Removal fishing to estimate catch probability: preliminary data analysis

Transcription

1 Removal fishing to estimate catch probability: preliminary data analysis Raymond A. Webster Abstract This project examined whether or not removal sampling was a useful technique for estimating catch probability and modelling the factors affecting catchability of Pacific halibut. Sampling was done at 20 setline survey stations in the eastern part of Area 3A, and at each station a sequence of five sets was made on consecutive days. The expectation was that catch would decrease over the five days of fishing, and the rate of decrease would provide information on catch probability. We anticipated some movement into and out of the catchable population during the five days, and developed models that allowed for some degree of local migration. Little, if any, decline in catch was observed, and the results of preliminary modelling imply that there was such large movement into the catchable population following removals that useful estimates of catch probability are impossible to obtain. Our conclusion is that removal sampling is not a promising approach for modelling the catchability of Pacific halibut. Introduction The current International Pacific Halibut Commission (IPHC) setline survey uses catch per unit effort (CPUE) as the basis of a relative index of population size or biomass in each regulatory area. However, CPUE is a function not only of the number of halibut, but also of their probability of capture. The capture probability may vary according to many factors, such as environmental covariates (depth, temperature), individual covariates (sex, maturity, size, prior injuries), and design variables (location of set, time of day or year, length of soak). Failure to account for potential variation in capture probability means CPUE can be a misleading index of abundance. Removal sampling of closed populations is a long established technique for estimating population size while accounting for detection or catch probability. When applied to fish sampling, the same population is repeatedly sampled over multiple occasions in quick succession. For halibut on the setline survey, this would require several consecutive sets to be made at a survey station. The basic idea is that the catch at a station will decline on each successive set as more of the local population is removed, and modeling the rate of decline will allow us to estimate the number of fish that were present prior to the first set. Standard removal models are equivalent to the behavioural response model of closed population capture-recapture modelling (Pollock, 1990), but with the practical advantage that animals do not need to be tagged and recaptured on multiple occasions. Depending on local abundance, catch probability and the number of consecutive sets, information at each individual station may be poor. However, when data from multiple stations are combined using hierarchical modelling, it is possible to obtain good estimates of relative abundance, capture probability, and their relationships with measured covariates for the whole regulatory area (Forsyth et al, 2005, Webster et al, 2008). Prior to the study, concern was raised about movement into and out of the catchable population (local migration) during removal sampling, violating the standard model assumption of population 221

2 closure. To accommodate the possibility of some movement, we modified the usual migration models to allow for a fixed daily rate of migration. Simulation studies showed that it was possible to estimate both the rate of migration and catch probability with little bias provided that migration was low to moderate and catch probability was not too low. We considered migration rates of r=0.5 or less, where r=1 means the migrants replace removed fish on average each day, and r=0 means there is no migration. Only when an animal s daily catch probability, p, was low (0.25 in our simulation study) did bias become a problem, and even then, estimators were great improvements over standard removal estimators. In this study, we trialed removal sampling as a technique for directly estimating catch probability at a sample of setline survey stations in one regulatory area in For the selected stations, a sequence of multiple consecutive sets was made. The first set was the standard survey set. Subsequent sets used the same methods and collected the same data on halibut and station conditions as standard survey sets, with the exception that otoliths were only collected during the first day s set for the setline survey. To maximize the number of stations we could include in the study, stations were selected in clusters of four (Figures 1 and 2), allowing four stations to be fished consecutively within a single day. Five clusters were selected for the study, three in the Yakutat setline survey region, and two in the Prince William Sound survey region. The clusters were selected by generating all possible designs with the stated number of clusters of four stations, discarding any that were considered operationally impractical, and selecting a design at random from the remaining designs. During the course of the data collection, one cluster was replaced due to the presence of a commercial fishing vessel on one of the stations of the original cluster (Figure 1). Halibut catch Table 1 and Figure 3 summarize catch of legal-sized halibut by cluster and fishing day, while Table 2 gives mean lengths of legal-sized fish. Overall, catch was greatest on the second day, and declined on average thereafter, with lowest catch on day 5. Changes in catch over the five days varied among the five removal clusters: cluster 1 had no obvious trend in catch; cluster 2 has highest catch during the first two days; clusters 3 and 4 both caught more legal halibut on the second and third days; and cluster 5 has highest catch on days 4 and 5. There was no clear trend in mean fish length over the five days, with average length over all clusters remaining stable. Catch of sublegal fish was highly variable across days and among clusters. Like legal halibut, the peak in catch was on the second day, largely due to high catches on cluster 3 stations. However, catch of sublegals increased in the last two days on clusters 4 and 5, leading to total catches for those days that were little different from day 2. Bycatch and returned bait Increases in competition of other species for bait can lead to decreases in catch probability for halibut as less bait becomes available for the target species. High levels of bycatch can therefore depress catch of halibut, while low amounts of returned bait can mean that fewer halibut had the opportunity to be caught. Table 4 shows the average percentage of hooks with bycatch for each cluster by fishing day, based on counts from the first 20 hooks of each skate. On all clusters, bycatch peaked on the fourth day, with an overall mean of 29%, and was lowest on average on the 222

3 final day, at 25%. As might be expected, the reverse was true for returned baits, with fewest on the fourth day (8% on average) and the most on the final day (13% on average). Preliminary modelling The hope was that we could use removal sampling to give us estimates of catch probability, and model its relationship with variables such as depth, weather conditions, tidal flux, and halibut size and sex. Successful modelling depended on observing a declining catch and on the rate of migration not being too high. As the rate of migration approaches 1, it becomes harder to distinguish high catchability and low local abundance from low catchabilty and high local abundance. The daily catches of legal-sized halibut (Table 1) showed little average decline over the five days, with some clusters showing no decline at all. As a first attempt at estimating catch probability, we fitted a simple removal with migration model to the total counts from Table 1. The migration rate for this model was estimated as r ˆ = 0.96 (95% CI: ), almost at the daily replacement rate of 1, and estimates of daily migrants range from 351 between the second and third daily sets and 318 after the fourth set. With such large daily movement of animals into the catchable population, useful estimation of catch probability is almost impossible, and the estimate of catch probability was p ˆ = 0.53, with a very wide 95% CI of We have also attempted to fit more complex models that include relationships between catch probability and individual station covariates using Bayesian hierarchical modelling. The Markov chain Monte Carlo algorithms we used to fit such models do not converge, and estimation of model parameters has been unsuccessful to date. This is not very surprising given that for many if not most stations, there was no apparent decline in legal catch over the five fishing days, and for some stations there was even an increase in catch. Modelling of these data is ongoing, but given the observed data, we are not optimistic that we will obtain useful results. Discussion Because of apparently very high rates of movement of fish into the catchable population around the survey station, removal sampling does not look like a promising method for estimation of catch probability of halibut or for exploration of the relationships of catchability with station or individual halibut level covariates. We anticipated some movement towards the survey lines between fishing days, either because of the attractive effect of baited lines, the replacement of depleted habitat with new fish, or the movement of groups of fish passing through the area around a station. However, rates of movement of the order of that estimated in our preliminary model fitting makes useful inference on catchabilty almost impossible. The models we have tried to fit to date assume catch probability of an individual fish is constant with time. There are a number of reasons why this might not be true. One suggestion is that the size distribution of catchable fish could change over the five days, possibly due to larger, more catchable fish being caught first. If this were the case, it might be expected that catches would be more likely to decline than maintain the same level on average, even in the presence of high migration. In any case, mean lengths remained very stable during the five fishing days, and changing fish size does not seem to be a factor. Changes in bycatch can also affect catchability: as competition with halibut for available baits increases, an individual halibut s chance of being caught decreases. Thus stable halibut catches could be explained by declining bycatch over the five days (and similarly by increased bait return) rather than a migration rate close to 1. However, 223

4 except for a drop on the final day in all five clusters, bycatch either remained stable or increased over the removal period. Another suggestion was that changes in local abundance could be due to tidal fluctuations, specifically, that abundance increases during building tides and decreases during declining tides. We have yet to look closely at tidal data during the removal fishing period, but information from staff on the vessel conducting the study was that fishing was carried out over both building and declining tides. References Forsyth, D. M., Link, W. A., Webster, R., Nugent, G. and Warburton, B Nonlinearity and seasonal bias in an index of brushtail possum abundance. Journal of Wildlife Management, 69, Pollock, K. H., Nichols, J. D., Brownie, C. and Hines, J. E Statistical Inference for Capture- Recapture Experiments. Wildlife Monographs, 107. Webster, R. A., Pollock, K. H., Ghosh, S. K. and Hankin, D. G Bayesian spatial modeling of data from unit-count surveys of fish in streams. Transactions of the American Fisheries Society, 137,

5 Table 1. Legal-sized catch by cluster, sex and removal fishing day. Totals for each cluster include a small number of fish of unknown sex. Cluster Day 1 Day 2 Day 3 Day 4 Day 5 Female Male Total Female Male Total Female Male Total Female Male Total Female Male Total Total Table 2. Average length (cm) of legal-sized catch by cluster, sex and removal fishing day. Means for each cluster include a small number of fish of unknown sex. Cluster Day 1 Day 2 Day 3 Day 4 Day 5 Female Male All Female Male All Female Male All Female Male All Female Male All All

6 Table 3. Catch of sublegal halibut by cluster and fishing day. Cluster Day 1 Day 2 Day 3 Day 4 Day All Table 4. Percentage of hooks catching other species (bycatch) by cluster and fishing day. Data come from the first 20 hooks of each skate of each set. Cluster Day 1 Day 2 Day 3 Day 4 Day All Table 5. Percentage of returned hooks with baits by cluster and fishing day. Data come from the first 20 hooks of each skate of each set. Cluster Day 1 Day 2 Day 3 Day 4 Day All

7 145 W 144 W 143 W 142 W 141 W 140 W N 60 N " " S S " " S S #* #* #* #* N 59 N Legend #* Cluster 1 Cluster 2 S Cluster 3 not fished " Cluster 3 fished W 144 W 143 W 142 W 141 W 140 W Figure 1. Survey stations in the Yakutat region selected for the removal sampling pilot study. 227

8 148 W 147 W 146 W 145 W 61 N 61 N N 60 N ^ ^ ^ ^ Legend % Cluster 4 ^ Cluster % % % % 148 W 147 W 146 W 145 W Figure 2. Survey stations in the Prince William Sound region selected for the removal sampling pilot study. 228

9 legal sized catch (count) total cluster 1 cluster 2 cluster 3 cluster 4 cluster Figure 3. Catch of legal-sized halibut by cluster and fishing day. day 229

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