From Ken Jones and John Zeissig of CA Fishing Coalition
At their Nov. 13 meeting the SAT for the North Central Region MLPA introduced a draft option for assessing the level of protection offered by various extractive processes (fishing techniques and methods of take) if allowed within MPAs. In order to provide more flexibility in assessing the impact of the various ranked techniques on MPAs, this draft option expanded a similar rank ordering of level of protection used in the South Central Region from three levels to six levels. Members of the SAT, the Regional Stakeholders Group, and the Blue Ribbon Task Force have all expressed some doubt or confusion over how to apply this ordinal list of levels of protection to the assessment of MPAs. (See “Proposed Revisions to the draft evaluation method report of the MLPA Master Plan Science Advisory Team”, from MLPA Initiative Staff, Nov. 18, 2007.)
One reason for this is that the six levels of protection relate to one another only by the logical operation “greater than”. For example, a ranking of 2 does not mean that the practices included in that category are half as protective as practices ranked in category 4, only that they are less protective by some unspecified amount. Furthermore, different practices ranked in the same category are not necessarily equivalent. In applying the rank ordering to assessing the impact of a particular practice on an MPA there is, therefore, no basis for quantifying the
effect that allowing that practice will have on any particular species or on the ecosystem in general.
In order to properly answer these types of questions it is necessary to quantify the various practices, preferably on a rational scale where the elements consist of integers or are continuous variables. Beyond that, it would be extremely important to have such quantification based on empirical data rather than the somewhat plausible but essentially ad hoc considerations that have lead to the present ranking scale. One way to accomplish this would be to relate some measure of angling effort, such as fishing trips taken or time spent fishing (independent variables), to some measure of fishing success, like number of fish caught, or pounds of fish caught (dependent variables).
The most obvious source of precisely these kinds of data are the data collected by the California Recreational Fishing Survey (CRFS) conducted by the California Department of Fish and Game (DFG). The stated purpose of this effort is: “In response to fishery managers' and constituents' concerns about the use of MRFSS for making management decisions, CDFG and the Pacific States Marine Fisheries Commission (PSMFC) developed the CRFS. The CRFS was created to provide accurate and timely estimates of marine recreational finfish catch and effort. The program was implemented state-wide in January 2004.”
What can we learn by looking at the CRFS database? Let’s take an example and see how it can be applied to the assessment of the impact of some fishing categories on an MPA. Specifically, we want to see how the number of fish caught (dependent variable) varies as a function of whether the fisherman is fishing from the shore or bank, from a private boat or rental skiff, or from a party fishing boat (independent variables).
We can go to the DFG website, http://www.dfg.ca.gov/ and then click on the tab at the top of the page that says “Marine”. On the page that comes up click on “Ocean Sport Fishing”, just below the tabs at the top. Scroll down a little way and click on “California Recreational Fishing Survey (CRFS)”. You will be taken to a page where you can query the database for information by using the categories above.
Note that the numbers obtained are estimates, rounded to the nearest 1000, of the total effort and total catch, generated from large scale sampling of actual effort and catch by a complex mathematical algorithm. Also obtained are estimated proportional standard errors that reflect uncertainties associated with the estimates.
Level of Protection (LOP): Examples Rating Angling Methods
The following information was obtained by asking for the number of fishing trips by anglers fishing in the ocean, for all species, from the bank, beach, or man made structures (all shore modes, MMBB) in the San Francisco District, in the ocean only, for fish inspected during the survey, between the start of the survey in January 2004 and October 2007, the last monthly data available at the time of this analysis:
Number of angler fishing trips (T) = 858,000.
Next we want to ask how many fish of all species were caught on these
858,000 fishing trips.
Number of fish caught (C) = 996,000.
To get an estimate of the efficiency of bank and beach fishing we take the ratio of fish caught per angler fishing trip:
C/T = 996,000 / 858,000 = 1.16 Fish/Trip.
Because the idea of LOP is reciprocally related to the catch per trip (more fish caught per trip results in a lower level of protection) we take the reciprocal of C/T = 1/C/T = T/C as our measure of LOP:
LOP = T/C = 0.86.
In order to relate the LOPs to the entire North Central Region of the MLPA, we need to expand our coverage by including the Wine District of the CRFS. The San Francisco District of the CRFS corresponds fairly well with the southern sub region of the North Central MLPA, but the northern sub region of the North Central MLPA is smaller than the Wine District of the CRFS, which extends from roughly the Tomales Bay area to Cape Mendocino. This will tend to result in underestimates of LOP for anglers, although the distortion should not be very large.
Taking the CRFS estimates from the Wine District for the same criteria that we used in the S.F. District and combining them gives us the following:
C = 996,000 (SF) + 117,000 (Wine) = 1,113,000.
Combining angler trips gives us:
T = 858,000 (SF) + 165,000 (Wine) = 1,023,000.
LOP = 1,023,000/1,113,000 = 0.92
Repeating this procedure for private boat and rental skiff fishing and party boat fishing gives us the following table for the LOP of the fishing methods in our original question. For boat fishing modes, however, the data query added the criterion that the fish were caught within 3 miles of shore to correspond to the seaward boundaries of MPAs.
Fishing Method LOP
Bank & Beach 0.96
Private Boat & Rental 0.48
Party Boat 0.13
We can now say, for example, for an angler fishing trip on a party boat in the North Central Region, from Jan. 2004 through Oct., within 3 mi. of shore, the angler will on the average catch approximately 3.69 times the number of fish that he would have caught had he fished from a private boat, and approximately 7.38 times the number of fish he would have caught had he fished from shore.
Before we can use LOP to assess the effect of some activity on an MPA, we’ll first have to deal with some obvious objections that could limit the generality of the concept. One might jump to the (false) conclusion that C/T = 0 means an infinite LOP. Realistically, fishermen have to be considered to be just one of a variety of predators in the ecosystem, so that eliminating fishing just shifts the balance of predation among species, and may reduce the overall level of predation, but certainly doesn’t eliminate it. For that matter, eliminating all predation will not result in a LOP of zero since some level of mortality will remain in any event. On the other hand, LOP allows a direct comparison between harbor seals and fishermen, for example, if one considers a day’s foraging of a harbor seal to be the equivalent of a day fishing by an angler.
Example Comparing Shore Angler LOP to Harbor Seal LOP
While not as straightforward as comparison of fishing modes using the CRFS data alone, it is nevertheless possible to make comparisons of LOP between different species. The major difficulties in doing this type of comparison arise from the paucity of data pertaining to some species and the fact that the relevant dependent variables are not always the same even when data is available. For the comparison of shore angler LOP to harbor seal LOP the first problem encountered is the measurement of harbor seal prey consumption in lbs./day rather than the fish/trip
metric used in the previous examples.
From the “MPLA Master Plan Science Advisory Team Draft Work Group Responses to Science Questions Posed by the NCCRSG at its August 22-23, 2007 Meeting (revised November 9, 2007)” we have the information that harbor seals consume 10 lbs of prey/day, as well as the information that there are approximately 8,000 harbor seals within the North Central Region during the “peak breeding season”. If we regard a day’s foraging by a harbor seal to be equivalent to a fishing trip by an angler then a seal has an LOP by weight in lbs. of 0.1 (Keeping in mind the uncertainty of this data).
The angler catch in tonnes is available from the CRFS database using the same MMBB criteria we used in our initial example, so we can obtain an estimate from the database that we can convert to lbs./trip for shore anglers, and use that to calculate a LOP by weight of catch. For catch by weight, we obtain the following for Jan. 2004-Oct. 2007:
C = (SF) tonnes 336 + (Wine) tonnes 76 = 472 tonnes
472 tonnes X 2200 = 1,038,400 lbs.
T = 858,000 (SF) + 165000 (Wine) = 102,3000 angler trips
LOP (by weight) = 1,023,000/1,038,400 = 0.99
So, to a first approximation, it appears that it takes about ten shore and pier anglers (0.99 LOP/0.10 LOP = 9.9) to equal the extractive effect of a single harbor seal.
Of course, there are a number of caveats that need to be attended to in using data like this. As mentioned previously, the LOP of anglers is likely to be underestimated by the way this analysis was conducted. Also the estimate of harbor seal population is almost certainly very rough. Comparisons to other pinnipeds were not considered, so the combined effect of all pinnipeds is certain to be much greater than the apparent order of magnitude prey-take advantage of harbor seals over shore anglers. The LOPs of bird and fish-fish predation have not been addressed at all. The estimates of LOP derived from any recreational fishing data in California are surely underestimates of the true efficiency of fishing effort in every category, because the size and take limits imposed by DFG regulations truncate the amount of catch for any species to which they apply (assuming anglers are abiding by the regulations). They also do not include take due to poaching.
Other factors to be considered are the validity of data available from the CRFS database. While most of the numbers seem plausible, there are some entries that do not correspond to what one would expect based on personal experience. Another difficulty, that arises from the way we constructed our examples above, is that it allows us to compare predation/angling methods in terms of their effect on overall numbers or weight of fish caught, but clearly there are differences in the particular species caught depending on the method as well as geographically within the region. This can be examined, but no attempt was made to do so at this time. In addition, there are a number of other cautions to be considered in using the CRFS, or any other data, for that matter. This is certainly not an exhaustive list of all the potential pitfalls involved in doing this kind of analysis, and there probably other data sources that can be usefully employed.
Given the caveats above, the goal is to accomplish something like what follows. Ascertain at least a manageable cluster of important predators and generate estimates of their effects on the ecosystem in terms of take of species of interest. Express these effects in terms of LOPs as outlined in this essay. If this can be accomplished, then it might be possible to get at least a static picture of the relative importance of these predators in the ecosystem. My suspicion, based on the preliminary analysis above, is that shore anglers will rank very low in the
hierarchy of predators (by a factor of at least 2-4 compared to boat fishermen, a factor of 7-10 compared to party boat fishermen, more than an order of magnitude in comparison to seals and sea lions, and unknown additional amounts attributable to birds etc.). The ratios are sufficiently divergent that it can be persuasively argued that allowing shore fishing has a negligible effect on the ecology of an MPA (i.e., a ribbon! proposal or variation thereof). In any event the LOP measurement scheme has considerable advantages over the current ad hoc ranking, which relies on subjective judgments and offers scant hope for an equitable solution.