By John McMillan
New Year, new Science Friday! Last week we looked at the concept of carrying capacity, how it is estimated, and the most important habitat factors used to come up with those estimations. This week we shift gears a bit and review studies that illuminate how patterns in fish distribution can affect assumptions about carrying capacity.
Recall that evaluations of the carrying capacity of a given habitat help determine the amount of fish (e.g. wild steelhead) a given habitat can support. This in turn informs scientists and fishery managers — especially those focused on listed or at-risk species — as to whether there could or should be more fish on spawning grounds or whether other actions, such as habitat restoration, need to occur to boost population size.
The overarching assumption underlying carrying capacity is that there is a point with any population where it becomes so abundant that there simply isn’t room for additional fish without depleting the productivity of the population. Basically, that is when density dependence is achieved: there are so many fish competing for limited space that not everyone can survive and grow.
Recent research indicates that just because you may find density dependence in a river it doesn’t necessarily mean the population of fish is using the habitat to full capacity. How can this be?
One reason is that the spatial distribution of spawners can vary. For example, studies by Achord et al. (2008) and Walters et al. (2013) on Chinook salmon in the Snake River revealed strong negative density dependence even when populations were at low levels and in cases where the populations had declined but the freshwater habitat had remained relatively unchanged. Similarly, a study by Will Atlas et al. (2015) found negative density dependence strengthened as abundance of steelhead declined to critically low levels due primarily to poor marine survival (rather than to declines in freshwater habitat quality).
Common among the studies was that the spawning distribution, and hence, distribution of offspring, contracted as the populations declined in size. This resulted in very patchy distribution where many fish aggregated to spawn in particular areas despite the availability of other adequate habitats. Because newly emerged fish are very small and have a hard swim dispersing from the vicinity of the redd, lots of spawning activity – and hence, lots of young-of-the-year fish – in small areas can trigger strong density dependence on the thousands of young fish that emerge (Einum et al. 2008).
Imagine thousands of mouths to feed in a cafeteria the size of tire. Not a lot of opportunity for many fish to grow or survive. The small fry would stand a better chance if they could somehow move to less-used habitats. Alas, steelhead of this age-class are not very mobile and can typically only disperse a few hundred yards from the redd during the first month or two of life. This makes for a really tough life and underscores why dispersing juveniles more continuously can result in better juvenile growth and survival in less used habitats.
It appears that density dependence can still occur when population levels are low and there is available habitat to use. This is a dilemma for steelhead managers because it runs counter to the traditional assumption that when populations reach density dependence they are essentially at carrying capacity, and that any further growth in the population would require extensive restoration of additional habitat. Resource managers rely heavily on habitat capacity models to generate stock-recruit curves and implement harvest strategies. The problem is, models that do not account for the spatial distribution of spawning fish can underestimate spawning targets (Finstad et al. 2014: http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2012-0455) and, as a result, managers may adopt harvest levels that suppress a population’s ability to take advantage of under-utilized habitat and become more productive.
There are ways to begin exploring the management implications for these studies. When run sizes of salmon and steelhead are smaller the fish tend to spawn in fewer places and aggregate into patches. Conversely, when run sizes are more abundant the fish are forced into less favorable and less utilized habitat, expanding their distribution and making it less patchy. This means that reducing harvest and increasing escapement is one way to test the findings of the recent studies in other populations. Another way is to incorporate the spatial structure of adults into stock-recruit and habitat capacity models.
The bottom line is these recent studies suggest that the carrying capacity of any fishery cannot be estimated solely based on how much habitat is available. The spatial distribution of adults and juveniles can have important effects on density dependence and establishing spawner goals and subsequent harvest levels. Thus, we at Wild Steelheaders United are working hard to educate anglers about these types of effects and are investing heavily in the generation of models that account for spatial distribution of redds.
Making progress in wild salmon and steelhead recovery is never easy, but such work is critical if we are to adaptively manage steelhead and sustain fisheries over the long-term. We must be more flexible and nimble in management of our precious wild steelhead, and emphasize strategies and tactics that allow fish to better take advantage of a habitat’s capacity — even if it means letting go of long-held assumptions.