Results - Fish and Wildlife Integration
This section of the Results addresses fish; it is organized as follows:
Integrated Assessments of Fish and Wildlife Populations and Ecological Functions
Influence of Habitats on Populations and Functions
Influence of Populations on Themselves
Influence of Populations on Other Populations
Influence of Populations on Habitats and KECs
This section presents the results of the integrated assessments of fish and wildlife populations and ecological functions. As shown in Figure IV.C.1 in Methods, we focused on specific interactions between habitats and populations, and between fish and wildlife.
The results of the analyses for fish and wildlife interaction also include the Ecosystem Functions Analyses. The functions analyses presented in this report build, in part, on the work compiled by Cederholm et al. (2000) who identified ecological relationships between Pacific salmon and wildlife. In this section, we first briefly review the fish and wildlife relationships presented and functional questions asked in Cederholm et al. (2000.) Our analysis suggests how functional assessments might be continued at the subbasin scale by relating specific management activities to specific habitat elements that occur within each wildlife habitat type (see Appendix K).
One result pertains to the influence of habitats (including KECs) on populations of fish and wildlife.
For fish, this was analyzed by using the EDT model to determine how the array of fish habitats potentially influence fish populations. Results are presented in the Fish-Results section.
For wildlife, we analyzed the influence of wildlife habitats and KECs on wildlife populations and KEFs by using the SHP database to determine (1) how wildlife habitats, terrestrial vegetation structural conditions (structural or successional stages of wildlife habitats), and KECs (“habitat elements” in the SHP database) influence the presence of or habitat value for wildlife species, and then (2) the arrays of KEFs associated with those wildlife species.
At the broad scale of this assessment, we could map and analyze only gross changes – that is, only changes in amount or types—of wildlife habitats. Changes in vegetation structural conditions and in KECs, which are finer-scale elements of habitats, could not be mapped and analyzed at the broad scale. They will need to be analyzed at the next finer scale of resolution, such as in a subbasin assessment, because there are no consistently mapped, broad-scale GIS data on these conditions for the entire Basin.
Results of the broad-scale influence of wildlife habitats on wildlife species were brought into the functional analyses to determine how gross changes in historic and future amounts and types of wildlife habitats might affect wildlife species and thence their arrays of KEFs. Results suggest that some wildlife communities have undergone major changes since historic time, particularly with the loss of native shrub steppe, conversion to agriculture, and increase in Eastside mixed conifer forest (Figure IV.B.5) with concomitant changes in associated wildlife species and functions. See previous section for details.
One way to think about integrating management of salmon and wildlife is to determine what wildlife species would benefit from providing habitat for salmon. We asked this question by first listing the habitat elements associated with salmon (Wildlife Methods) and then querying the wildlife database to determine which wildlife species use each of those habitat elements. At least some of the 74 types of wildlife habitat elements are used by various life stages of chinook salmon (Wildlife Methods). A number of wildlife species are also associated with each of these habitat elements. Some examples are shown in Figure IV.C.15. For example, one habitat element related to chinook salmon is “open water in rivers or streams.” Some 107 wildlife species are associated with this habitat element, and 26 of these wildlife species have a strong or recurrent relationship with salmon as feeders on one or more salmon life stages. Many wildlife species are also associated with the salmon habitat elements of open water in lakes and ponds, oxbows, water depth, beaver and muskrat activity, water velocity, pools in rivers, and others.
The results of the analyses to address the influence of fish habitats and fish KECs on wildlife populations include the HCI method where output from the EDT fish analyses served as input to the American black bear HCI analysis (presented above). This resulted in an increase in HCI values for American black bear that occurred in the 75 subwatersheds that would have salmon reintroduced as a result of improving fish runs.
The SHP database suggests that many wildlife species are associated with KECs affecting fish. For example, throughout the Columbia River Basin, 133 wildlife species are influenced by water characteristics, including 16 herps influenced by levels of dissolved oxygen, 66 wildlife species influenced by water depth, 17 species by water temperature, 36 species by water velocity, and so on. Some 203 wildlife species are associated with rivers and streams, including 17 species positively associated with cobble or gravel stream substrates, and 12 species with coarse woody debris in streams or rivers. Also, seven wildlife species associate with stream riffles, and at least some 69 wildlife species are affected by seasonal flooding of open water. Many other such associations are described by the database for freshwater as well as coastal and marine KECs and wildlife species.
It is clear that managing for habitat for fish, including salmon, can positively influence a wide array of wildlife species as well. The SHP databases provide a means by which such wildlife species can be listed for specific wildlife habitats and Basin-wide.
Some 74 categories and subcategores of wildlife KECs are shared between fish and wildlife. It may be of interest to managers to know which KECs these are, in order to know which wildlife species may be influenced (mostly positively) by managing KECs for fish species, and which fish KECs can influence the most number of wildlife species. Further, the SHP database can be used to generate lists of wildlife species associated with each of these KECs or combinations thereof.
Among wildlife species associated with KECs shared with fish, the most number of wildlife species (>100 species) are associated with lakes, ponds, and reservoirs; open water zones of lakes; riverine wetlands; and open water zones of rivers (Figure IV.C.2). This holds for species of wildlife associated with these KECs, as well as those wildlife species that also have a strong or recurrent relationship with salmon (that is, that commonly feed on salmon).
The fish-wildlife interaction Figure IV.C.1 also depicts that at least some populations of fish or wildlife might have some feedback or density-dependent influences. We included density-dependency for the wildlife populations models for American black bear and bald eagle. This was done through estimating the factor “percent key habitat” which uses an HCI method. Percent key habitat, in turn, is one of the variables used to calculate carrying capacity.
For fish, density-dependence was considered as part of the Beverton-Holt formulation in the EDT model. Specifically, density-dependence was considered in the EDT model runs for Chinook. This was done by calculating P/C (production/capacity), which is a density-dependence factor in aggregate population modeling.
Density dependent relations, however, were not used in the functional analysis of fish and wildlife KEFs, because these were categorical relations, not population, demographic, or rate models.
The direct influence of populations of fish on populations of wildlife, or vice versa, were major interactions between fish and wildlife assessed for this report. In part, this is because such interactions are direct, mostly represented by predation or feeding, and have been studied or at least categorized in greater detail than many of the other fish-wildlife interactions discussed here.
The two major direct population interactions we evaluated were the influence of fish populations on wildlife populations, and the influence of wildlife populations on fish populations.
We evaluated the influence of fish populations on wildlife populations by reference to the major report by Cederholm et al. (2000), who explored salmon as prey for wildlife.
According to the SHP database, some 605 species of terrestrial or marine amphibians, reptiles, birds, and mammals currently or historically occur in Washington and Oregon. According to the Cederholm et al. report, of these 605 species, some 137 have a positive feeding relation with salmon. The 137 species include nine wildlife species with a strong consistent relation (the wildlife species is supported by salmon), 59 with a recurrent relation (regular but not necessarily essential use of salmon), 25 with an indirect relation (important but indirect use of salmon, such as feeding on insects occurring on salmon carcasses), and 64 with a rare relation (use salmon but only in a minor diet role). Figure IV.C.3 depicts these associations by each salmon life stage. Some wildlife species have more than one type of relation and may use more than one salmon life stage.
There are 88 wildlife species that have what Cederholm et al. (2000) called a routine relation with salmon (combining strong consistent, recurrent, and indirect relations); these include two amphibian species, one reptile, 60 birds, and 25 mammals (including eight marine mammals). An additional 62 wildlife species have an unknown relation with salmon, and with further study some of these species might exhibit some relation.
Across the salmon life stages and all degrees of use, some 23 wildlife species use the incubation stage, 50 species use the freshwater rearing stage, 64 species use the saltwater stage, 16 species use the spawning stage, and 110 species use the carcass stage. Figure IV.C.4 illustrates the number of strong or recurrent relationships by salmon life stages. At least 41 wildlife species aggregate at salmon congregations (Cederholm et al. 2000).
The wildlife species attracted to the various salmon life stages in turn perform specific key ecological functions (KEFs) or roles in their environment that could affect the presence, distribution, and abundance of environmental factors for, or populations of, other fish and wildlife species (Wildlife Methods). Understanding how salmon influence the broader functional web of the ecosystems in which they reside is an important facet of ecosystem management, particularly in regard to determining how salmon management can affect broader ecosystem functions affecting sustainability, productivity, and biodiversity. To urge managers to think functionally,
Cederholm et al. (2000) suggested the following questions:
· In what way does providing for salmon also provide for a wider array of ecological functions of wildlife species associated with salmon?
· What are those functions?
· How do different kinds of salmon-wildlife relations, and different salmon life stages, provide for an array of ecological functions?
They concluded that salmon provide a causal basis for a wide variety of wildlife species that in turn perform a surprisingly broad array of ecological functions. Those functions cross many types of habitats including, and extending well beyond, the salmon-bearing aquatic systems per se.
Among the many kinds of ecological functions provided by wildlife that are associated with salmon are some that are provided more or less uniquely by each salmon life stage. The ecological wildlife functions that are unique to each salmon life stage are as follows.
· Wildlife that use the incubation stage of salmon include species that are secondary cavity users or that are primary excavators of small ground burrows that are used by other wildlife species.
·
The saltwater rearing stage of
salmon provides uniquely for wildlife that create aerial or aquatic structures
used by other wildlife species.
·
The spawning stage of salmon
provides uniquely for wildlife that are also spermivores (seed-eaters),
grazers, frugivores (fruit-eaters), root-feeders, and bark, cambium or tree
bole feeders; for wildlife that might control other vertebrate populations
through predation, that create feeding opportunities for other wildlife
species, that are primary cavity or large ground-burrow excavators, or
secondary ground runway users; or that can kill standing trees (creating snags)
and fragment standing and down wood (adding to soil organic matter).
·
The carcass stage of salmon
provides uniquely for fungivores (fungi-eaters), for insectivorous wildlife
that might control some insect populations, and for wildlife that serve as
interspecific hosts for avian nest parasites (principally the brown-headed
cowbird).
·
The freshwater rearing stage of
salmon, although providing for many wildlife species and their associated
ecological roles, does not necessarily provide for any unique wildlife KEF
categories.
The patterns of fish-wildlife functional relations suggest that, most or all salmon life stages contribute to providing for the full array of all wildlife ecological functions; no one (or two, or three) salmon life stage provides for all functions. Also note the unique wildlife ecological functions provided by spawning and carcass stages, which may be truncated with purely hatchery-raised fish.
The brief review of Cederholm et al. (2000) asks: in what way does providing for salmon also provide for a wider array of ecological functions of wildlife associated with salmon? The Ecosystem Functional Analyses conducted for the Framework address this question by assessing ecological functional redundancy for wildlife as a result of the three proposed Alternatives that provide for salmon. The functional redundancy analysis is outlined and the results for the Alternatives are presented below. Details of these analyses are available upon request from the Framework office. Functional redundancy was evaluated basin-wide by showing the change in the weighted value of wildlife habitat type from one Alternative to another. Specifically, the amount of wildlife habitat that changed from one Alternative to another was displayed using a matrix that showed the number of wildlife species associated with each Key Ecological Function by wildlife-habitat type. The total amount of change in functional redundancy for each Alternative is mapped in a geographic information system (GIS).
Maps illustrating changes from historic and current conditions were created to assess the amount of change from historic or current conditions by alternative. Historic condition has sometimes been defined as normative condition. Figure IV.C.5 shows the total change (across all KEFs) in functional diversity (number of KEF categories weighted by the number of species performing each KEF) between historic and current conditions. To depict the various alternative’s total change in functional diversity using historic conditions as a baseline, see Figure IV.C.6, Figure IV.C.7, and Figure IV.C.8. Alternatives that have been assessed using current conditions as a baseline can be seen in Figure IV.C.9, Figure IV.C.10, and Figure IV.C.11.
A few selected key ecological functions (KEFS) for wildlife were also evaluated to see how they might be influenced by each set of alternatives. Three KEFs that were chosen were: transportation of viable seeds, spores, plants or animals; primary cavity excavator; and physically affects (improves) soil structure, aeration typically by digging. Because of space, all 51 maps are not presented here, but three maps illustrate the potential of doing such an evaluation (see Figure IV.C.12, Figure IV.C.13, and Figure IV.C.14) that show change in historic to current conditions for each KEF.
Salmon would have the ability to interact with wildlife in areas where there is either an overlap in the use of aquatic KECs or where salmon occur or aggregate. Figure IV.C.15 gives an example of aquatic KECs where overlapping uses may occur. Further, Figure IV.C.16 shows an example of chinook salmon KEFs that potentially can influence wildlife. Of these functions, eating aquatic and terrestrial invertebrates, and carrier and transmitter of vertebrate diseases, may have the greatest potential for demonstrating cause-and-effect relationships regarding how fish can influence wildlife.
Overall, results of this analysis suggest that providing KECs for salmon benefits a wide array of wildlife species as well. Of course, individual wildlife species also use other KECs, but the analysis suggests than there is an economy to be gained by integrating habitat requirements for fish and wildlife.
Further, one can identify which management activities or strategies can affect each habitat element. In this way, one can determine how proposed land management activities under a specific planning alternative, for example, can affect habitat elements and thereby affect both salmon and wildlife associated with those elements. Figure IV.C.17 shows the schematic of how these relationships exist with the different data sets.
One example of this concept is, if Alternative 5 called for a strategy to enhance wildlife habitat by changing the operational aspects of road maintenance and road use, then the SHP database could be queried to determine the array of habitat elements, and thence the wildlife species that use these habitat elements, that could be affected by such a management activity. Results show that 17 habitat elements could be affected by this management activity. Upon further re-evaluation, we could look at two habitat elements that affect both fish and wildlife, such as beaver/muskrat activity and water pollution. Querying the SHP database on these habitat elements, we would find the former habitat element, has 50 wildlife species associated with it that in turn perform 61 KEFs, and the latter habitat element has 21 wildlife species associated with it that in turn perform 35 KEFs. Reviewing each KEF and species would then give a manager an idea of which wildlife species that might be involved and which ecological function(s) might be influenced from performing such a management activity.
Additional influences of fish on wildlife can be characterized by transfer of parasites or disease among species, particularly from fish to amphibians, mammals, and other species.
Fish-amphibian interactions. – Little has been written in regards to fish interacting with amphibians. Hence, personal contacts were made with several wildlife biologists who are currently working with amphibians. Two biologists, Deanne Olson (Forest Service, PNW, Corvallis, OR) and Charlie Crisafulli, (Forest Service, Gifford Pinchot Forest, Vancouver, WA) gave some insight in regards to amphibians potentially affected from hatchery fish via inoculation of several fungus forms. For instance, Olson stated, “Saprolegnia ferax fungus is common in fish hatcheries and it also infects native freshwater fishes (i.e., trout spp). Amphibian eggs, especially those of Bufo species, are especially susceptible to Saprolegnia fungal infections. Having communal oviposition and explosive breeding, an infection has been known to cause complete loss of a year's recruitment at a site.”
The spores of Saprolegnia ferax appear to settle in the substrate at an oviposition site, and quickly infect the eggs oviposited there year after year (the toads often use traditional microsites for oviposition) (Kiesecker and Blaustein 1997). It has been suggested that fish stocking could have increased the incidence of this fungus, but there are no "before" data on fungi. UV-B radiation and Saprolegnia are synergistic in that UV appears to make the eggs more vulnerable to infection (Kiesecker 1997, Kiesecker and Blaustein 1995).
Fish-mammal interactions. – In the Pacific Northwest, the common fluke Nanophyetus salmincola is an intestinal parasite of canids, felids, raccoons, and humans, and is relatively harmless. This fluke, however, can be a vector for the rickettsial organism, which is usually fatal to canines. This fluke is associated with "salmon poisoning" in dogs, although it is a slight misconception to say that salmon poison canids because dogs contract this disease from eating salmon that carry the Nanophyetus larvae. Normally, this fluke lives within the intestines and does not cause any sickness. But when the bacterium Neorickettsia helminthoeca occurs inside the fluke, the fluke can carry a rickettsial organism that causes the salmon poisoning. Symptoms of salmon poisoning include high fever, appetite loss, or depression and are almost always fatal to dogs, foxes, and coyotes (Disease Lab Manual, Univ. of Montana, 1980).
Another effect that fish can have on wildlife is with the
transfer of tapeworms, although most tapeworms infect mostly dogs when they
ingest fleas or non-aquatic animals.
However, in the case of the tapeworm Diphyllobothrium
latum, canids become infected by eating a fish that is infected with larval
tapeworms. Diphyllobothrium adults can grow up to 30 feet in length. Their eggs are released into water through
the feces of an infected dog, fox, mink, or even bear. The eggs are ingested by copepods, which are
eaten by small fish. Diphyllobothrium larvae live within the
muscles of fish and are passed up the food chain from fish to fish until they
are eaten by a mammal, where they mature in the digestive system and lay eggs
that are passed through the feces (American
Animal Hospital Association, Columbia Animal Hospital, Columbia, MD,
2000).
Fish-other species interactions. – As for fish influencing other wildlife, as with birds and reptiles, this interaction primarily pertains to predator-prey relationships. That is, certain fish species are known to be opportunistic and will on occasion prey upon some wildlife species. An example would be northern pike eating a dipper or an aquatic snake. Also, some fish will eat amphibians, their eggs and larvae if an opportunity presents itself.
In some instances, direct predation of wildlife on fish can influence fish populations. This has been the concern for least terns and sea lions feeding on salmon in the mouth of the Columbia River.
This interaction was not explicitly analyzed in this report. It may prove useful, however, to consider at a finer spatial scale of resolution, such as when considering introductions of fish species into systems containing other fish species.
We intended to use output from the American beaver HCI analysis as input to the fish EDT analysis but, as mentioned in the section on Wildlife Methods, this attempt was not possible due to lack of data on beaver habitat at the scale of our analysis. We did create a prototype Bayesian belief network model, however, that illustrates the potential of this approach (Figure IV.C.18).
In this hypothetical example, three management alternatives or strategies are shown influencing habitats for American beaver and other wildlife species that, in turn, provide the KEF of creating aquatic structures such as by damming or building lodges in waterways (other such species can include nutria or muskrat, for example). These wildlife KEFs in turn can modify the values of aquatic KECs important to salmon and other fish. As depicted in Figure IV.C.18, such aquatic KECs can include, for example, the degree of embeddedness (the extent that larger cobbles or gravel are surrounded by or covered by fine sediment), temperature spatial variation (the extent of water temperature variation within the stream reach as influenced by inputs of groundwater), monthly average minimum width of the wetted channel, and daily variation in stream flow level. In this way, wildlife KEFs can be explicitly and quantitatively linked to fish habitats (KECs) and then, by modifying those habitat values in the EDT fish population model, to fish populations. Figure IV.C.18 also illustrates how the value of salmon can be included explicitly in the model, so that the economic or social cost or benefit of the wildlife KEFs on salmon production, and the optimal management decision, can be explicitly determined.
In summary, such an approach can be further developed from this framework to clearly depict alternative management activities, their influence on wildlife (and fish) habitats and KECs, the modifying influence of wildlife KEFs on fish habitats, and the resulting fish population response and associated social values. Further, such a construct can be used to help determine the optimal set of management decisions to maximize salmon value. Through sensitivity analysis, it can also show which factors have the greatest influence on fish, thereby helping prioritize monitoring or management of those factors.