washington, and Vancouver Island. Here, the predictions of the potential habitat and seasonal migration of the northern stock of sardine are validated using data from “acoustic–trawl” surveys of the entire west coast of the United States during the spring and summer of 2008. The estimates of sardine biomass and lengths from the two surveys are not significantly different between spring and summer, indicating that they are representative of the entire stock. The results also confirm that the model of potential sardine habitat can be used to optimally apply survey effort and thus minimize random and systematic sampling error in the biomass estimates. Furthermore, the acoustic–trawl survey data are useful to estimate concurrently the distributions and abundances of other pelagic fishes.

Prediction of discard mortality for Alaskan crabs after exposure to freezing temperatures, based on a reflex impairment index

Millions of crabs are sorted and discarded in freezing conditions each year in Alaskan fisheries for Tanner crab (Chionoecetes bairdi) and snow crab (C. opilio). However, cold exposures vary widely over the fishing season and among different vessels, and mortalities are difficult to estimate. A shipboard experiment was conducted to determine whether simple behavioral observations can be used to evaluate crab condition after low-temperature exposures. Crabs were systematically subjected to cold in seven different exposure treatments. They were then tested for righting behavior and six different ref lex actions and held to monitor mortality. Crabs lost limbs, showed ref lex impairment, and died in direct proportion to increases in cold exposure. Righting behavior was a poor predictor of mortality, whereas reflex impairment (scored as the sum of reflex actions that were lost) was an excellent predictor. This composite index could be measured quickly and easily in hand, and logistic regression revealed that the relationship between reflex impairment and mortality correctly predicted 80.0% of the mortality and survival for C. bairdi, and 79.4% for C. opilio. These relationships provide substantial improvements over earlier approaches to mortality estimation and were independent of crab size and exposure temperature.

Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.

Prediction of drained weight in canned prawn under commercial conditions

A general formula for the prediction of drained weight of canned prawn processed under laboratory condition has been worked out earlier (Chaudhuri et al., 1978). Attempts were made in this communication to modify the general formula to predict the drained weight under commercial conditions of processing particularly blanching, as the moisture content of meat depends on the quantum of heat received during blanching (Govindan, 1975).

Trophic State Index, morphoedaphic index and fish yield prediction in a sub-tropical lake, Manchar (Sindh), Pakistan

Limnological factors of a sub-tropical lake Manchar were studied on seasonal basis. The mean values of various parameters were: transparency, (secchi disc reading): 90.5 cm, Orthophosphate: 0.257 mg/l, TDS: 3310,5 mg/l, Conductivity: 5232 µs/l, Total Chlorophyll (Planktonic): 31.3 µg/l Planktonic biomass: 5466 µg/l. Trophic state index (TSI) was calculated by using Carlson's (1977) equations. Mean TSI for transparency was 61, while for orthophosphate and chlorophyll, it was 82 and 64 respectively. TSI values indicate advanced eutrophic state of Manchar Lake. Morphoedaphic index (MEI) was also calculated on seasonal basis. The mean values were, TDS: 1103, conductivity: 1744, alkalinity: 60, transparency: 29 and biomass (plankton dry weight): 1746. Fish yield prediction for Manchar Lake (Z =3m, mean area=100 km²) was calculated by using MEI values. The results were quite different among various parameters. Conductivity (89.1mt/y), biomass (67.6 mt/y) and TDS (44.6 mt/y) were found to be good predictors of fish yield. Chlorophyll, transparency and alkalinity values gave very low estimate.