18 research outputs found

    Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

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    Summary: 1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data

    Environmental preferences of tuna and non-tuna species associated with drifting fish aggregating devices (DFADs) in the Atlantic Ocean, ascertained through fishers' echo-sounder buoys

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    Understanding the relationship between environmental variables and pelagic species concentrations and dynamics is helpful to improve fishery management, especially in a changing environment. Drifting fish aggregating device (DFAD)-associated tuna and non-tuna biomass data from the fishers' echo-sounder buoys operating in the Atlantic Ocean have been modelled as functions of oceanographic (Sea Surface Temperature, Chlorophyll-a, Salinity, Sea Level Anomaly, Thermocline depth and gradient, Geostrophic current, Total Current, Depth) and DFAD variables (DFAD speed, bearing and soak time) using Generalized Additive Mixed Models (GAMMs). Biological interaction (presence of non-tuna species at DFADs) was also included in the tuna model, and found to be significant at this time scale. All variables were included in the analyses but only some of them were highly significant, and variable significance differed among fish groups. In general, most of the fish biomass distribution was explained by the ocean productivity and DFAD-variables. Indeed, this study revealed different environmental preferences for tunas and non-tuna species and suggested the existence of active habitat selection. This improved assessment of environmental and DFAD effects on tuna and non-tuna catchability in the purse seine tuna fishery will contribute to transfer of better scientific advice to regional tuna commissions for the management and conservation of exploited resources

    Incorporating covariates into standard line transect analyses

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    Summary. An implicit assumption of standard line transect methodology is that detection probabilities depend solely on the perpendicular distance of detected objects to the transect line. Heterogeneity in detection probabilities is commonly minimized using stratification,but this may be precluded by small sample sizes. We develop a general methodology which allows the effects of multiple covariates to be directly incorporated into the estimation procedure using a conditional likelihood approach. Small sample size properties of estimators are examined via simulations. As an example the method is applied to eastern tropical Pacific dolphin sightings data

    Purse-seine vessels as platforms for monitoring the population status of dolphin species in the eastern tropical Pacific Ocean : the use of fishing vessels as scientific platforms

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    In the eastern tropical Pacific Ocean, yellowfin tuna (Thunnus albacares) are often found in association with spotted (Stenella attenuata) and spinner (Stenella longirostris) dolphins. Purse-seine vessels use this co-occurrence to locate the tuna by searching for dolphins and associated birds. Data collected by onboard observers since the late 1970s were used to develop indices of relative abundance for dolphins, based on line-transect methodology, when the primary method of detection of dolphin herds was with binoculars. However, trend estimation was subsequently discontinued in 2000 due to concerns about changes in reporting rates of dolphin herd detections with increased use of helicopter and radar search. At present, as a result of a hiatus in fishery-independent surveys since 2006, fisheries observer data are the only source of information with which to monitor the status of eastern tropical Pacific Ocean dolphin populations. In this paper, trend estimation with the onboard observer data is revisited using a sightings-per-unit-effort approach. Despite different assumptions and model structure, the results indicate a lack of independence between the distribution of search effort and the search methods used, and the abundance of dolphin herds associated with tunas, on several spatial and temporal scales. This lack of independence poses a considerable challenge to the development of a reliable index of relative abundance for dolphins with these data. Given these results, alternatives for dolphin abundance estimation are discussed. One alternative is the use of purse-seine vessels for line-transect surveys during fishery closure periods. Another alternative is the use of purse-seine vessels during normal fishing operations as platforms for the collection of mark-recapture data (e.g., passive integrated transponder tags or genetics sampling). Life-history data collection, as a supplement to the collection of other data types, is also discussed. Further research and development is needed to assess whether these alternative methods will be useful.PostprintPeer reviewe
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