models with cost effectiveness
In reality, capacity (b) is a function of both quality and quantity of habitat
the specific adaptations of salmon to climate change are uncertain, but maintaining diversity (life history and genetic) will likely increase resilience @Battin2007
habitat restoration important part of "offsetting effects of climate change" for salmon @Battin2007
"Viable salmon populations (VSP) are defined by four important metrics: abundance, productivity, spatial structure, and diversity (McElhany et al. 2000)."
Shiraz model is similar, the primary difference is that we simply one aspect, modelling life-stages separately, to focus on the important aspects for our research questions. We aren't focused on the role of affecting the vital rates at various life-stages but on the environment-response relationship and habitat capacity. Also, our model uses a Ricker instead of a Beverton-Holt @Scheuerell2013
our model therefore focuses on the 3 key components of salmon performance productivity, capacity, and life-history diversity @Mobrand1997
"the extinction of a salmon population can represent an irreversible loss of genetic diversity" and therefore, identifying local adaptation is of great importance @Mobrand1997
key reference life-history diversity dampens extinction risk with environmental fluctuations @denBoer1968
key reference @Taylor1991: local adaptation of salmonids is evident on broad scales (100s of kms apart) and locally (between pops that are a < a few km apart); likely quite important for persistence and should be maintained; important to study
General rule for straying from @Schtickzelle2007: straying should be sufficient to avoid extinction or bring back subpops from low abundance, but unlikely to affect general population dynamics or synchronize pops
metapopulation concept has important implications for salmon but is usually ignored (word only mentioned in 0.25% of papers!) @Schtickzelle2007
importance of metapopulations for salmon been known for decades - see (Ricker's 1972) review: @Schtickzelle2007
``For an ESU, the importance of dispersal typically arises, however, at longer-time scales (evolutionary time) allowing gene flow across the entire unit.'' @Schtickzelle2007
``The term ‘metapopulation’ was coined more than three decades ago by Levins, who defined it as a population of populations which go extinct locally and recolonize (Levins 1969, 1970), ''
From the relatively narrow Levins concept, i.e. independent and identical populations, our present view of metapopulations has broadened (Harrison 1991, 1994; Hanski and Gilpin 1997; Harrison and Taylor 1997): ‘any assemblage of discrete local populations with migration among them is considered to be a metapopulation, regardless of the rate of population turnover’ (Hanski and Gilpin 1997 p. 2). `` @Schtickzelle2007
``Peterman et al. (1998) found correlation coefficients below 0.75 for survival rates of sockeye salmon at the regional or larger scale '' @Schtickzelle2007
``This is confirmed by other studies, both at the regional scale: approximately )0.50 to 1.00 for distances up to 175 km in the Kvichak River system (Stewart et al. 2003a)'' @Schtickzelle2007
``Dispersal among populations seems to be too limited (see below) to play a role in synchronizing populations, except in situations when abundance decreases to low levels (Isaak et al. 2003) or perhaps for certain types of habitats, e.g. beaches (Stewart et al. 2003b).'' @Schtickzelle2007
``Nevertheless, heterogeneity in habitat features and life history traits, collectively termed ‘biocomplexity’ (Hilborn et al. 2003), may induce a different response of the populations to the same cause (Kindvall 1996).'' @Schtickzelle2007
``p.305: This interaction with biocomplexity is probably also responsible for the fact that environmental conditions explain a relatively small proportion of the variability in salmon survival rates (Mueter et al. 2005) -- Highlighted 2013-03-02'' @Schtickzelle2007
``Generally, both shared environmental conditions and dispersal are assumed a priori to be more likely to happen for populations close to each other; for many species correlation effectively decreases with the distance between populations (Liebhold et al. 2004).'' @Schtickzelle2007
``p.305: Individuals from different populations of the same region, even very distant populations, meet in the same area during the time they spend at sea or are subject to processes that are well correlated over large spatial scales (Quinn 2005 and references therein). There, they encounter similar conditions affecting their survival, e.g. coastal conditions experienced by juvenile salmons and influenced by the Pacific Decadal Oscillation (Mantua et al. 1997; Mueter et al. 2005). -- Highlighted 2013-03-02'' @Schtickzelle2007
``temperature and precipitation, might affect populations during their freshwater life his- tory stages over large areas within years. '' @Schtickzelle2007
``Indeed, populations close to each other experience similar freshwater conditions, but all populations in a certain region experience similar, although certainly not identical, marine conditions. '' @Schtickzelle2007
ESUs: interbreeding and straying shouldn't substantially affect population dynamics or extinction risk over a 100-year time period @McElhany2000 (also key VSP reference)
Important to integrate uncertainty into ecosystem-based models - one way to to this is through sensitivity analyses across a range of possible values (we do something a bit simpler here, looking at high and low possible values) @McElhany2010
Main reference that straying occurs: Quinn 1993 Quinn, T.P. (1993) A review of homing and straying of wild and hatchery-produced salmon. Fisheries Research 18, 29–44.
``p.306: The fraction of strayers, or dispersers, even if quite low in general, seems largely sufficient to ensure (re)colonization of suitable habitat. -- Highlighted 2013-03-04'' @Schtickzelle2007
@Schtickzelle2007 ``numerous examples of rapid natural recolonizations by salmonids have been observed in several species, e.g. after glacial recession in southeast Alaska (Quinn 1993; Milner et al. 2000) or after some natural or artificial barrier is removed (Bryant et al. 1999; Anderson and Quinn 2007). Even if a small fraction of strays seems at first glance incompatible with such a high power of (re)colonization, it is not.''
``p.306: Nevertheless, immigrants are probably seldom numerous enough to affect population dynamics in the target population, and especially to synchronize dynamics of source and target populations. -- Highlighted 2013-03-04'' @Schtickzelle2007
@Schtickzelle2007 ``p.307: On a more routine basis, differences in the quality of the spawning and rearing habitat greatly influence the number of recruits per spawner, i.e. the population growth rate, as well as density of spawners. Consequently, models with source and sink populations (Cooper and Mangel 1999) might be quite appropriate in some areas (Hindar et al. 2004 -- Highlighted 2013-03-04''
@Schtickzelle2007 ``In regions still close to their pristine state, like Bristol Bay, Alaska, the habitat supports many populations of sockeye salmon with thousands of spawning adults. Fisheries remove a large number and proportion of individuals, commonly 50–70\% or more in recent years (Clark et al. 2006),''
@Schtickzelle2007 p.309: ``Third, it is important to remember that correlation of local dynamics may be due to similar environmental conditions, to dispersal, or more likely to a combination or both. Methods that combine different types of information to partition the roles of these two processes in creating synchrony between populations are needed. -- Highlighted 2013-03-04''
@Schtickzelle2007 p.309: Even more important, straying should not be presented merely as a negative process leading to the loss of fish.
example of ecological surprise or black swan for salmon in nature: ``extreme natural conditions such as the 1980 eruption of Mt St Helens (Leider 1989).u'' Leider, S.A. (1989) Increased straying by adult steelhead trout, Salmo gairdneri, following the 1980 eruption of Mount St. Helens. Environmental Biology of Fishes 24, 219–229.
``p.305: populations farther away, experiencing different freshwater and marine conditions, are less correlated or even negatively correlated if climate-driven processes such as upwelling create favourable conditions in part of the species’ range and adverse conditions elsewhere (Mantua et al. 1997; Mueter et al. 2005). -- Highlighted 2013-03-02'' @Schtickzelle2007
``p.305: On the contrary, in anadromous species all fish start their return to spawn from the sea. Dispersal is therefore not really influenced by physical barriers: all populations are accessible; otherwise they would rapidly go extinct.'' @Schtickzelle2007
@Mueter2002 use residuals from B-H S-R relationship as an index of survival, as did @Peterman1998
@Mueter2002 in general looked at decay of correlation between environmental variables and survival for pacific salmon
@Mueter2002 In particular, regional averages of summer SST may be useful
predictors in models of survival rates or recruitment of Pacific salmon''
future studies of salmon recruitment or survival should focus on regional
environmental variability rather than large- scale climate indicators.''
``Stock-recruitment relationships usually explain lit- tle of the variation in survival rates, which suggests that environmental processes are important (Peterman 1987).'' (in @Peterman1998)
@Peterman1998 `` p.2515: Our results suggest that the shared environmental causes of variation in survival rates of sockeye salmon operate mainly on regional spatial scales (i.e., within Bristol Bay stocks and within Fraser River stocks). -- Highlighted 2013-03-03''
@Peterman1998 ``p.2515: The limited evidence available suggests that these sources of environmental variation arise during early marine life (and to some extent in fresh water in the Bristol Bay stocks) -- Highlighted 2013-03-03''
``Evidence for autocorrelated residuals for the spawner- to-recruit relation in equations (1) and (2) is particularly strong for northeastern Pacific Ocean sockeye salmon populations (Korman et al. 1995; Peterman et al. 1998) but is weak for pink salmon (Pyper et al. 2001).'' @Peterman2009
SST important in Ricker S-R models of pacific salmon pops - @Peterman2009 more important than getting any error structure right, also multistock fits better than single stock fits
@Peterman2009 - 15 pops, 100 years, p.141: The five models that we explored were: (1) a standard Ricker stock–recruitment model (equation (1), (2) a Ricker model but with an autocorrelated lag-1 (AR(1)) error term (equations (1) and (4)), (3) a Ricker model that assumed that the ai parameter in equation (1) could vary with time (ai,t) and that was fit using a Kalman filter (Peterman et al. 2000), (4) the multi-stock mixed-effects model (equation (6)) used by Mueter et al. (2002a), and (5) the version of the multi-stock equation (6) used by Su et al. (2004) that allowed for a distance-based structure to the ai parameters across stocks. -- Highlighted 2013-03-04
@Peterman2009 ``In the most realistic environmental scenarios, which assumed an AR(1) climate process and step functions in mean productivity like that seen in the mid-1970s in the North Pacific Ocean,''
From @Collie2012 SOM: ``Sea-surface temperature is not likely a direct physiological limiting factor on survival rate, but rather is more likely an indirect surrogate for oceanographic conditions that reflect predator abundance and/or food supply for chum salmon. Recent warmer conditions in the Bering Sea have led to earlier ice retreat and a later bloom with a large copepod biomass (Macklin and Hunt 2004). Thus, warmer conditions may enhance feeding, growth, and survival of chum salmon stocks in the AYK region. These correlations are consistent with the hypothesis that chum salmon productivity is primarily determined by ocean survival, as opposed to freshwater survival (Kruse 1998).''
@Collie2012 ``There is considerable empirical evidence that productivity of salmon populations is influenced by variation in environmental (especially oceanographic) conditions at both high-frequency, interannual scales (Mueter et al. 2002) and at low-frequency, decadal scales (Beamish 1995; Mantua et al. 1997; Francis et al. 1998). Therefore, to generate spawner-to-recruit dynamics in our simulations, we used a standard Ricker model that was modified to have a time-varying a parameter to reflect that decadal-scale environmental variability in addition to the usual high-frequency variability:''
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