California coastal salmonid population monitoring: strategy, design, and methods

Citation

Adams, P. B., L. B. Boydstun, S. P. Gallagher, M. K. Lacy, T. L. McDonald, and K. E. Shaffer (2011). “California coastal salmonid population monitoring: strategy, design, and methods”. In: Fish Bulletin 180. URL: https://escholarship.org/uc/item/9036n65t.

Abstract

California’s salmon and steelhead populations have experienced marked declines leading to listing of almost all of California’s anadromous salmonids under the California Endangered Species Act (CESA) and Federal Endan-gered Species Act (ESA). Both CESA and ESA listings require recovery plans that call for monitoring to provide some measure of progress toward recovery. In addition, there are related monitoring needs for other management activi-ties such as hatchery operations and fisheries management.
This California Coastal Salmonid Monitoring Plan (CMP) has been devel-oped to meet these monitoring needs, describing the overall strategy, design, and methods used in monitoring salmonid populations. Implementation de-tails of the plan are described in Shaffer (in prep.). The CMP uses the Viable Salmonid Population (VSP; McElhany et. al. 2000) concept as the framework for plan development. The VSP conceptual framework assesses salmonid viability in terms of four key population characteristics: abundance, produc-tivity, spatial structure, and diversity. High abundance buffers a population against both ‘normal’ and catastrophic variation due to environmental condi-tions and loss due to anthropogenic factors. High productivity will lead to more certain replacement when populations are placed under either natural or anthropogenic stress. Wide spatial structure reduces extinction risk due to catastrophic events and provides pathways for recolonization. Diversity in life history traits (e.g., time of spawning, juvenile life history, adult fish size, age structure, degree of anadromy, etc.) provides resilience against extinction risk from changing conditions.
The CMP divides California into Northern and Southern areas with a bound-ary south of Aptos Creek and north of the Pajaro River, based on differences in species composition, levels of abundance, distribution patterns, and habitat differences that necessitate different monitoring approaches. Both the larger Evolutionarily Significant Units-level scale and the popula-tion viability criteria are based on the four VSP parameters. The assessment of viability, however, will be based upon adult population size, and the distribu-tion and connectivity of these populations (Boughton et al. 2007, Spence et al. 2008, and Williams et al. 2008). The CMP provides a sampling frame-work to collect information at the appropriate life stages and spatial scales to evaluate adult salmonid abundance both at larger regional scales and at the population level. Productivity is calculated as the trend in abundance over time. CMP design also allows basic assessments of connectivity through the collection of juvenile distribution and relative abundance data. Measurement of diversity will be based on local evaluation of essential life history variants and both broad and focused assessments of genetic diversity patterns.
Adult abundance monitoring will be approached differently between the Northern and Southern areas due to differences in species composition, abun-dances, and habitat conditions. In the Northern Area, adult numbers will be estimated mostly through expanded redd surveys and in the Southern Area adults will be counted at fixed stations. In the Northern Area, adult abun-dance estimates will be needed for multiple species over large areas. Surveys will be selected in a random, spatially balanced manner. Spatial balance is important because salmonid numbers from samples near each other tend to be similar, so that more information relevant to a regional scale evaluation is obtained from samples that are spaced out. Redd surveys have generally been shown to be the most reliable means of estimating multi-species populations in California, but will require redd-to-adult corrections to estimate numbers of adults by species from them. Other methods (e.g., live fish counts for Chi-nook salmon) will be used where necessary.
In the Southern Area, steelhead are the only salmonid present and popula-tions are very small, making abundance difficult to assess. Steelhead arrival is associated with storm events that raise water levels drastically. These species characteristics and environmental features therefore make steelhead in the Southern Area difficult to monitor, and due to the low abundance and dif-ficult sampling conditions, fixed stations will be used to count adult Southern Area steelhead.Spatial structure refers to the geographical and ecological distribution of salmonids across the landscape. Broad spatial distribution and connectiv-ity among populations are important traits that protect against the effects of catastrophic events and buffer extinction risk, particularly at low abundance.
Spatial structure will be monitored using summer and fall juvenile snorkel surveys over reaches selected in a random, spatially balanced manner. A larger number of juvenile surveys can be accomplished in less time and expense than adult surveys because it is simpler and can occur at a more operationally favorable time of the year. In the Northern Area, spatial structure monitoring will be conducted only for coho salmon since steelhead occur over a wider area. This monitoring will provide estimates of coho salmon spatial structure. Since steelhead occur over a wide area, they will be counted as well as a relative measure of spatial struc-ture. Chinook salmon spawn in only a few well-defined areas and outmigrate in the spring before the juvenile surveys take place, and information on their spatial structure will come from adult monitoring. In the Southern Area, juvenile spatial structure monitoring will be conducted for steelhead, the only salmonid present. Diversity traits are strongly adaptive for local areas and populations, and these traits allow salmonids to survive in the face of unique local natural and anthropogenic challenges. Higher level diversity traits have been considered in the creation of the listing and stratification units; however, population level diversity traits may be very different from one geographical or popula-tion unit to another. Therefore, local diversity traits will need to be surveyed, eventually leading to local diversity monitoring plans. Specific projects target-ing both broad and focused levels and patterns of genetic diversity will be developed. Tissue collections for these projects will be coordinated with other CMP activities. Life Cycle Monitoring (LCM) stations will provide estimates of freshwater and ocean survival, essential to understanding whether changes in salmonid numbers are due to recovery from improvements in freshwater habitat condi-tions or changes in ocean conditions. An LCM station will include an abso-lute measure of adult abundance from a counting facility, a spawning survey estimate of adult abundance, and an estimate of outmigrating smolts. The adult counts and outmigrant smolt counts will provide estimates of fish in and fish out, that can be used to provide relative estimates of freshwater and marine survival. The counting station data and adult survey estimates will be used to develop an estimation factor between redds and adults for calibra-tion of adult surveys conducted in other watersheds. The LCM sites are also expected to be magnets for other kinds of recovery-oriented research, par-ticularly studies of fish habitat-productivity relationships and evaluations of habitat restoration effectiveness. Finally, a data management structure will be created to provide general ac-cess to the CMP data. Monitoring is necessary to provide data that will be analyzed to inform management decisions, and those data must be made available in a timely manner to managers in a usable form. The data manage-ment structure is one of the most important parts of the CMP, ensuring that consistent data standards and protocols are applied across and within monitoring areas and that data flow is coordinated from the field to a central data collection center. It will also ensure that data reporting necessary for common analytical activities occurs in a timely manner and will provide a data source for other analytical needs.