Publications
Publications & Presentations
Submitted Papers • Published Papers
Video Lectures
Re-interpreting the Fisheries Crisis
In Press
Minte-Vera, C.V., R. Hilborn. Bayesian hierarchical meta-analysis of density-dependent body growth in haddock (Melanogrammus aeglefinus). Can. J. Fish. Aquat. Sci.
Abstract
The evidence for changes in somatic growth related to population density was investigated for eleven stocks of haddock using Bayesian hierarchic meta-analysis. A within-stock growth model that includes density-dependence in the growth increment of ages 2 and older was used. The posterior distribution for the hyper-mean of the density-dependence parameter indicated overall evidence of negative density-dependence, owever, there was considerable heterogeneity among stocks. Five stocks had negative density-dependence (Georges Bank, Eastern Scotian Shelf, North East Artic, West of Scotland and Iceland), three stocks had positive density-dependence (Bay of Fundy/Scotian Shelf, North Sea/Skagerrak and West of Scotland), one stock had density-dependence around zero (Faroes), the remainders had little information about density-dependent on their data (Irish Sea and Celtic Sea/West of Ireland) and thus their estimate was closer to the prediction from the hierarchical model for an unobserved stock, which includes the information for all the stocks.
In Review
Scheuerell, M.D., R. Hilborn. Estimating the freshwater component of essential fish habitat for Pacific salmon (Oncorhynchus spp.) with the Shiraz model.
Abstract
The 1996 Sustainable Fisheries Act contained provisions that all federal fisheries management plans should contain some description of essential fish habitat (EFH). While much emphasis has been placed on estimating EFH for marine stocks, very little attention has been paid to doing so for Pacific salmon, in part due to their complex life history strategies. An earlier assessment of EFH for Pacific salmon across the west coast of the United State focused on the freshwater component of EFH due to limited knowledge about marine distributions. That analysis concluded that a more in-depth examination of how freshwater habitat affects the various life stages, at much smaller spatial scales than previously considered, was indeed necessary. Here we used a detailed life history model for Pacific salmon to estimate the freshwater component of EFH for two populations of Chinook salmon listed as threatened under the Endangered Species Act within a large watershed draining into Puget Sound, Washington, U.S.A. By accounting for proposed harvest rates, hatchery practices, and habitat structure, we were able to identify 23 of 60 subbasins that were essential fish habitat for insuring that there would be no significant decline in the total number of spawners relative to the current average escapement. Our analytical framework could be easily applied to other populations or species of salmon to aid in developing recovery and management plans.
Hilborn, R. Life history models for salmon management: the challenges.
Abstract
Salmon have complex life histories that have been extensively studied, particularly in freshwater, yet most salmon management relies on models that ignore much of salmon life history. For instance, calculation of optimal escapement for most Pacific salmon stocks summarizes their entire life history into a single relationship between spawners and subsequent recruits. Similarly, most analyses of salmon habitat have used models that fail to integrate the complex life history of salmon and have often considered only a single “limiting factor”. Computational methods and models are now being used to incorporate life history and habitat information directly into evaluations of both harvesting and habitat management policies. Challenges and opportunities in using life history models include (1) the need for better dynamic understanding of how habitat affects survival, (2) turning current “expert system” analysis into statistical estimation, (3) application of life history models to hatchery/wild interaction, (4) quantifying essential fish habitat using life history models and (5) use of such models to explore salmon/ocean interactions.
Magnusson, A., R. Hilborn. Information about fish stock abundance: Data, models, and assumptions.
Abstract
Informative data in fisheries stock assessment are those that lead to accurate estimates of abundance and reference points. In practice, the accuracy of estimated abundance is unknown and it’s often unclear which features of the data make them informative or uninformative. Neither is it obvious which model assumptions will improve estimation performance, given a particular dataset. In this simulation study, 10 hypotheses are addressed using multiple scenarios, estimation models, and reference points. The simulated data scenarios all share the same biological and fleet characteristics, but vary in terms of the fishing history. The estimation models are based on a common statistical catch-at-age framework, but estimate different parameters and have different parts of the data available to them. Among the findings is that a “one-way trip” scenario, where harvest rate gradually increases while abundance decreases, proved no less informative than a contrasted catch history. Models that excluded either abundance index or catch at age performed surprisingly well, compared to models that included both data types. Natural mortality rate, M, was estimated with some reliability when age composition data were available from before major catches were removed. Stock-recruitment steepness, h, was estimated with some reliability when abundance index or age composition data were available from years of very low abundance. Understanding what makes fisheries data informative or uninformative enables scientists to identify fisheries for which stock assessment models are likely to be biased or imprecise. Managers can also benefit from guidelines on how to distribute funding and manpower among different data collection programmes to gather the most information.
Hilborn, R., C. Minte-Vera. Fisheries induced changes in growth rates in marine fisheries: are they significant?
Abstract
Fishing provides selective pressure on many fisheries life history traits, and there has long been an interest in the impact of size selective fishing on the evolution of growth rates. Recent studies, both laboratory and empirical, suggest that such size selective fishing may be significant. Using a meta analysis of 73 commercially fished stocks we show that declines in mass-at-age are slightly more common than increases, but there is no relationship between the intensity of fishing and the change in growth rate. We review a number of size selectivity patterns in major commercial fisheries and show that the intensity of selection and the size selectivity are both considerably less than used in laboratory experiments. We simulate the evolutionary impact of fishing on growth and show that given the actual selectivity patterns found in most commercial fisheries little evolutionary impact in growth rates is expected. The model shows the best way to reduce evolutionary impacts is to lower exploitation rates. We suggest that for fisheries where there is very intense size specific selection, managers would be advised to use a model such as ours to evaluate potential evolutionary impacts.
Lessard, R.B., R. Hilborn, B. Chasco. Beyond brood tables: life-history models of sockeye salmon (Oncorynchus nerka) populations.
Abstract
We compare two methods of analyzing stock recruitment relationships. Our primary concern is to develop a new method to establish harvest goals for sockeye salmon populations in Bristol Bay Alaska. We model the life history of a fish population from a spawning stage, through juvenile and adult stages, and ending with adults that return to spawn. We specifically model a Bristol Bay sockeye population composed of age-classes coming from 1 or 2 years of lake rearing and 2 or 3 years of ocean residency. We initially place density dependence in the egg to fry stage. We fit the model to spawner and recruit data with each adult age class represented and compare the results of fitting the model with and without smolt composition data. Parameters are estimated by maximizing a likelihood objective function. Posterior estimates of parameters from MCMC simulations are then used to assess optimal harvest policies. We search for policies that produce the highest average yield under the assumption that estimated parameters reflect the best estimate of the ”state-of-nature” of the system. We found that it is possible to detect density dependence with a life history model where analysis of Beverton-Holt stock recruitment relationship fails to do so. We find that Beverton-Holt relationships produce policies and long term yield estimates that are inconsistent with empirical trends. Conversely, we find that harvest rates and maximum sustained yield estimates using the life history model estimate are consistent with the historical behavior of fisheries examined.
PDFs
Please contact rayh@u.washington.edu to obtain PDF copies. Links to PDFs (Acrobat Reader required) of various Hilborn publications will be provided when possible.
Citations
Books and Monographs
Hilborn, R. 2012. Overfishing: What Everyone Needs to Know. Oxford University Press. 150 p.
Punt, A, R Hilborn. 2002. Bayesian stock assessment methods in fisheries. FAO Computerized Information Series (Fisheries) No. 12. 56 p.
Hilborn, R, M Mangel. 1997. The Ecological Detective: confronting models with data. Princeton University Press, Princeton, N.J. 315 pps.
Punt, AE, R Hilborn. 1996. Biomass dynamics models. FAO Computerized Information Series (Fisheries). No. 10. Rome, FAO. 62p.
Hilborn, R, CJ. Walters. 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty. Chapman and Hall, New York. 570 p. Also available in Russian.
Bazykin, A, P Bunnell, WC Clark, GC Gallopin, J Gross, R Hilborn, CS Holling, DD Jones, RM Peterman, JE Rabinovich, JH Steele, CJ Walters. 1978. Adaptive Environmental Assessment and Management. John Wiley and Sons, New York. 375 pp.
Refereed Journals
Costello, C, D Ovando, R Hilborn, SD Gaines, O Deschenes, SE Lester. 2012. Status and Solutions for the World’s Unassessed Fisheries. Science Early Online. doi:10.1126/science.1223389.
Buhle, ER, Feist, BE, and Hilborn, R. 2012. Population dynamics and control of invasive Spartina alterniflora: inference and forecasting under uncertainty. Ecol. Appl. 22:880-893.
Hilborn, R. 2012. The evolution of quantitative marine fisheries management 1985-2010. Natural Resource Modeling. 25:122-144.
Hilborn, R, Stewart, IJ, Branch, TA, and Jensen, OP. 2012. Defining trade-offs among Conservation of species diversity abundances, profitability, and food security in the California Current bottom-trawl fishery. Cons. Biol. 26:257-266.
Jensen, OP, Branch, TA, Hilborn, R. 2012. Marine fisheries as ecological experiments. Theoret. Ecol. 5:3-22.
Pess, G R, Hilborn, R, Kloehn, K, Quinn, T P. 2012. The influence of population dynamics and environmental conditions on pink salmon re-colonization after barrier removal. Can. J. Fish. Aquat. Sci. 69:970-982.
Sethi, SA, Dalton, M, Hilborn, R. 2012. Quantitative risk measures applied to Alaskan commercial fisheries. Can. J. Fish. Aquat. Sci. 69:487-498.
Banobi, JA, Branch, TA, Hilborn, R. 2011. Do rebuttals affect future science? Ecosphere. 2:1-11.
Branch, TA, Jensen, OP, Ricard, D, Ye, Y, Hilborn, R. 2011. Contrasting global trends in marine fishery status obtained from catches and from stock assessments. Cons. Biol. doi:10.1111/j.1523-1739.2011.01687.x.
Chauvenet, ALM, Durant, SM., Hilborn, R., and Pettorelli, N. 2011. Unintended consequences of conservation actions: managing disease in complex ecosystems. PLOS One. 6:e28671. doi:10.1371/journal.pone.0028671.
Cowan, JH, Grimes, CB, Patterson, WF, Walters, CJ, Jones, AC, Lindberg, WJ, Sheehy, DJ, Pine, WE, Powers, JE, Campbell, MD, Lindeman, KC, Diamond, SL, Hilborn, R, Gibson, HT, Rose, KA. 2011. Red snapper management in the Gulf of Mexico: science- or faith-based? Rev. Fish Biol. Fish. 21:187-204.
Durant, SM, Craft, ME, Hilborn, R, Bashir, S, Hando, J, Thomas, L. 2011. Long-term trends in carnivore abundance using distance sampling in Serengeti National Park, Tanzania. J. Appl. Ecol. doi:10.1111/j.1365-2664.2011.02042.x.
Grafton, QR, Kompas, T, Che, TN, Chu, L, Hilborn, R. 2011. BMEY as a fisheries management target. Fish and Fisheries doi:10.1111/j.1467-2979.2011.00444.x.
Gutiérrez, N. L., S. R. Valencia, T. A. Branch, D. J. Agnew, J. K. Baum, P. L. Bianchi, J. Cornejo-Donoso, C. Costello, O. Defeo, T. E. Essington, R. Hilborn, D. D. Hoggarth, A. E. Larsen, C. Ninnes, K. Sainsbury, R. L. Selden, S. Sistla, A. D. M. Smith, A. Stern-Pirlot, S. J. Teck, J. T. Thorson, and N. E. Williams. 2012. Eco-label conveys reliable information on fish stock health to seafood consumers. PLoS ONE 7(8):e43765. doi: 10.1371/journal.pone.0043765.
Gutierrez, NL, Hilborn, R, Defeo, O. 2011. Leadership, social capital and incentives promote successful fisheries. Nature 470:386-389.
Hauser, L, Baird, M, Hilborn, R, Seeb, LW, Seeb, JE. 2011. An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population. Molec. Ecol. Resourc. 11(Suppl. 1):150-161.
Hilborn, R. 2011. Future directions in ecosystem based fisheries management: A personal perspective. Fisheries Research 108: 235-239.
Hilborn, R, Stewart, IJ, Branch, TA, Jensen, AP. 2011. Defining trade-offs among conservation, profitability, and food security in the California Current bottom-trawl fishery. Cons. Biol. 26(2):257-266. doi:10.1111/j.1523-1739.2011.01800.x.
Krkošek, M, Conners, BM, Ford, H, Peacock, S, Mages, P, Ford, JS, Morton, A, Volpe, JP, Hilborn, R, Dill, L M, Lewis, MA. 2011. Fish farms, parasites, and predators: implications for salmon population dynamics. Ecol. Applic. 21:897-914.
Krkošek, M, Connors, BM, Morton, A, Lewis, MA, Dill, LM, Hilborn, R. Effects of parasites from salmon farms on productivity of wild salmon. Proc. Nat. Acad. Sci. 108:14700-14704.
Krkošek, M, Hilborn, R. 2011. Sea lice (Lepeophtheirus salmonis) infestations and the productivity of pink salmon (Oncorhynchus gorbuscha) in the Broughton Archipelago, British Columbia, Canada. Can. J. Fish. Aquat. Sci. 68:17-29.
Krkošek, M, R Hilborn, RM Peterman, TP Quinn. 2011. Cycles, stochasticity and density dependence in pink salmon population dynamics. Proc. R. Soc. B 278:2060-2068. DOI: 10.1098/rspb.2010.2335.
Complex dynamics of animal populations often involve deterministic and stochastic components. A fascinating example is the variation in magnitude of 2-year cycles in abundances of pink salmon (Oncorhynchus gorbuscha) stocks along the North Pacific rim. Pink salmon have a 2-year anadromous and semelparous life cycle, resulting in odd- and even-year lineages that occupy the same habitats but are reproductively isolated in time. One lineage is often much more abundant than the other in a given river, and there are phase switches in dominance between odd- and even-year lines. In some regions, the weak line is absent and in others both lines are abundant. Our analysis of 33 stocks indicates that these patterns probably result from stochastic perturbations of damped oscillations owing to density-dependent mortality caused by interactions between lineages. Possible mechanisms are cannibalism, disease transmission, food depletion and habitat degradation by which one lineage affects the other, although no mechanism has been well-studied. Our results provide comprehensive empirical estimates of lagged density-dependent mortality in salmon populations and suggest that a combination of stochasticity and density dependence drives cyclical dynamics of pink salmon stocks.
Lin, JE, R Hilborn, TP Quinn, L Hauser. 2011. Self-sustaining populations, population sinks or aggregates of strays: chum (Oncorhynchus keta) and Chinook salmon (Oncorhynchus tshawytscha) in the Wood River system, Alaska. Molec. Ecol. 20:4925-4937. doi:10.1111/j.1365-294X.2011.05334.x.
McGilliard, CR, Hilborn, R, MacCall, A, Punt, AE, Field, JC. 2011. Can information from marine protected areas be used to inform control-rule based management of small-scale, data-poor stocks? ICES J. Mar. Sci. 68:201-211.
McGilliard, CR, AE Punt, R Hilborn. 2011. Spatial structure induced by marine reserves shapes population responses to catastrophes in mathematical models. Ecol. Applic. 21(4):1399-1409. DOI: 10.1890/10-0001.1.
Catastrophic events such as oil spills, hypoxia, disease, and major predation events occur in marine ecosystems and affect fish populations. Previous evaluations of the performance of spatial management alternatives have not considered catastrophic events. We investigate the effects of local and global catastrophic events on populations managed with and without no-take marine reserves and with fishing mortality rates that are optimized accounting for reserves. A spatial population dynamics model is used to explore effects of large, catastrophic natural mortality events. The effects of the spatial spread, magnitude, probability of catastrophe, and persistence of a catastrophic event through time are explored. Catastrophic events affecting large spatial areas and those that persist through time have the greatest effects on population dynamics because they affect natural mortality nonlinearly, whereas the probability and magnitude of catastrophic events result in only linear increases in natural mortality. The probability of falling below 10% or 20% of unfished abundance was greatest when a no-take marine reserve was implemented with no additional fishing regulations and least when a no-take marine reserve was implemented in addition to the maintenance of optimal fishing mortality in fished areas. In the absence of implementation error, maintaining abundance across space using restrictions on fishing mortality rates, regardless of the existence of a no-take marine reserve, decreased the probability of falling below 10% or 20% of unfished abundance.
Branch, TA, R Hilborn. 2010. A general model for reconstructing salmon runs. Can. J. Fish. Aquat. Sci. 67:886-904. DOI: 10.1139/F10-032.
A general model is developed for salmon run reconstruction based on catch, escapement, and age composition data. The model is based on ‘‘groups’’ of salmon, each of which share the same characteristics but can differ from other groups in run timing, abundance, gear selectivity, and migration routes. The model is highly flexible so that it can be adapted to a variety of fisheries and can compare the fits of alternative hypotheses to available data. The model is applied to three sockeye salmon (Oncorhynchus nerka) districts in Bristol Bay, Alaska, USA, to show the effect of allowing age classes to arrive at different times and the impact of including process errors to mimic day-to-day arrival variability. The model predicts that in 2005, Wood River salmon comprised only 54% of the catch in the Nushagak fishing district (but 71% of the escapement), although these predictions are contradicted by genetic data for 2006–2008 showing high harvest rates of Wood River and Nushagak River fish but only light harvest rates of Igushik River fish. The genetics highlight theimportance of including stock-specific availability parameters in future versions of the model to account for differences in harvest rates among stocks caught in the same fishing district.
Courtenay, WR, BB Collette, TE Essington, R Hilborn, JW Orr, D Pauly, JE Randall, WFS Vaniz. 2010. North Atlantic fisheries: a response to criticism of the proactive proposal reply. Fisheries. 35: 298-298.
Cowan, JHJ, CB Grimes, WFI Patterson, CJ Walters, AC Jones, WJ Lindberg, DJ Sheehy, WEI Pine, JE Powers, MD Campbell, KC Lindeman, SL Diamond, R Hilborn, HT Gibson, KA Rose. 2010. Red snapper management in the Gulf of Mexico: science- or faith-based. Rev. Fish boil. Fish. Online. DOI 10.1007/s11160-010-9165-7.
Dobson, A, M Borner, ARE Sinclair, 24 others including R Hilborn. 2010. Road will ruin Serengeti. Nature 467:272-273.
Doctor, KK., R Hilborn, T Quinn. 2010. Spatial and temporal patterns of upriver migration by sockeye salmon populations in the Wood River system, Bristol Bay, Alaska. Trans. Am. Fish. Soc. 139:80-91.
Goñi, R, R Hilborn, D Díaz, S Mallol, S Adlerstein. 2010. Net contribution of spillover from a marine reserve to fishery catches. Mar. Ecol. Progr. Ser. 400:233-243.
Grafton, RQ, T Kompas, R Hilborn. 2010. Limits to the privatization of fishery resources: comment. Land Economics 86:609-613.
Gutiérrez, NL, R Hilborn, O Defeo. 2011. Leadership, social capital and incentives promote successful fisheries. Nature (online). DOI: 10.1038/nature09689.
Harwell, MA, JH Gentile, KW Cummins, RC Highsmith, R Hilborn, CP McRoy, J Parrish, T Weingartner. 2010. A conceptual model of natural and anthropogenic drivers and their influence on the Prince William Sound, Alaska, ecosystem. Human Ecol. Risk Assess. 16:672-726.
Hilborn, R. 2010. Pretty Good Yield and exploited fishes. Mar. Pol. 34:193-196
Hilborn, R, JH Cowan. 2010. Marine stewardship: high bar for seafood. Nature 467:531-531.
Hilborn, R, K Stokes. 2010. Defining overfished stocks: have we lost the plot? Fisheries 35:113-120.
Holdo, RM, KA Galvin, E Knapp, S Polasky, R Hilborn, RD Holt. 2010. Responses to alternative rainfall regimes and antipoaching in a migratory system. Ecol. Applic. 20:381-397.
McGilliard, CR, R Hilborn, A MacCall, AE Punt, JC Field. 2010. Can information from marine protected areas be used to inform control-rule-based management of small-scale, data-poor stocks? ICES J. Mar. Sci. 68(1):201-211. DOI: 10.1093/icesjms/fsq151.
Many small-scale, nearshore fisheries lack the historical catch and survey information needed for conventional stock-assessment-based management. The potential use of the ratio of the density of fish outside a marine protected area to that inside it each year (the density ratio, DR) in a control rule is evaluated to determine the direction and magnitude of change in fishing effort in the next year. Management strategy evaluation was used to evaluate the performance of this DR control rule (DRCR) for a range of movement rates of larvae and adults and other biological scenarios, and the parameters of the control rule that maximized cumulative catch (over 95 years) for each scenario were found. The cumulative catch under the optimal DRCR was 90% of the cumulative catch from an optimal constant effort rule (CER). A small range of parameter values for the DRCR produced 75% or more of the cumulative catch produced from optimal CERs for a variety of assumptions about biology and initial stock status. The optimal DRCR was most sensitive to the movement patterns of larvae and adults and survey variability.
Metzger, KL, ARE Sinclair, R Hilborn, JGC Hopcraft, AR Mduma Simon. 2010. Evaluating the protection of wildlife in parks: the case of African buffalo in Serengeti. Biodivers. Cons. 19:3431-3444.
Schindler, DE, R Hilborn, B Chasco, CP Boatright, TP Quinn, LA Rogers, MS Webster. 2010. Population diversity and the portfolio effect in an exploited species. Nature 465:609-613.
One of the most pervasive themes in ecology is that biological diversity stabilizes ecosystem processes and the services they provide to society, a concept that has become a common argument for biodiversity conservation. Species-rich communities are thought to produce more temporally stable ecosystem services because of the complementary or independent dynamics among species that performsimilar ecosystemfunctions. Such variance dampeningwithin communities is referred to as a portfolio effect and is analogous to the effects of asset diversity on the stability of financial portfolios8. In ecology, these arguments have focused on the effects of species diversity on ecosystem stability but have not considered the importance of biologically relevant diversity within individual species. Current rates of population extirpation are probably at least three orders ofmagnitudehigher thanspecies extinction rates10, so there is a pressing need to clarify how population and life history diversity affect the performance of individual species in providing important ecosystem services. Here we use five decades of data from Oncorhynchus nerka (sockeye salmon) in Bristol Bay, Alaska, to provide the first quantification of portfolio effects that derive from population and life history diversity in an important and heavily exploited species. Variability in annualBristol Bay salmon returns is 2.2 times lower than it would be if the system consisted of a single homogenous population rather than the several hundred discrete populations it currently consists of. Furthermore, if it were a single homogeneous population, such increased variability would lead to ten times more frequent fisheries closures. Portfolio effects are also evident in watershed food webs, where they stabilize and extend predator access to salmon resources. Our results demonstrate the critical importance of maintaining population diversity for stabilizing ecosystem services and securing the economies and livelihoods that depend on them. The reliability of ecosystem services will erode faster than indicated by species loss alone.
Westley, PAH, DE Schindler, TP Quinn, GT Ruggerone, R Hilborn. 2010. Natural habitat change, commercial fishing, climate, and dispersal interact to restructure an Alaskan fish metacommunity. Oecologia 163:471-484.
Mantua, NJ, NG Taylor, GT Ruggerone, KW Myers, D Preikshot, X Augerot, ND Davis, B Dorner, R Hilborn, RM Peterman, P Rand, D Schindler, J Stanford, RV Walker, CJ Walters. 2009. The salmon MALBEC Project: a North Pacific-scale study to support salmon conservation planning. N. Pac. Anadr. Fish Comm. Bull. 5: 333-354. (Available at http://www.npafc.org.)
The Model for Assessing Links Between Ecosystems (MALBEC) is a policy gaming tool with potential to explore the impacts of climate change, harvest policies, hatchery policies, and freshwater habitat capacity changes on salmon at the North Pacific scale. This article provides background information on the MALBEC project, methods, input data, and preliminary results pertaining to (1) hatchery versus wild salmon production in the North Pacific Ocean, (2) rearing, movement, and interactions among Pacific salmon populations in marine environments, (3) marine carrying capacities, density-dependent growth, and survival in Pacific salmon stocks, and (4) climate impacts on productivity in salmon habitat domains across the North Pacific. The basic modeling strategy underlying MALBEC follows the full life cycle of salmon and allows for density-dependence at multiple life stages, and it includes spatially explicit ecosystem considerations for both freshwater and marine habitat. The model is supported by a data base including annual run sizes, catches, spawning escapements, and hatchery releases for 146 regional stock groups of hatchery and wild pink, chum, and sockeye salmon around the North Pacific for the period 1952–2006. For this historical period, various hypotheses about density-dependent interactions in the marine environment are evaluated based on the goodness of fit between simulated and observed annual run-sizes. Based on the information we used to inform our ocean migration table, interactions among stocks that originate from geographically distant regions are greatest in the Bering Sea in summer–fall and in the eastern sub-Arctic in winter–spring. While the model does not reproduce the observed data for some specific stock groups, it does predict the same overall production pattern that was observed by reconstructing run sizes with catch and escapement data alone. Our preliminary results indicate that simulations that include density-dependent interactions in the ocean yield better fits to the observed run-size data than those simulations without density-dependent interactions in the ocean. This suggests that for any level of ocean productivity, the ocean will only support a certain biomass of fish but that this biomass could consist of different combinations of stocks, stock numbers and individual fish sizes. MALBEC simulations illustrate this point by showing that under scenarios of Pacific-wide reduced hatchery production, the total number of wild Alaskan chum salmon increases, and that such increases are large where density-dependent effects on survival are large and small where they are not. Under scenarios with reduced freshwater carrying capacities for wild stocks, the impacts of density-dependent interactions also lead to relative increases in ocean survival and growth rates for stocks using ocean habitats where density-dependence is large.
Courtenay, WR, Jr., BB Collette, TE Essington, R Hilborn, JW Orr, D Pauly, JE Randall, WF Smith-Vaniz. 2009. Risks of introductions of marine fishes: reply to Briggs. Fisheries 34:181-186.
This is a rebuttal to a publication by John C. Briggs in the April 2008 issue of Fisheries in which he suggested introducing fishes and invertebrates from the North Pacific into the North Atlantic to increase diversity toward improving fisheries in the latter. We argue otherwise for reasons that Briggs downplayed or never considered. Using examples of introductions within the Pacific and the Atlantic, and movements of species from the Pacific to the Atlantic, we provide a record of failures and damage or dangers to native species from the few introductions that became successful. We argue that a lack of diversity of fishes and invertebrates in the North Atlantic versus that of the North Pacific is not the problem to be corrected by introductions as Briggs suggested. A record of overfishing and management policies is the problem in the North Atlantic. Introductions from the North Pacific to the North Atlantic are not worth the costs or the environmental risks involved.
Doctor, KK, R Hilborn, M Rowse, T Quinn. 2009. Spatial temporal patterns of upriver migration by sockeye salmon populations in the Wood River System, Bristol Bay, Alaska. Trans. Am. Fish. Soc. 139:80-91.
Knowledge of temporal segregation in migration timing among populations is critical for management of fisheries that exploit a complex of populations with an overlap in timing. We examined the potential for fishery selection on populations of sockeye salmon Oncorhynchus nerka in the Wood River system, Bristol Bay, Alaska, by determining the relationship between migration timing (hence, vulnerability to fishing) and the population of origin and breeding date. We assessed migration patterns among populations with a multiyear mark–recapture study testing the hypotheses that the timing of upriver migration varies systematically with respect to spawning habitat, lake of origin, and spawning population. The results revealed organization in migration timing through the Wood River among populations spawning in the streams, beaches, and rivers of the system. The primary source of variation in migration timing among populations was spawning habitat and, to a lesser extent, the lake of origin. Stream-spawning populations migrated before river-spawning populations, consistent with the earlier spawning in streams than in rivers. However, beachspawning populations were among the earliest to migrate, yet they spawned as late as river spawners. A likelihood model revealed that spawn timing was not tightly coupled with migration timing by populations through the Wood River, and there was broad overlap in migration timing among spawning populations. Results also revealed a link between migration timing and arrival on spawning grounds within a population that was intensively sampled, indicating that early upriver migrants also tended to enter the spawning grounds before later-migrating individuals. Fisheries that are selective with respect to timing can have strong effects on the phenotypic and genotypic diversity of the populations under such pressure, and the phenomenon of temporally biased fisheries merits further investigation.
Hilborn, R. 2009. Pretty Good Yield and exploited fishes. Marine Policy, doi:10.1016/ j.marpol.2009.04.013.
While much of traditional fisheries theory has concentrated on maximum or optimum yield, the reality of fisheries management is that biomass yield is only one of the several indicators of fisheries performance, and desired outcomes generally only need to provide something near the maximum possible yield. A range of policies are explored to find those that produce ‘‘Pretty Good Yield’’ defined as sustainable yield at least 80% of the maximum sustainable yield. Such yields are generally obtained over a broad range of stock sizes (20–50% of unfished stock abundance), and this range is not sensitive to the population’s basic life history parameters such as natural mortality rate, somatic growth rate, or age at maturity. The most important biological parameter determining this range is the intensity of recruitment compensation. Meta-analysis shows compensation is usually strong and there is reasonably little yield lost at what are now widely accepted definitions of overfishing or risk for most stocks. Similarly, maintaining stocks at 50% of unfished stock abundance for ecological or economic reasons results in little expected loss of yield.
Hilborn, R, E Litsinger. 2009. Cause of decline and potential for recovery of Atlantic cod populations. The Open Fish Science Journal 2:32-38.
The large declines in abundance and failure to recover in many Atlantic cod populations has been the subject of numerous papers and the continued low abundance of several Canadian cod populations has become an icon for failed fisheries management. It has been argued that many stocks failed to recover after declines, despite reduced fishing pressure. A range of complex mechanisms have been invoked to explain failure to recover, including decreased age-atmaturity, vulnerability to by-catch, fishing induced evolution, depensatory predation and habitat change caused by fishing gear. We show that, for all North East Atlantic cod populations, continued high fishing pressure is sufficient to explain the failure of stocks to recover and the stocks would increase at 40-60% per year in the absence of fishing. This is also true for four out of nine North American cod stocks. The other five North American stocks, located in the Gulf of St Lawrence and around the Grand Banks and Labrador, show no net productivity (would not increase in the absence of fishing) since the late 1980s or early 1990s. Four of the Canadian stocks show a rapid shift in the mid 1980s, from being highly productive to low or negative net productivity, despite having been at relative high abundance. We conclude that for most Atlantic cod stocks (13 out of 18) no mechanism other than excessive fishing is required to explain their failure to recover. Fishing pressure cannot lead to the sudden decrease in productivity in the four Canadian stocks which flipped from high to low productivity; environmental change seems the likely cause, although continued fishing drove these stocks to very low abundance and likely impaired their ability to recover.
Honea, JM, JC Jorgensen, MM McClure, MM, TD Cooney, K Engie, D Holzer, R Hilborn, R. 2009 Evaluating habitat effects on population status: influence of habitat restoration on spring-run Chinook salmon. Freshwat. Biol. DOI:10.1111/j.1365-2427.2009.02208.x.
Schroeter SC, NL Gutiérrez, M Robinson, R Hilborn, P Halmay. 2009. Moving from data poor to data rich: a case study of community-based data collection for the San Diego red sea urchin (Strongylocentrotus franciscanus) fishery. Mar. Coast. Fish. 1:230–243.
Responding to the need for management of California’s nearshore fisheries mandated in state law by the Marine Life Management and Marine Life Protection acts, the San Diego Watermen’s Association (SDWA), which includes divers that target local red sea urchins Strongylocentrotus franciscanus, initiated a community-based data collection program in 2001. In collaboration with independent scientists and biologists from the California Department of Fish and Game, the SDWA developed an ongoing program to gather, organize, and analyze both fishery-dependent and fishery-independent data on the local red sea urchin fishery. The goal of the program is to collect data that will support periodical stock assessments needed for sustainable management of existing nearshore fisheries (including red sea urchins) as well as the kelp forest ecosystem on which these fisheries depend. Here, we discuss sampling designs, methods for determining data quality (bias and precision), and methods for detecting change, and we provide some examples of results from the ongoing community-based data collection program. We also report on (1) the design and implementation of scientifically valid sampling protocols; (2) data quality assurance and control collaboratively conducted with scientists and resource agency biologists; (3) calibration studies to determine accuracy and precision and the magnitude of detectable changes in red sea urchin populations; and (4) visualization and dissemination of data and results and incremental changes in protocols that would facilitate the monitoring of associated biological communities. Finally, we discuss keys for success in this cooperative-based data collection program and its implications for stock assessment and management of the red sea urchin fishery in California.
Worm, B, R Hilborn, JK Baum, TA Branch, JS Collie, C Costello, MJ Fogarty, EA Fulton, JA Hutchings, S Jennings, OP Jensen, HK Lotze, PM Mace, TR McClanahan, C Minto, SR Palumbi, AM Parma, D Ricard, AA Rosenberg, R Watson, D Zeller. 2009. Rebuilding global fisheries. Science 325:578-585.
After a long history of overexploitation, increasing efforts to restore marine ecosystems and rebuild fisheries are under way. Here, we analyze current trends from a fisheries and conservation perspective. In 5 of 10 well-studied ecosystems, the average exploitation rate has recently declined and is now at or below the rate predicted to achieve maximum sustainable yield for seven systems. Yet 63% of assessed fish stocks worldwide still require rebuilding, and even lower exploitation rates are needed to reverse the collapse of vulnerable species. Combined fisheries and conservation objectives can be achieved by merging diverse management actions, including catch restrictions, gear modification, and closed areas, depending on local context. Impacts of international fleets and the lack of alternatives to fishing complicate prospects for rebuilding fisheries in many poorer regions, highlighting the need for a global perspective on rebuilding marine resources.
Bue, BG, R Hilborn, MR Link. 2008. Optimal harvesting considering biological and economic objectives. Can. J. Fish. Aquat. Sci. 65:691-700.
Most examinations of optimal harvesting policies have considered only biological objectives, yet it is increasingly recognized that a primary objective of many fisheries is economic profitability. Using Bayesian risk analysis, we compare policies that combine fisheries harvesting, the revenue brought in by fish sales, the cost of harvesting and processing, and processing and fishing capacity to find policies that maximize biological yield and economic profit to the processing and harvesting sectors, for a major Pacific salmon (Oncorhynchus spp.) fishery in Bristol Bay, Alaska. We show that while average catch is maximized by a fixed escapement policy, total revenue is maximized by a policy that includes some harvesting at stock sizes below that required to produce maximum average catch. In addition, there is a wide range of policies that provide 90% of the maximum for any of the biological and economic objectives considered and economic profitability is enhanced by limitations on processing and harvesting capacity.
Costello, C, N Burger, KA Galvin, R Hilborn, R, S Polasky. 2008. Dynamic consequences of human behavior in the Serengeti ecosystem. Pages 301-324 in ARE Sinclair, C Packer, SAR Mduma, J Fryxell (eds), Serengeti III. Human impacts on Ecosystem Dynamics. University of Chicago press, Chicago.
Fryxell, J, P Abrams, R Holt, J Wilmshurst, ARE Sinclair, R Hilborn. 2008. Spatial dynamics and coexistence of the Serengeti grazer community. Pages 277-300 in ARE Sinclair, C Packer, SAR Mduma, J Fryxell (eds), Serengeti III. Human impacts on Ecosystem Dynamics. University of Chicago Press, Chicago.
Grafton, RQ, R Hilborn, L Ridgeway, D Squires, M Williams, S Garcia, T Groves, J Joseph, K Kelleher, T Kompas, G Libecap, CG Lundin, M Makino, T Matthiasson, R McLoughlin, A Parma, G San Martin, B Satia, C-C Schmidt, M Tait, LX Zhang. 2008. Positioning fisheries in a changing world. Mar. Pol. 32:630-634.
Marine capture fisheries face major and complex challenges: habitat degradation, poor economic returns, social hardships from depleted stocks, illegal fishing, and climate change, among others. The key factors that prevent the transition to sustainable fisheries are information failures, transition costs, use and non-use conflicts and capacity constraints. Using the experiences of fisheries successes and failures it is argued only through better governance and institutional change that encompasses the public good of the oceans (biodiversity, ecosystem integrity, sustainability) and societal values (existence, aesthetic and amenity) will fisheries be made sustainable.
Gunderson, DR, AM Parma, R Hilborn, JM Cope, DL Fluharty, ML Miller, RD Vetter, SS Heppell, HG Greene. 2008. The challenge of managing nearshore rocky reef resources. Fisheries 33(4):172-179.
Nearshore temperate reefs are highly diverse and productive habitats that provide structure and shelter for a wide variety of fishes and invertebrates. Recreational and commercial fisheries depend on nearshore reefs, which also provide opportunities for non-extractive recreational activities such as diving. Many inhabitants of nearshore temperate reefs on the west coast of North America have very limited home ranges as adults, and recent genetic evidence indicates that the dispersion of the larval stages is often restricted to tens of kilometers. Management of temperate reef resources must be organized on very small spatial scales in order to be effective, offering unique technical challenges in terms of assessment and monitoring. New enabling legislation could assist in specifying mandates and adjusting institutional design to allow stakeholders and concerned citizens to formulate management policies at local levels, and to aid in implementing and enforcing these policies.
Hard, JJ, MR Gross, M Heino, R Hilborn, RG Kope, R Law, JD Reynolds. 2008. Evolutionary consequences of fishing and their implications for salmon. Evol. Applic. 1:388-408. DOI: 10.1111/j.1752-4571.2008.00020.x
We review the evidence for fisheries-induced evolution in anadromous salmonids. Salmon are exposed to a variety of fishing gears and intensities as immature or maturing individuals. We evaluate the evidence that fishing is causing evolutionary changes to traits including body size, migration timing and age of maturation, and we discuss the implications for fisheries and conservation. Few studies have fully evaluated the ingredients of fisheries-induced evolution: selection intensity, genetic variability, correlation among traits under selection, and response to selection. Most studies are limited in their ability to separate genetic responses from phenotypic plasticity, and environmental change complicates interpretation. However, strong evidence for selection intensity and for genetic variability in salmon fitness traits indicates that fishing can cause detectable evolution within ten or fewer generations. Evolutionary issues are therefore meaningful considerations in salmon fishery management. Evolutionary biologists have rarely been involved in the development of salmon fishing policy, yet evolutionary biology is relevant to the long-term success of fisheries. Future management might consider fishing policy to (i) allow experimental testing of evolutionary responses to exploitation and (ii) improve the long-term sustainability of the fishery by mitigating unfavorable evolutionary responses to fishing. We provide suggestions for how this might be done.
Hilborn, R. 2008. Knowledge on how to achieve sustainable fisheries. Pages 45-56 in K Tsukamoto, T Kawamura, T Takeuchi, TD Beard, Jr, MJ Kaiser (eds), Fisheries for Global Welfare and Environment, 5th World Fisheries Congress 2008.
I review the state of current knowledge with respect to the requirements for achieving sustainable fisheries. I consider the range of objectives for fisheries and identify conflicting objectives as a major issue in achieving sustainability. Next I review historical and current practice in allocation of fish resources and regulation of harvest and highlight existing knowledge. Evidence suggests that both restriction of access and maintenance of biological productivity are necessary conditions to achieve biological, economic and social sustainability. However, the tools appropriate to achieve these differ greatly across fisheries and societies, and for both elements of fisheries management localsolutions are needed in most cases. Attempts to impose standardized solutions to either issue frequently result in ineffective solutions. Evidence also suggests that involvement of consumptive users through appropriate incentives is an essential element in achieving sustainability.
Hilborn, R, CV Minte-Vera. 2008. Fisheries-induced changes in growth rates in marine fisheries: are they significant? Bull. Mar. Sci. 83(1):95-105.
Fishing provides selective pressure on many fisheries life-history traits, and interest in the impact of size-selective fishing on the evolution of growth rates is long standing. Recent studies, both laboratory and empirical, suggest that such size-selective fishing is significant. Using a metaanalysis of 73 commercially fished stocks, we found that declines in mass at age are slightly more common than increases, but no relationship was apparent between the intensity of fishing and the change in growth rate. We reviewed a number of size-selectivity patterns in major commercial fisheries and found that the intensity of selection and the size selectivity were both considerably less than are used in laboratory experiments. We simulated the evolutionary impact of fishing on growth and found that, given the actual selectivity patterns found in most commercial fisheries, little evolutionary impact on growth rates is expected. The model showed that the best way to reduce evolutionary impacts is to lower exploitation rates. We suggest that, for fisheries where size-specific selection is very intense, managers should use a model such as ours to evaluate potential evolutionary impacts.
Hilborn, R, ARE Sinclair, J Fryxell. 2008. Propagation of change through a complex ecosystem. Pages 417-442 in ARE Sinclair, C Packer, SAR Mduma, J Fryxell (eds), Serengeti III. Human impacts on Ecosystem Dynamics. University of Chicago Press, Chicago.
Lessard RB, R Hilborn, BE Chasco. 2008. Escapement goal analysis and stock reconstruction of sockeye salmon populations (Oncorhynchus nerka) using life-history models. Can. J. Fish. Aquat. Sci. 65(10):2269–2278. Available online.
We compare life-history models with the Beverton–Holt approach of escapement goal analysis. We model the life history of a sockeye salmon (Onchorhynchus nerka) population from a spawning stage, through juvenile and adult stages, and ending with adults that return to spawn. We fit models to data by statistically comparing predicted and observed numbers of four dominant adult ages. Posterior estimates of parameters from Markov chain Monte Carlo simulations are then used to assess optimal harvest policies. We search for policies that produce the highest average yield. We find that it is possible to detect density dependence with a life-history model where analysis of Beverton–Holt stock–recruitment relationship fails to do so. We find that Beverton–Holt relationships produce policies and long-term yield estimates that are inconsistent with empirical trends. Conversely, we find that optimal spawning stock sizes and maximum sustained yield estimates using the life-history model estimate are consistent with the historical behavior of fisheries examined. Adding smolt data to the analysis does not substantially change predicted optimal spawning stock size, but decreases the variance in estimated posterior parameter distributions and policy variable distributions.
Lin, J, TP Quinn, R Hilborn, L Hauser. 2008. Fine-scale differentiation between sockeye salmon ecotypes and the effect of phenotype on straying. Heredity 101:341-350.
A long-standing goal of evolutionary biology is to understand the factors that drive population divergence and speciation, and conspecific ecotypes are considered an intermediate step towards speciation. Competing hypotheses for differentiation among salmonid ecotypes include geographic separation, accurate homing, and selection against introgression. Here, we used genetic and phenotypic data from geographically proximate populations of beach and stream ecotypes of sockeye salmon (Oncorhynchus nerka) in Little Togiak Lake, Alaska, to examine the relationship between ecological and genetic differentiation. Both genetic and phenotypic differentiation was high and significant between beach and creek samples in all years. Within ecotypes, beach spawners showed lower differentiation (FST =0.007) and higher genetic variability (HE=0.789) than stream spawners (FST=0.038, HE =0.730). Fish genetically identified as strays differed phenotypically from their resident conspecifics: males collected in a creek but genetically assigned to the beach population had shallower body depths (similar to native creek fish) than males assigned to and sampled on beaches, and males genetically assigned to creeks but collected on a beach were deeper-bodied than males genetically assigned to and sampled in the creeks. Thus the fish that strayed tended to resemble the morphology of the fish in the population that they joined.
Martell, S.J.D., C.J. Walters, and R. Hilborn. 2008. Retrospective analysis of harvest management performance for Bristol Bay and Fraser River sockeye salmon (Oncorhynchus nerka). Can. J. Fish. Aquat. Sci. 65:409-424.
Given current knowledge of mean stock-recruitment relationships and past recruitment anomalies due to environmental factors, and absent constraints on exploitation rates due to mixed stock harvesting, yield of sockeye salmon in Bristol Bay Alaska and Fraser River B.C. might have been at least 100% larger since 1950 than was actually achieved, and possibly as much as 300% larger depending on responses of a few large stocks for which the optimum stock size remains highly uncertain. Most of these gains would have been due to knowledge of optimum mean spawning stock size rather than specific recruitment anomalies; knowing all future recruitment anomalies at the time of each spawning stock choice would have likely only added 2-5% to total catches. For some stocks, delayed density dependence (cyclic dominance) might have resulted in somewhat lower yields, but under optimal management would still have been higher than were achieved. Even given only estimates of optimum spawning stock size each year based on data available as of that year, but following fixed escapement harvest policy rules, managers could likely have achieved 30-40% higher total yield. Key management experiments for the future will involve testing for cyclic dominance effects on two major stocks (Kvichak, Late Shuswap), to determine whether stocks with strong delayed density dependent survival effects should be deliberately managed through fallow rotation strategies for juvenile nursery lakes.
de Mutsert, K, JH Cowan, Jr, TE Essington, R Hilborn. 2008. Reanalyses of Gulf of Mexico fisheries data: Landings can be misleading in assessments of fisheries and fisheries ecosystems. PNAS 105(7):2740-2744.
We used two high profile articles as cases to demonstrate that use of fishery landings data can lead to faulty interpretations about the condition of fishery ecosystems. One case uses the mean trophic level index and its changes, and the other uses estimates of fishery collapses. In earlier analyses by other authors, marine ecosystems in the Gulf of Mexico (GOM) and U.S. Atlantic Ocean south of Chesapeake Bay were deemed to be severely overfished and the food webs badly deteriorated using these criteria. In our reanalyses, the low mean trophic level index for the GOM actually resulted from large catches of two groups of low trophic level species, menhaden and shrimp, and the mean trophic level was slowly increasing rather than decreasing. Commercial targeting and high landings of shrimps and menhaden, especially in the GOM, drove the index as previously calculated. Reanalyses of fishery collapses incorporating criteria that included targeting, variability in fishing effort, and market forces discovered many false cases of collapse based simply upon a decline of catches to 10% of previous maximum levels. Consequently, we suggest that the low mean trophic level index calculated in the earlier article for the GOM did not reflect the overall condition of the fishery ecosystem, and that the 10% rule for collapse should not be interpreted out of context in the GOM or elsewhere. In both cases, problems lay in the assumption that commercial landings data alone adequately reflect the fish populations and communities.
McGilliard, CR, R Hilborn. 2008. Modeling no-take marine reserves in regulated fisheries: assessing the role of larval dispersal. Can. J. Fish. Aquat. Sci. 65:2509-2523.
We explored the effects of larval dispersal distance on the impact of no-take marine reserves (NTMRs) implemented in fisheries with catch regulations. NTMRs exist in many fisheries with harvest regulated by annual catch limits. In these fisheries, catch is taken from outside NTMRs, potentially resulting in reduced abundance outside NTMRs and an overall reduction in catch. We used a spatial model with two life stages (larvae and adults) to evaluate the effects of larval dispersal distance for fisheries managed by a total allowable catch (TAC) and an NTMR. We examined effects of the timing of density-dependent mortality in relation to larval movement. Abundance reached similar values for populations with long and short larval dispersal distances. Catch declined substantially for stocks with short larval dispersal distances. When larval dispersal distances were long, catch declined to values below maximum sustainable yield (MSY), but stabilized. Catch per unit effort (CPUE) declined to 9% of CPUE at MSY for stocks with short distance larval dispersal after the implementation of an NTMR; with long distance larval dispersal, CPUE declined to approximately 50% or less of the CPUE at MSY. The CPUE did not reflect trends in abundance after the implementation of an NTMR.
Sethi, S.A., and R. Hilborn. 2008. Interactions between poaching and management policy affect marine reserves as conservation tools. Biol. Cons. 141:506-516.
This analysis uses a simple age-structured reserve model with Black rockfish biology to explore the effects of poaching within reserve boundaries under three different management policies based on yield maximization or reproductive thresholds. Departures from the traditional assumptions of full compliance to reserve boundaries alter the conclusions of prior modeling work that demonstrate yield equivalence to no-reserve effort control management and augmented reproductive benefits when small reserves are implemented. By degrading the recruitment subsidization effect to nonreserve areas from protected reserve populations, poaching resulted in negative externalities for compliant fishermen in open areas in terms of yield and degraded the reproductive output and age-structure of the system. All three policies required effort reduction in open areas as a response to poaching in reserves. The strength of the impacts from poaching varied with policy choice and harvest intensity in the reserve, where at the highest level of poaching modeled here (15% annual exploitation rate of the vulnerable reserve population) biological and fishery benefits of implementing reserves were totally negated. Under the assumptions of this model, a policy managing for a reproductive threshold that excludes the reserve population is the precautionary choice if poaching is likely. The results of this exercise emphasize the importance of garnering compliance to reserve boundaries from resource-users for spatial closures to be successful ocean management tools.
Valero, JL, B Lee, D Armstrong, L Orensanz, A Parma, R Hilborn, B Sizemore, T Palzer. 2008. Population dynamics and historic trends of geoduck clams under episodic low dissolve oxygen conditions in Hood Canal. J. Shellf. Res. 27:462-463.
Walters, CJ, R Hilborn, V Christensen. 2008. Surplus production dynamics in declining and recovering fish populations. Can. J. Fish. Aquat. Sci. 65:2536-2551.
Surplus production rates predicted by simple biomass dynamics models are generally expected to follow a simple dome-shaped pattern as population size changes and to show similar trajectories during population decline and recovery. Age-structured models, however, predict substantially lower surplus production rates during population recovery than during decline because of reduced mean fecundity, unless recruitment compensation is very strong. Ecosystem models like Ecosim predict more complex patterns, with reduced production during recoveries due to both age-structure effects and cultivation–depensation effects related to changes in competitor and predator abundances. Production-driven recoveries, where surplus production per biomass is higher during recovery than decline, are predicted in cases where there has been substantial change in overall ecosystem productivity or community structure. 110 case examples illustrate that simple, repeatable relationships between stock size and production are uncommon, and the most common pattern is production-driven change in stock size, where changes in production rate apparently independent of stock size then drive stock increase or decrease. We conclude that nonstationarity in productivity needs to be considered as part of population rebuilding and that empirical estimates of surplus production may provide insight in this process.
Westley, PAH, R Hilborn, TP Quinn, GT Ruggerone, DE Schindler. 2008. Long-term changes in rearing habitat and downstream movement by juvenile sockeye salmon (Oncorhynchus nerka) in an interconnected Alaska lake system. Ecol. Freshwat. Fish. 17:443–454.
In some populations the phenomenon of partial migration develops where some individuals stay in a given habitat rather than move with the migratory component. Depending on the selective pressures, the individuals that stay may be larger, smaller or similar in size to those that move. Freshwater movements of juvenile sockeye salmon (Oncorhynchus nerka Walbaum) fry vary among and within populations, and can be complex, especially in interconnected lake systems. We examined variation of movement patterns by a sockeye salmon population in an interconnected lake system during a period of rapid natural habitat change and found that fry migrating downstream were shorter, had lower body condition, and were more likely ill and moribund compared with fish remaining in the lake. However, otolith microstructure measurements indicated that emigrants did not grow significantly slower than residents prior to downstream movement. We show that patterns (i.e., demography of migrants, timing of movement) of downstream movement have changed since the 1970s, corresponding to changes in rearing habitat. Our findings parallel the results with other salmonid species and are generally consistent with the paradigm that density-dependent interactions from declining habitat availability or quality result in the downstream movement of competitively inferior individuals, although the mechanisms governing downstream migration are unclear in this system
Carlson, S.M., R. Hilborn, A.P. Hendry, and T.P. Quinn. 2007. Predation by bears drives senescence in natural populations of salmon. PLoS One 2(12):ed1286. doi:10.1371/journal.pone.0001286.
Classic evolutionary theory predicts that populations experiencing higher rates of environmentally caused (“extrinsic”) mortality should senesce more rapidly, but this theory usually neglects plausible relationships between an individual's senescent condition and its susceptibility to extrinsic mortality. We tested for the evolutionary importance of this condition dependence by comparing senescence rates among natural populations of sockeye salmon (Oncorhynchus nerka) subject to varying degrees of predation by brown bears (Ursus arctos). We related senescence rates in six populations to (1) the overall rate of extrinsic mortality, and (2) the degree of condition dependence in this mortality. Senescence rates were determined by modeling the mortality of individually-tagged breeding salmon at each site. The overall rate of extrinsic mortality was estimated as the long-term average of the annual percentage of salmon killed by bears. The degree of condition dependence was estimated as the extent to which bears killed salmon that exhibited varying degrees of senescence. We found that the degree of condition dependence in extrinsic mortality was very important in driving senescence: populations where bears selectively killed fish showing advanced senescence were those that senesced least rapidly. The overall rate of extrinsic mortality also contributed to among-population variation in senescence-but to a lesser extent. Condition-dependent susceptibility to extrinsic mortality should be incorporated more often into theoretical models and should be explicitly tested in natural populations.
Chasco, B., R. Hilborn, and A.E. Punt. 2007. Run reconstruction of mixed-stock salmon fisheries using age-composition data. Can. J. Fish. Aquat. Sci. 64:1479-1490.
A method for using age composition data to determine stock-specific migration timing and abundance in a mixed-stock salmon fishery is developed. The Chignik sockeye fishery has two stocks, but only aggregate catch and escapement data are available. The age composition of the two stocks, however, is known to be consistently different, and age composition data are collected from one stock at the beginning of the commercial fishing season and from the commercial catch throughout the season. Using the changes in age composition in the commercial catch throughout the season we estimate the total abundance and migration timing for the two Chignik stocks using maximum likelihood and Bayesian analyses. The accuracy of this stock separation model was highly correlated with that of scale pattern analysis for most years from 1978 to 2002 (r=0.89). The results suggest that age-composition may provide salmon managers with a reliable and inexpensive method for determining stock-specific migration timing and abundance in a mixed-stock fishery.
Grafton, R.Q., T. Kompas, and R.W. Hilborn. 2007. Economics of overexploitation revisited. Science 318:1601.
Hilborn, R. 2007. Biodiversity loss in the oceans: how bad is it? Science 316:1281-1282.
Hilborn, R. 2007. Defining success in fisheries and conflicts in objectives. Marine Policy 31:153-158.
Hilborn, R. 2007. Faith, evolution, and the burden of proof—the author responds. Fisheries 32:91-93.
Hilborn, R. 2007. Managing fisheries is managing people: what has been learned? Fish and Fisheries 8:285–296.
Understanding the behaviour of fishermen is a key ingredient to successful fisheries management. The aggregate behaviour of fishing fleets can be predicted and managed with appropriate incentives. To determine appropriate incentives, we should look to successes to learn what works and what does not. In different fisheries incentive systems have been found to reduce the race-for-fish and make fisheries profitable, to stimulate stock rebuilding, to reduce bycatch, and to provide for reductions in illegal fishing. Yet, success can be evaluated in many dimensions, but is, in fact, rarely done – per cent overfished seems to be the dominant measure of performance. I evaluate the yield lost due to overfishing in several ecosystems and contrast the situation of North Atlantic cod where considerable yield is lost, to fisheries in New Zealand and the west coast of the USA where lost yield due to overfishing is very small. Much more systematic evaluation of the other aspects of fisheries performance is greatly needed. From examples explored in this paper I conclude that prevention of overfishing can be achieved with strong central governments enforcing conservative catch regulations, but economic success appears to require an appropriate incentive structure.
Hilborn, R. 2007. Moving to sustainability by learning from successful fisheries. Ambio 36(4):296-303.
There are two diverging views of the status and future of the world’s fisheries. One group represented largely by academic marine ecologists sees almost universal failure of fisheries management and calls for the use of marineprotected areas as the central tool of a new approach to rebuilding the marine ecosystems of the world. The scientists working in fisheries agencies and many academic scientists see a more complex picture, with many failed fisheries but also numerous successes. This group argues that we need to apply the lessons from the successful fisheries to stop the decline and rebuild those fisheries threatened by excess fishing. These lessons are stopping the competitive race to fish by appropriate incentives for fishing fleets and good governance. The major tool of resetting incentives is granting various forms of dedicated access, including community-based fishing rights, allocation to cooperatives, and individual fishing quotas. Many of the failed fisheries of the world occur in jurisdictions where central governments are not functional, and local control of fisheries is an essential part of the solution.
Hilborn, R. 2007. Reinterpreting the state of fisheries and their management. Ecosystems. DOI: 10.1007/s10021-007-9100-5.
Hilborn, R. 2007. Review: Return to the River: Restoring Salmon to the Columbia River, RN Williams (ed). 2006. Elsevier Academic Press, Amsterdam. Restoration Ecology 15(4):747–748.
Hilborn, R, G Hopcraft, P Arcese. 2007. Wildlife population increases in Serengeti National Park—response. Science 315:1790-1791.
Magnusson, A., R. Hilborn. 2007. What makes fisheries data informative? Fish and Fisheries 8:337-358.
Informative data in fisheries stock assessment are those that lead to accurate estimates of abundance and reference points. In practice, the accuracy of estimated abundance is unknown and it is often unclear which features of the data make them informative or uninformative. Neither is it obvious which model assumptions will improve estimation performance, given a particular data set. In this simulation study, 10 hypotheses are addressed using multiple scenarios, estimation models, and reference points. The simulated data scenarios all share the same biological and fleet characteristics, but vary in terms of the fishing history. The estimation models are based on a common statistical catch-at-age framework, but estimate different parameters and have different parts of the data available to them. Among the findings is that a ‘one-way trip’ scenario, where harvest rate gradually increases while abundance decreases, proved no less informative than a contrasted catch history. Models that excluded either abundance index or catch at age performed surprisingly well, compared to models that included both data types. Natural mortality rate, M, was estimated with some reliability when age-composition data were available from before major catches were removed. Stock-recruitment steepness, h, was estimated with some reliability when abundance-index or age-composition data were available from years of very low abundance. Understanding what makes fisheries data informative or uninformative enables scientists to identify fisheries for which stock assessment models are likely to be biased or imprecise. Managers can also benefit from guidelines on how to distribute funding and manpower among different data collection programmes to gather the most information.
Metzger, KL, ARE Sinclair, KLI Campbell, R Hilborn, JGC Hopcraft, SAR Mduma, RM Reich. 2007. Using historical data to establish baselines for conservation: The black rhinoceros (Diceros bicornis) of the Serengeti as a case study. Biol. Cons. 139:358-374.
Using historical animal counts, human population censuses and arrest records we determined the potential contemporary distribution of the black rhino in the Serengeti National Park. Prior to extensive poaching of the black rhino in the Serengeti (1977-78), 31 monthly reconnaissance surveys (1969-72) were made over the ecosystem, recording the number and location of animals. Using these data, we determined a reliable historical population estimate for the black rhino. We also developed a habitat suitability model of the black rhino in the Serengeti National Park using the spatial location of historical count data and contemporary vegetation and landscape variables. However because illegal hunting still remains a significant threat to the persistence of the rhino, we also determined areas where the likelihood of encountering people is high. From this analysis, we determined possible locations within the park for reintroduction of the black rhino under current conditions.
Naish, KA, JE Taylor, PS Levin, TP Quinn, JR Winton, D Huppert, R Hilborn. 2007. An evaluation of the effects of conservation and fishery enhancement hatcheries on wild populations of salmon. Advanc. Mar. Biol. 53:61-194. doi:10.1016/S0065-2881(07)53002-6.
The historical, political and scientific aspects of salmon hatchery programmes designed to enhance fishery production or to sustain or recover endangered populations are reviewed. Recognizing that the establishment of hatcheries is a political response to societal demands for harvest and conservation, we critically examine the levels of activity, the biological risks, and the economic analysis associated with salmon hatchery programmes within this social context. However, a rigorous analysis of the impacts of hatchery programmes was hindered by the lack of standardized data on release sizes and survival rates at all ecological scales, and since hatchery programme objectives are rarely defined, it was also difficult to measure their effectiveness at meeting release objectives. We examined in detail the genetic and competitive outcomes, and the risks of disease transmission of releasing hatchery fish on wild populations, and the effects of harvesting mixed stocks comprising both groups. Debates on the genetic effects of hatchery programmes are dominated by whether correct management practices can reduce negative outcomes, but there is an absence of programmatic research approaches addressing this important question. The outcome of competition between hatchery and wild fish is complex and fishery enhancement programmes should seek to reduce interactions between hatchery and wild fish at all ecological scales during their life history; but these issues are rarely studied and thus are not typically considered. Recently, managers have recognized that fishing effort on salmon released from fishery enhancement hatcheries likely impacts vulnerable wild populations and have responded by mass marking hatchery fish, so that fishing effort can be directed towards hatchery populations. However, the effectiveness of the approach is dependant on accurate marking and production of hatchery fish with high survival rates, and it is not yet clear whether selective fishing on hatchery stocks will be effective. Research demonstrating disease transmission from hatchery fish to wild populations is equivocal; evidence in this area is constrained by the lack of effective approaches to studying the fate of pathogens in the wild. We review several approaches to studying the economic consequences of hatchery programmes, but recognize that placing monetary value on conservation efforts or on hatcheries that mitigate cultural groups’ loss of historical harvest opportunities is difficult. We end by identifying existing major knowledge gaps, which, if filled, could contribute towards a fuller understanding of the role that hatchery programmes could play in meeting divergent goals. However, we 5 recognize that many management recommendations arising from such research may involve trade-offs between different risks, and that decisions about these trade-offs must occur within a social context. Hatcheries have played an important role in sustaining some highly endangered populations, and it is possible that reform of conservation hatchery practices will lead to an increase in the number of successful programmes. However, a serious appraisal of the role of hatcheries in meeting broader needs, such as harvest augmentation and mitigation, is urgently warranted and should take place at the scientific, but more effectively, at the societal level.
Quinn, TP, S Hodgson, L Flynn, R Hilborn, DE Rogers. 2007. Directional selection by fisheries and the timing of sockeye salmon migrations. Ecol. Applic. 17:731-739.
Sinclair, ARE, SAR Mduma, GC Hopcraft, JM Fryxell, R Hilborn, S Thirgood. 2007. Long-term ecosystem dynamics in the Serengeti: lessons for conservation. Cons. Biol. 21(3):580-590.
Long-term ecological studies are important to understanding ecosystem dynamics and for guiding evidence-based management. In the Serengeti-Mara Ecosystem, we examined natural and anthropogenic disturbances to further understanding of how the system functions. Through long-term monitoring of different components of the system we traced the effects of disturbances to elucidate cause and effect connections between them. Our quasi-natural experiment showed how different components of the ecosystem are integrated. Long-term data illustrated the role of population regulation in mammals, particularly in migratory wildebeest and non-migratory buffalo, through food limitation. Predation limited populations of smaller resident ungulates and small carnivores. Abiotic events, such as droughts and floods, created disturbances that affected survivorship of ungulates and birds. Such disturbances showed feedbacks between the system’s biotic and abiotic realms. Interactions between elephants and their food allowed savanna and grassland communities to co-occur as multiple states. Predators made use of the increase in woodland vegetation to facilitate capture of prey. This was a non-linear indirect interaction. Anthropogenic disturbances were direct through and hunting and indirect through transfer of disease to wildlife. Slow and rapid change and multiple ecosystem states became apparent only over a period of several decades and involved events at different spatial scales.
Conservation efforts need to accommodate both infrequent and unpredictable events and long-term trends. Management should plan on the time scale of those events and should not aim to maintain the status quo. Systems can be self-regulating by either food or natural enemies; thus, culling may not be required. Conservation efforts should consider that the ecosystem can occur in multiple states, and that there is no a priori need to maintain only one natural state. Finally, conservation efforts outside protected areas must distinguish between natural change and direct human-induced change. Protected areas can act as ecological baselines where human-induced change is kept to a minimum.
Walters, CJ, R Hilborn, R Parrish. 2007. An equilibrium model for predicting the efficacy of marine protected areas in coastal environments. Can. J. Fish. Aquat. Sci. 64:1009-1018.
Quantitative models of marine protected area proposals can be used to compare outcomes given current biological and economic knowledge. We used a model of a linear coastline, broken into 200 discrete cells each spanning 1.6 km of coast. This model is used to evaluate alternative proposals for marine protected area networks, predicting long-term (equilibrium) changes in abundances and harvests while accounting for dispersal of both larvae and older fish, changes in mean fecundity with reduced mortality in reserves, impacts of displaced fishing effort on abundances outside reserves, and compensatory (stock-recruitment) changes in post-settlement juvenile survival. The model demonstrates that even modest dispersal rates of older fish can substantially reduce the increase of abundance within protected areas compared to predictions from simpler models that ignore such dispersal. The strength of compensatory improvements in post-settlement juvenile survival is the most critical factor in determining whether a reserve network can rescue populations from the impacts of severe overharvesting. We use of the model to compare specific alternative proposals for protected area networks along the California coast, as mandated through California’s Marine Life Protection Act, and show that achieving the goals of the Act depends primarily on the fisheries management regulations outside of protected areas, and that the size and configuration of MPAs has a little impact.
Ward, EJ, R Hilborn, RG Towell, L Gerber. 2007. A state–space mixture approach for estimating catastrophic events in time series data. Can. J. Fish. Aquat. Sci. 64:899-910.
Catastrophic events are considered a major contributor to extinction threats, yet rarely included in population viability analysis. We extend the basic state-space population dynamics model to include a mixture distribution for the process error component of the model. The mixture distribution consists of a “normal” component describing regular variability, and a “catastrophic” component. The catastrophic component represents rare events that negatively affect the population. Direct estimation of parameters is rarely possible using a single time series, however estimation is possible when multiple surveys are available, or time series are combined in a meta-analysis. We apply the catastrophic state-space model to simulated time series of abundance from simple non-linear population dynamics models. Applications of the model to these simulated time series indicate that population parameters, and observation and process errors are estimated robustly. Both the frequency and magnitude of catastrophes are susceptible to bias, which is a linear function of the true values of the parameters. Our simulations indicate that the power to detect a catastrophe is also a function of the magnitude of catastrophes, and the degree of observation and process error present. A model that contains a mixture of gamma process errors and gamma observation error is more robust to model misspecification than a model that contains lognormal observation errors.
Branch, TA, R Hilborn, AC Haynie, G Fay, L Flynn, J Griffiths, KN Marshall, JK Randall, JM Scheuerell, EJ Ward, M Young. 2006. Fleet dynamics and fishermen behavior: lessons for fisheries managers. Canadian Journal of Fisheries and Aquatic Sciences 63:1647-1668.
We review fleet dynamics and fishermen behavior from an economic and sociological basis in developing fisheries, in mature fisheries near full exploitation, and in senescent fisheries that are overexploited and overcapitalized. In all cases, fishing fleets behave rationally within the imposed regulatory structures. Successful, generalist fishermen who take risks often pioneer developing fisheries. At this stage, regulations and subsidies tend to encourage excessive entry and investments, creating the potential for serial depletion. In mature fisheries, regulations often restrict season length, vessel and gear types, fishing areas, and fleet size, causing or exacerbating the race for fish and excessive investment, and are typically unsuccessful except when combined with dedicated access privileges (e.g., territorial rights, individual quotas). In senescent fisheries, vessel buyback programs must account for the fishing power of individuals and their vessels. Subsidies should be avoided as they prolong the transition towards alternative employment. Fisheries managers need to create individual incentives that align fleet dynamics and fishermen behavior with the intended societal goals. These incentives can be created both through management systems like dedicated access privileges and through market forces.
Branch, TA, K Rutherford, R Hilborn. 2006. Replacing trip limits with individual transferable quotas: implications for discarding. Mar. Pol. 30:281-292.
Flynn, L, AE Punt, R Hilborn. 2006. A hierarchical model for salmon run reconstruction and application to the Bristol Bay sockeye salmon (Oncorhynchus nerka) fishery. Canadian Journal of Fisheries and Aquatic Sciences 63:1564-1577.
Grafton, R.Q., R. Arnason, T. Bjørndal, D. Campbell, H.F. Campbell, C.W. Clark, R. Connor, D.P. Dupont, R. Hannesson, R. Hilborn, J.E. Kirkley, T. Kompas, D.E. Lane, G.R. Munro, S. Pascoe, D. Squires, S.I. Steinshamn, B.R. Turris, and Q. Weninger. 2006. Incentive-based approaches to sustainable fisheries. Canadian Journal of Fisheries and Aquatic Sciences 63:699-710.
The failures of traditional target-species management have led many to propose an ecosystem approach to fisheries to promote sustainability. The ecosystem approach is necessary, especially to account for fishery-ecosystem interactions, but does little to directly address two important factors of unsustainability — inappropriate incentives for fishers and the ineffective governance that exists in ‘command and control’ fisheries. We contend that much greater emphasis must be placed on fisher motivation when managing fisheries. Using evidence from more than a dozen ‘natural experiments’ in fisheries management, we argue that incentive-based approaches engendered by community, individual harvest or territorial rights, and coupled with public research, monitoring and effective oversight, promote sustainable fisheries.
Keywords: incentives, sustainability, rights, fisheries management
Hilborn, R. 2006. Defining success in fisheries and conflicts in objectives. Mar. Pol. doi:10.1016/j.marpol.2006.05.014/
Hilborn, R. 2006. Faith-based fisheries. Fisheries 31:554-555.
Hilborn, R. 2006. Fisheries success and failure: the case of the Bristol Bay salmon fishery. Bull. Mar. Sci. 78:487-498.
Hilborn, R, P Arcese, P, M Borner, J Hando, G Hopcraft, M Loibooki, S Mduma, ARE Sinclair. 2006. Effective enforcement in a conservation area. Science. 314:1266-1266.
Hilborn, R, J Annala, DS Holland. 2006. The cost of overfishing and management strategies for new fisheries on slow-growing fish: orange roughy (Hoplostethus atlanticus) in New Zealand. Canadian Journal of Fisheries and Aquatic Sciences 63:2149-2153.
Hilborn, R., F. Micheli, and G.A. De Leo. 2006. Integrating marine protected areas with catch regulation. Canadian Journal of Fisheries and Aquatic Sciences 63:642-649.
Previous models of Marine Protected Areas (MPAs) have generally assumed there were no existing regulations on catch, and have frequently shown that MPAs, by themselves, can be used to maintain both sustainable fish stocks and sustainable harvests. We explore the impact of implementing a MPA in a spatially structured model of a single species fish stock that is regulated by total allowable catch (TAC). We find that when a stock is managed at maximum sustainable yield, or is overfished, implementation of a MPA will require a reduction in TAC to avoid increased fishing pressure on the stock outside the MPA. In both cases catches will be lower as a result of overlaying an MPA on existing fisheries management. Only when the stock is so overfished that it is headed towards extinction does a MPA not lead to lower catches. In a TAC regulated fishery, even if the stock is overfished, MPA implementation may not improve overall stock abundance or increase harvest, unless catch is simultaneously reduced in the areas outside the MPA. Models that consider differential adult and larval dispersal need to be explored to see if these results are found with the more complex biology of a two stage model.
Hobbs, N.T., R. Hilborn. Alternatives to statistical hypothesis testing in ecology: A guide to self teaching. Ecological Applications 16:5-19.
Statistical methods emphasizing formal hypothesis testing have dominated the analyses used by ecologists to gain insight from data. Here, we review alternatives to hypothesis testing including techniques for parameter estimation and model selection using likelihood and Bayesian techniques. These methods emphasize evaluation of weight of evidence for multiple hypotheses, multimodel inference, and use of prior information in analysis. We provide a tutorial for maximum likelihood estimation of model parameters and model selection using information theoretics, including a brief treatment of procedures for model comparison, model averaging, and use of data from multiple sources. We discuss the advantages of likelihood estimation, Bayesian analysis, and meta-analysis as ways to accumulate understanding across multiple studies. These statistical methods hold promise for new insight in ecology by encouraging thoughtful model building as part of inquiry, providing a unified framework for the empirical analysis of theoretical models, and by facilitating the formal accumulation of evidence bearing on fundamental questions.
Hodgson, S., Quinn, T.P. Hilborn, R., Francis, R.C. and D.E. Rogers. 2006. Marine and freshwater climatic factors affecting interannual variation in the timing of return migration to fresh water of sockeye salmon (Oncorhynchus nerka). Fisheries Oceanography 14:1-24.
Scheuerell, MD, R Hilborn, MH Ruckelshaus, KK Bartz, KM Lagueux, AD Haas, K Rawson. 2006. The Shiraz model: a tool for incorporating anthropogenic effects and fish–habitat relationships in conservation planning. Canadian Journal of Fisheries and Aquatic Sciences 63:1596-1607.
Current efforts to conserve Pacific salmon (Oncorhynchus spp.) rely on a variety of information sources, including empirical observations, expert opinion, and models. Here we outline a framework for incorporating detailed information on density-dependent population growth, habitat attributes, hatchery operations, and harvest management into conservation planning in a time-varying, spatially explicit manner. We rely on a multistage Beverton ?Holt model to describe the production of salmon from one life stage to the next. We use information from the literature to construct relationships between the physical environment and the necessary productivity and capacity parameters for the model. As an example of how policy makers can use the model in recovery planning, we applied the model to a threatened population of Chinook salmon (Oncorhynchus tshawytscha) in the Snohomish River basin in Puget Sound, Washington, USA. By incorporating additional data on hatchery operations and harvest management for Snohomish River basin stocks, we show how proposed actions to improve physical habitat throughout the basin translate into projected improvements in four important population attributes: abundance, productivity, spatial structure, and life history diversity. We also describe how to adapt the model to a variety of other management applications.
Parma, AM, R Hilborn, JM Orensanz. 2006. The good, the bad and the ugly: learning from experience to achieve sustainable fisheries. Bull. Mar. Sci. 78:411-428.
Branch, TA, R Hilborn, E Bogazzi. 2005. Escaping the tyranny of the grid: a more realistic way of defining fishing opportunities. Canadian Journal of Fisheries and Aquatic Sciences 62:631-642.
de Valpine, P. and R. Hilborn. 2005. State-space likelihoods for nonlinear fisheries time-series. Canadian Journal of Fisheries and Aquatic Sciences 62:1937-1952.
Hyun, S.-Y., Hilborn, R. Anderson J. and Ernst, B. 2005. A statistical model for in-season forecasts of sockeye salmon (Oncorhynchus nerka) returns to the Bristol Bay districts of Alaska. Canadian Journal of Fisheries and Aquatic Sciences 62:1665-1680.
Branch, T. A., Hilborn, R., and Bogazzi, E. 2005. Escaping the tyranny of the grid: a more realistic way of defining fishing opportunities. Canadian Journal of Fisheries and Aquatic Sciences 62:631-642.
Hilborn, R. 2005. Fisheries management. Issues in Science and Technology, 21:10-11.
Hilborn, R., J.M. Orensanz, and A.M. Parma. 2005. Institutions, incentives and the future of fisheries. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 360:47-57.
Hilborn, R., J.K. Parrish, and K. Litle. 2005. Fishing Rights or Fishing Wrongs? Rev. Fish Biol. Fish. 15:191-198.
Packer, C., R. Hilborn, A. Mosser, B. Kissui, M. Borner, G. Hopcraft, J. Wilmshurst, S. Mduma, and A.R.E. Sinclair. 2005. Ecological Change, Group Territoriality, and Population Dynamics in Serengeti Lions. Science 307:390-393.
Sharma, R., A. Cooper, and R. Hilborn. 2005. A quantitative framework for the analysis of habitat and hatchery practices on Pacific salmon. Ecological Modelling. 183:231-250.
Walters, C.J., and R. Hilborn. 2005. Exploratory assessment of historical recruitment patterns using relative abundance and catch data. Canadian Journal of Fisheries and Aquatic Sciences 62:1985-1990.
Valero, J., C. Hand, J.M. Orensanz, A. M. Parma, D.Armstrong, R. Hilborn. 2004. Geoduck (Panopea abrupta) recruitment trends in the Pacific northwest: long-term changes in relation to climate. California Cooperative Oceanic Fisheries Investigations Report 45:80-86.
Boatright, C., T. Quinn, and R. Hilborn. 2004. Timing of adult migration and stock structure for sockeye salmon in Bear Lake, Alaska. Transactions of the American Fisheries Society 133:911-921.
Orensanz, J. M., C. M. Hand, A. M. Parma, J. Valero, and R. Hilborn. 2004. Precaution in the harvest of Methuselah's clams—the difficulty of getting timely feedback from slowpaced dynamics. Canadian Journal of Fisheries and Aquatic Sciences 61:1355-1372.
Hilborn, R., Punt, A.E., Orensanz, J. 2004. Beyond band-aids in fisheries management: fixing world fisheries. Bulletin of Marine Science 74(3):493-507.
Hilborn, R., K. Stokes, J.J. Maguire, A.D.M. Smith, L.W. Botsford, M. Mangel, J. Orensanz, A. Parma, J. Rice, J. Bell, K.L. Cochrane, S. Garcia, S.J. Hall, G.P. Kirkwood, K. Sainsbury, G. Stefansson, C.J. Walters. 2004. When can marine reserves improve fisheries management? Ocean and Coastal Management 47/3-4:197-205.
Hilborn, R. 2004. Ecosystem-based fisheries management: the carrot or the stick? Marine Ecology-Progress Series 274:275-278.
Flynn, L., and R. Hilborn. 2004. Test fishery indices for sockeye salmon (Oncorhynchus nerka) as affected by age composition and environmental variables. Canadian Journal of Fisheries and Aquatic Sciences 61:80- 92
Gende, S.M., Quinn, T.P., Hilborn, R., Hendry A.P. and Dickerson, B. 2004. Brown bears selectively kill salmon with higher energy content but only in habitats that facilitate choice. Oikos 104:518-528.
Norse, E. A., C. B. Grimes, S. Ralston, R. Hilborn, J. C. Castilla, S. R. Palumbi, D. Fraser, and P. Kareiva. 2003. Marine reserves: the best option for our oceans? Frontiers in Ecology and Environment 1:495- 502.
Hilborn, R., T.A. Branch. B. Ernst, A Magnusson, C.V. Minte-Vera, M.D. Scheuerell, and J.L. Valero. 2003. State of the world's fisheries. Annual Review of Environment and Resources 28:359-399.
Magnusson, A. and R. Hilborn. 2003. Estuarine influence on survival rates of coho (Oncorhynchus kisutch) and chinook salmon (Oncorhynchus tshawytscha) released from hatcheries on the U.S. Pacific coast. Estuaries 26:1094-1103.
Butterworth, D.S., J.N. Ianelli, R. Hilborn. 2003. A statistical model for stock assessment of southern bluefin tuna with temporal changes in selectivity. South African Journal of Marine Science 25:331-361.
Cooper, Andrew B., Hilborn, Ray, Unsworth, James W. 2003. An approach for population assessment in the absence of abundance indices. Ecological Applications 13(3):814-828.
Barrowman, Nicholas J., Myers, Ransom A., Hilborn, Ray, Kehler, Daniel G., Field, Chris A. 2003. The variability among populations of coho salmon in the maximum reproductive rate and depensation. Ecological Applications 13(3):784-793.
Flynn, L., R. Hilborn and A.E. Punt. 2003. Identifying the spatial distribution of stocks of migrating adult sockeye salmon using age composition data. Alaska Fishery Research Bulletin 10:50-60.
Stewart, I.J. R. Hilborn and T.P. Quinn. 2003. Coherence of observed adult sockeye salmon abundance within and among spawning habitats in the Kvichak River watershed. Alaska Fishery Research Bulletin 10:28-41.
Hilborn, R. 2003. The state of the art in stock assessment: where we are and where we are going. Scientia Marina 67(supplement 1):15-20.
Breen, P.A., R. Hilborn, M. Maunder, S. Kim . 2003. Comparing alternative harvest rules to minimise the effects of squid fishery bycatch on Hooker's sea lions (Phocarctos hookeri) in New Zealand. Canadian Journal of Fisheries and Aquatic Sciences 60:527:541.
Hilborn, R., T.P. Quinn, D.E. Schindler and D.E. Rogers. 2003. Biocomplexity and fisheries sustainability. Proceedings of the National Academy of Sciences 100:6564-6568.
Cooper, A. B., J. C. Pinheiro, J.W. Unsworth and R. Hilborn. 2002. Predicting hunter success rates from elk and hunter abundance, season structure, and habitat. Wildlife Society Bulletin 30:1068-1077.
Hilborn, R. 2002. The Dark Side of Reference Points. Bulletin of Marine Science 70:403-408
Myers, R.A., N.J. Barrowman, R. Hilborn and D.G. Kehler. 2002. Inferring Bayesian priors with limited direct data: applications to risk analysis. North American Journal of Fisheries Management 22:351-364.
Hilborn, R. 2002. Marine reserves and fisheries management. Science 295:1233-1234.
Hilborn, R., A. Parma and M. Maunder. 2002. Exploitation rate reference points for west coast rockfish: are they robust and are there better alternatives. North American Journal of Fisheries Management 22:365- 375.
Schindler, D., T.E. Essington, J.F. Kitchell, C. Boggs and R. Hilborn. 2002. Sharks and tunas: fisheries impacts on predators with contrasting life histories. Ecological Applications 12:735-748.
Essington, T.E., J.F. Kitchell, C. Boggs, D.E. Schindler, R.J. Olson and R. Hilborn. 2002. Alternative fisheries and the predation rate of yellowfin tuna in the eastern Pacific Ocean. Ecological Applications 12:724-734.
Rose, K.A., J.H. Cowan Jr., K.O. Winemiller, R.A. Myers and R. Hilborn. 2001. Compensatory density dependence in fish populations: importance, controversy, understanding and prognosis. Fish and Fisheries 2:293-327.
Sharma, R. and R. Hilborn. 2001. Empirical relationships between watershed characteristics and coho salmon (Oncorhynchus kisutch) smolt abundance in 14 western Washington streams. Canadian Journal of Fisheries and Aquatic Sciences 58:1453-1463.
Gerber, L.R. and R. Hilborn. 2001. Catastrophic events and recovery from low densities in populations of otariids: implication for risk of extinction. Mammal Review 11:131-150.
Hilborn, R. and D. Eggers. 2001. A review of the hatchery programs for pink salmon in Prince William Sound and Kodiak Island, Alaska: response to comment. Transactions of the American Fisheries Society 130:720-724.
Liermann, M. and R. Hilborn. 2001. Depensation, evidence, models and implications. Fish and Fisheries 2:33-58.
Hilborn, R. 2001. Calculation of biomass trend, exploitation rate and surplus production from survey and catch data. Canadian Journal of Fisheries and Aquatic Sciences 58:579-584.
Hilborn, R., J.J. Maguire, A. M. Parma, and A. A. Rosenberg. 2001. The precautionary approach and risk management: can they increase the probability of success in fisheries management. Canadian Journal of Fisheries and Aquatic Sciences 58:99-107
Hilborn, R. and D. Eggers. 2000. A review of the hatchery programs for pink salmon in Prince William Sound and Kodiak Island, Alaska. Transactions of the American Fisheries Society 129:333-350.
Hamon, T.R., C.J. Foote, R. Hilborn and D.E. Rogers. 2000. Selection on morphology of spawning wild salmon by a gill-net fishery. Transactions of the American Fisheries Society 129:1300-1315.
Maunder, M., Starr, P.J. and R. Hilborn. 2000. A Bayesian analysis to estimate loss in squid catch due to the implementation of a sea lion population management plan. Marine Mammal Science 16: 413-426.
Mduma, S. Sinclair, A.R.E. and R. Hilborn. 1999. Food regulates the Serengeti wildebeest: a forty-year record. Journal of Animal Ecology 68:1101-1122.
Hilborn, R., B.G. Bue, and S. Sharr. 1999. Estimating spawning escapements from periodic counts: a comparison of methods. Canadian Journal of Fisheries and Aquatic Sciences 56:888-896.
Hilborn, R. 1999. Confessions of a reformed hatchery basher. Fisheries 24:30-31.
Hilborn, R. and M. Liermann. 1998. Standing on the shoulders of giants: learning from experience. Reviews in Fish Biology and Fisheries 8:273-283
Coronado, C. and R. Hilborn. 1998. Spatial and temporal factors affecting survival in coho salmon (Oncorhynchus kisutch) in the Pacific Northwest. Canadian Journal of Fisheries and Aquatic Sciences 55:2067-2077.
Hilborn, R. 1998. The economic performance of marine stock enhancement projects. Bulletin of Marine Science 62:661-674
Coronado, C. and R. Hilborn. 1998. Spatial and temporal factors affecting survival in coho and fall chinook salmon in the Pacific northwest. Bulletin of Marine Science 62:409-425.
Orensanz, J.M., J. Armstrong, D. Armstrong and R. Hilborn. 1998. Crustacean resources are vulnerable to serial depletion—the multifaceted declines of crab and shrimp fisheries in the Greater Gulf of Alaska. Reviews in Fish Biology and Fisheries 8:117-176
Starr, P., J.H. Annala and R. Hilborn. 1998. Contested stock assessment: two case studies. Canadian Journal of Fisheries and Aquatic Sciences 55:529-537.
Prince J. and R. Hilborn. 1998. Concentration profiles and invertebrate fisheries management.. Canadian Special Publication of Fisheries and Aquatic Sciences 125:187-196.
Hilborn, R. 1997. Statistical hypothesis testing and decision theory in fisheries science. Fisheries 22(10):19-20
Pascual, M.A., P. Kareiva and R. Hilborn. 1997. The influence of model structure on conclusions about the viability and harvesting of Serengeti wildebeest. Conservation Biology 11:966-976.
Starr, P.J., Breen, P.A., Hilborn, R. and T.H. Kendrick. 1997. Evaluation of a management decision rule for a New Zealand rock lobster substock. Mar. Freshwater Res. 48:1093-1101.
Hilborn, R. 1997. Lobster stock assessment: report from a workshop; II. Mar. Freshwater Res. 48:945-947
Liermann, M. and R. Hilborn. 1997. Depensation in fish stocks: a hierarchic Bayesian meta-analysis. Canadian Journal of Fisheries and Aquatic Sciences 54:1976-1984.
Fogarty, M.J., Hilborn, R. and D. Gunderson. 1997. Chaos and parametric management. Marine Policy 21:187-194.
Punt, A.E. and R. Hilborn. 1997. Fisheries stock assessment and decision analysis: the Bayesian approach. Reviews in Fish Biology and Fisheries 7:35-63.
Hilborn, R. 1997. Recruitment paradigms for fish stocks. Canadian Journal of Fisheries and Aquatic Sciences 54:984-985. doi:10.1139/f97-050.
Hilborn, R. 1996. Risk analysis in fisheries and natural resource management. Human Ecology and Risk Assessment 2:655-659.
Hilborn, R. 1996. Do principles for conservation help managers? Ecological Applications 6:364-365.
Hilborn, R. and D. Gunderson. 1996. Chaos and paradigms for fisheries management. Marine Policy 20:87-89.
Hilborn, R., C.J. Walters and D. Ludwig. 1995. Sustainable exploitation of renewable resources. Annual Review of Ecology and Systematics 26:45- 67.
Pascual, M. A., and R. Hilborn. 1995. Conservation of harvested populations in fluctuating environments: the case of the Serengeti wildebeest. Journal of Applied Ecology 32:468-480.
McAllister, M.M, E.K. Pikitch, A.E. Punt and R. Hilborn. 1994. A Bayesian approach to stock assessment and harvest decisions using the sampling/importance resampling algorithm. Canadian Journal of Fisheries and Aquatic Sciences 51:2673-2687.
Anganuzzi, A., R. Hilborn and J. R. Skalski. 1994. Estimation of size selectivity and movement rates from mark-recapture data. Canadian Journal of Fisheries and Aquatic Sciences 51:734-742
Punt, A.E. and R. Hilborn. 1994. A comparison of fishery models with and without cannibalism with implications for the management of the Cape hake resource off southern Africa. ICES Journal of Marine Science 51:19-29
Winton, J. and R. Hilborn. 1994. Lessons from supplementation of chinook salmon in British Columbia. North American Journal of Fisheries Management 14:1-13
Hilborn, R., E. K. Pikitch, and M. K. McAllister. 1994. A Bayesian estimation and decision analysis for an age-structured model using biomass survey data. Fisheries Research 19:17-30
Schnute, J. T. and R. Hilborn. 1993. Analysis of contradictory data sources in fish stock assessment. Canadian Journal of Fisheries and Aquatic Sciences 50:1916-1923
Polacheck, T., R. Hilborn and A. E. Punt. 1993. Fitting surplus production models: comparing methods and measuring uncertainty. Canadian Journal of Fisheries and Aquatic Sciences 50:2597-2607.
Hilborn, R. and J. Winton. 1993. Learning to enhance salmon production: lessons from the salmonid enhancement program. Canadian Journal of Fisheries and Aquatic Sciences 50:2043-2056
Hilborn, R. and D. Ludwig. 1993. The limits of applied ecological research. Ecological Applications 3:550-552
Ludwig, D., R. Hilborn, and C. Walters. 1993. Uncertainty, resource exploitation, and conservation: lessons from history. Science 260:17/36.
Hilborn, R., E. K. Pikitch, M. K. McAllister, and A. E. Punt. 1993. Use of Risk Analysis to Assess Fishery Management Strategies—a Case-Study Using Orange Roughy (Hoplostethus atlanticus) on the Chatham Rise, New-Zealand—Comment. Canadian Journal of Fisheries and Aquatic Sciences 50:1122-1125.
Hilborn, R., E.K. Pikitch, and R.C. Francis. 1993. Current trends in including risk and uncertainty in stock assessment and harvest decisions. Canadian Journal of Fisheries & Aquatic Sciences 50:874-880.
Hilborn, R. 1992. Current and future trends in fisheries stock assessment and management. South African Journal of Marine Science 12:975-988.
Hilborn, R. 1992. Can fisheries agencies learn from experience? Fisheries 17:6-14.
Hilborn, R. 1992. Hatcheries and the future of salmon in the northwest. Fisheries 17:5-8.
Hilborn, R. 1992. Institutional learning and spawning channels for sockeye salmon (Oncorhynchus nerka). Canadian Journal of Fisheries and Aquatic Science 49:1126-1136.
Hilborn, R. and R. Kennedy. 1992. Spatial pattern in catch rates: a test of economic theory. Bulletin of Mathematical Biology 54:263-273.
Hilborn, R., and C. J. Krebs. 1992. Bias in the Minimum Number Alive Estimator - a Reply. Canadian Journal of Zoology. 70:632-632.
Hilborn, R. 1991. Modeling the stability of fish schools: exchange of individual fish between schools of skipjack tuna (Katsuwonus pelamis). Canadian Journal of Fisheries and Aquatic Sciences 48:1081-1091.
Hilborn, R. 1990. Determination of fish movement patterns from tag recoveries using maximum likelihood estimators. Canadian Journal of Fisheries and Aquatic Sciences 47:635-643.
Hilborn, R. 1989. Yield estimation for spatially connected populations: an example of surface and longline fisheries for yellowfin tuna. North American Journal of Fisheries Management 9:402-410.
Hilborn, R. 1989. Models of tag dynamics with exchange between available and unavailable populations. Canadian Journal of Fisheries and Aquatic Sciences 46:1356-1366.
Hilborn, R. 1989. International Management of Tuna. Marine Policy, 13:166- 166.
Hilborn, R. and P. Medley. 1989. Tuna purse seine fishing with fish aggregating devices: models of tuna FAD interactions. Canadian Journal of Fisheries and Aquatic Sciences 46:28-32.
Hilborn, R. and J. Sibert. 1988. Is international management of tuna necessary? Marine Policy. January 1988, pp. 31-39.
Hilborn, R. and J. Sibert. 1988. Adaptive management of developing fisheries. Marine Policy. April 1988, pp. 112-121.
Hilborn, R. 1988. Determination of tag return from recaptured fish by sequential examination for tags. Transactions of the American Fisheries Society 117:510-514.
Starr, P.J. and R. Hilborn. 1988. Reconstruction of harvest rates and stock contribution in gauntlet salmon fisheries. Canadian Journal of Fisheries and Aquatic Sciences 45:2216-2229.
Hall, D.L, R. Hilborn, M. Stocker and C.J. Walters. 1988. Alternative harvest strategies for Pacific Herring (Clupea harengus pallasi). Canadian Journal of Fisheries and Aquatic Sciences 45:888-897.
Fried, S.M. and R. Hilborn. 1988. A Bayesian approach to inseason run size estimation for Bristol Bay, Alaska, Sockeye Salmon (Oncorhynchus nerka). Canadian Journal of Fisheries and Aquatic Sciences 45:850-855.
Hilborn, R. and W. Luedke. 1987. Rationalizing the irrational: a case study in user group participation in Pacific salmon management. Canadian Journal of Fisheries and Aquatic Sciences 44:1796-1805.
Hilborn, R. 1987. Living with uncertainty in resource management. North American Journal of Fisheries Management 7:1-5.
Shardlow, T., R. Hilborn, and D. Lightly. 1987. Components analysis of instream escapement methods for Pacific Salmon. Canadian Journal of Fisheries and Aquatic Sciences 44:1031-1037.
Hilborn, R. and C.J. Walters. 1987. A general model for simulation of stock and fleet dynamics in spatially heterogeneous fisheries. Canadian Journal of Fisheries and Aquatic Sciences 44:1366-1370.
Hilborn, R. and C.J. Walters. 1987. Microcomputer simulation for training and teaching. Environmental Software 1:156-163.
Hilborn, R. 1986. A comparison of alternative harvest tactics for invertebrate fisheries. Pp. 313-317 in G.S. Jamieson and N. Bourne (eds.), Canadian Special Publication in Fisheries and Aquatic Sciences 92.
Hilborn, R. 1986. Some Remarks on Determinants of Catching Power in the British-Columbia Salmon Purse Seine Fleet by Hilborn and Ledbetter—Reply. Canadian Journal of Fisheries and Aquatic Sciences, 43:1086- 1088.
Moussalli, E. and R. Hilborn. 1986. Optimal stock size and harvest rate in multistage life history models. Canadian Journal of Fisheries and Aquatic Sciences 43:135-141.
Renyard, T.S. and R. Hilborn. 1986. Sport angler preferences for alternative regulatory methods. Canadian Journal of Fisheries and Aquatic Sciences 43:240-242.
Lawson, T.A. and R. Hilborn. 1985. Equilibrium yields and yield isopleths from a general age-structured model of harvested populations. Canadian Journal of Fisheries and Aquatic Sciences 42:1766-1771.
Hilborn, R. 1985. Simplified calculation of optimum spawning stock size from Rickers' stock recruitment curve. Canadian Journal of Fisheries and Aquatic Sciences 42:1834-1835.
Hilborn, R. 1985. Fleet dynamics and individual variation: why some people catch more fish than others. Canadian Journal of Fisheries and Aquatic Sciences 42:2-13.
Hilborn, R. 1985. Apparent stock recruitment relationships in mixed stock fisheries. Canadian Journal of Fisheries and Aquatic Sciences 42:718-723.
Shardlow, T. and R. Hilborn. 1985. Density dependent catchability coefficients. Transactions of the American Fisheries Society 114:436-438.
Hilborn, R. and M. Ledbetter. 1985. Determinants of catching power in the B.C. salmon purse seine fleet. Canadian Journal of Fisheries and Aquatic Sciences 42:51-56.
Hilborn, R., C.J. Walters, R.M. Peterman and M.J. Staley. 1984. Models and fisheries: A case study in implementation. North American Journal of Fisheries Management 4:9-15.
Walker, K.D., R.B. Rettig, and R. Hilborn. 1983. Analysis of multiple objectives in Oregon coho salmon policy. Canadian Journal of Fisheries and Aquatic Sciences 40:580-587.
Argue, A.W., R. Hilborn, R.M. Peterman, M.J. Staley, and C.J. Walters. 1983. The Strait of Georgia Chinook and Coho fishery. Canadian Journal of Fisheries and Aquatic Sciences Bulletin 211.
Ludwig, D. and R. Hilborn. 1983. Adaptive probing strategies for age structured fish stocks. Canadian Journal of Fisheries and Aquatic Sciences 40:559-569.
Stocker, M. and R. Hilborn. 1982. Comment on "Short-term forecasting in marine fish stocks." Canadian Journal of Fisheries and Aquatic Sciences 39:1071-1072.
Hilborn, R. and S. Stearns. 1982. On inference in ecology and evolutionary biology: the problem of multiple causes. Acta Biotheoretica 32:145-164.
Hilborn, R. and C.J. Walters. 1981. Pitfalls of environmental baseline and process studies. Environmental Impact Assessment Review 2: 265-278.
Stocker, M. and R. Hilborn. 1981. Short term forecasting in marine fish stocks. Canadian Journal of Fisheries and Aquatic Sciences 38:1247-1254.
Yom-Tov, Y. and R. Hilborn. 1981. Energetic constraints on clutch size and time of breeding in temperate zone birds. Oecologia 48:234-243.
Hilborn, R. 1979. Comparison of fisheries control systems that utilize catch and effort data. Journal of the Fisheries Research Board of Canada 36:1477-1489.
Hilborn, R. 1979. Some failures and successes at applying systems analysis to ecological problems. Journal of Applied Systems Analysis 6:25-31.
Hilborn, R. and M. Ledbetter. 1979. Analysis of the British Columbia salmon purse seine fleet: dynamics of movement. Journal of the Fisheries Research Board of Canada 36:384-391.
Hilborn, R. 1979. Some long term dynamics of predator–prey models with diffusion. Ecological Modelling 6:23-30.
Walters, C.J., R. Hilborn, R.M. Peterman and M. Staley. 1978. A model for examining early ocean limitation of Pacific salmon production. Journal of the Fisheries Research Board of Canada 35:1303-1315.
Walters, C.J. and R. Hilborn. 1978. Ecological optimization and adaptive management. Annual Review of Ecology and Systematics 8:157-188.
Hilborn, R. and C.J. Walters. 1977. Differing goals of salmon management on the Skeena River. Journal of the Fisheries Research Board of Canada 34:64-72.
Hilborn, R., C.J. Krebs, and J.A. Redfield. 1976. On the reliability of enumeration for mark and recapture census of voles. Canadian Journal of Zoology 54:1019-1024.
Hilborn, R. and C.J. Krebs. 1976. Fates of disappearing individuals in fluctuating populations of Microtus townsendi. Canadian Journal Zoology 54:1501-1520.
Hilborn, R. 1976. Optimal exploitation of multiple stocks by a common fishery. Journal of the Fisheries Research Board of Canada 33:1-5.
Walters, C.J. and R. Hilborn. 1976. Adaptive control of fishing systems. Journal of the Fisheries Research Board of Canada 33:145-159.
Krebs, C.J. I. Wingate, J. LeDuc, J. Redfield, M. Taitt and R. Hilborn. 1976. Microtus population biology: dispersal in fluctuating populations of Microtus townsendi. Canadian Journal of Zoology 54:79-95.
Hilborn, R. 1975. Similarities in dispersal tendency among siblings in four species of voles (Microtus). Ecology 56:1221-1225.
Hilborn, R. 1975. The effect of spatial heterogeneity on the persistence of predator-prey interactions. Theoretical Population Biology 8:346-355.
Walters, C.J., Bunnell, F., Hilborn, R., and R.M. Peterman. 1975. Computer simulation of barren ground caribou dynamics. Ecological Modelling 1:303-315.
Himamowa, Bubu. 1975. The Obergurgl model: a microcosm of economic growth in relation to limited ecological resources. Nature and Resources 2:10-21. (Himamowa is a pseudonym for myself and six other authors)
Hilborn, R. 1974. Inheritance of skeletal polymorphism in Microtus californicus. Heredity 33:81-83.
Walters, C.J. R. Hilborn, E. Oguss, R. Peterman and J. Stander. 1974. Development of a simulation model of Mallard duck populations. Canadian Wildlife Service Occasional Paper No. 20:1-34.
Hilborn, R. 1973. A control system for FORTRAN simulation programming. Simulation. 20:172-175.