From harvest regulations to harvest plans - and a step further to biological reference points.

Oddgeir Andersen	Hedmark University College - HIHM Norwegian Institute for Nature Research - NINA
Mikkel Kvasnes	Hedmark University College - HIHM

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Abstract

We discuss the development of some central management principles for recreational fishing and hunting. As ecological knowledge has been gained, it has influenced how managers have applied economic, ecological and sociocultural principles to harvest management, and contributed to the field of applied ecology.  We also describe how applied ecology has been imbedded through the history of harvest regulations by giving examples of management practices in Norway and the United States.  The key purpose is to draw some lessons from comparing applications used in management of recreational fishing and hunting. The most important lesson learned is that adaptive harvest management based on management plans are better tools than regulations without any evaluation of the outcome. For game species that do not have a management based on plans, we recommend adaptive management plans for the future.

Key words: adaptive management, applied ecology, hunting, Norway, recreational fishing, USA, wildlife.

Norsk sammendrag:

Her beskrives utviklingen av noen sentrale prinsipper som benyttes i forvaltningen av rekreasjonsjakt og –fiske. Etter som den økologiske kunnskapen har økt, har forvaltningen tatt i bruk både økologiske, økonomiske og sosiokulturelle prinsipper i reguleringene av jakt og fiske og således bidratt til fagfeltet anvendt økologi. Vi gir her en kort fremstilling av hvordan anvendt økologi gjennom tiden har blitt innlemmet i forvaltningen av jakt og fiske gjennom å gi eksempler på ulike praksiser i Norge og USA. Vi konkluderer med at den viktigste lærdommen å ta med seg fra vilt- og fiskeforvaltningen i USA og Norge, er at planbasert beskatning er bedre styringsverktøy enn reguleringer uten noen form for evaluering av utfallet. For viltarter som beskattes uten noen form for beskatningsplan, vi anbefaler å utarbeide adaptive forvaltningsmodeller i fremtiden.

Introduction

In modern history, harvesting has turned from a subsistence-activity to a recreational- and industrial activity. Despite increased knowledge about harvesting and its effects, overexploitation related to both commercial- and recreational harvest is still causing fish stocks and game populations to go extinct or being heavily reduced (Dudgeon et al., 2006; Lewin, Arlinghaus, & Mehner, 2006; Milner-Gulland et al., 2003; Post et al., 2002; Storch, 2007). For instance, as much as 70% of the world’s marine resources were overharvested or depleted in 1995 (World Resources Institute, 1996).

The first regulations of harvesting were commonly related to property rights (landowners or regents), but as soon as recreational fishing and hunting were considered as common pool resources, the need for harvest regulations increased to avoid what Hardin described as  “The tragedy of the commons” (Hardin, 1968). Measures such as regulations from authorities were taken already in the 13th century in Norway (R. Andersen, Fagerheim, & Solheim, 2009) and in the 15th century in colonial North America (Connelly, Gammonley, & Peek, 2005). The development of more effective harvesting techniques, weapons and fishing gear led to an increase in harvest efficiency, and thus is an important factor in the reduction of populations and the introduction of regulations. Currently, hundreds of species of mammals, birds and fish are listed as endangered because of human persecution (Vié, Hilton-Taylor, & Stuart, 2009). Known examples of recreational overexploitation are;  River salmonids in Canada (Post et al., 2002), and several tetraonids in Europe, Asia and north America (see review in (Storch, 2007).

Wildlife management as a scientific discipline is approximately a century old (Organ, Decker, Carpenter, Siemer, & Riley, 2006). The “Doctrine of wise use” was introduced by Theodore Roosevelt and Gifford Pinchot in 1910, and the idea was that wildlife, forests, ranges and waterpower where conceived as “renewable organic resources” which might last forever if they were “harvested scientifically and not faster than they reproduced”.  The doctrine was determinant for the subsequent history of American game management in three basic respects (cited from Leopold, 1933):

1. It recognized all these “outdoor” resources as one integral one
2. It recognized their “conservation through wise use” as a public responsibility, and their private ownership as a public trust.
3. It recognized science as a tool for discharging that responsibility.

Harvesting was in the early years of wildlife management not considered to have major impact on population dynamics, in spite of numerous examples of species endangered for extinction (buffalo, musk ox) or species that went extinct (e.g. the Arizona elk) caused by hunting. The primary goal was to prevent overharvesting. Aldo Leopold used the term “sustained” in the first phrase of his book “Game management” (Leopold, 1933) where he defined game management like this:  “game management is the art of making land produce sustained annual crops of wild game for recreational use”. “Sustainable use” has turned out to be a fundamental concept in the management of all natural resources that man utilizes on earth. Note that recreational use also was mentioned. In recreational fishery, there has always been accepted that recreational harvesting affects populations. One exception might be highly successful catch and release (C & R) fishing regulations.

Extinction or decimation of predators has caused high abundances of many prey species (Sinclair, Fryxell, & Caughley, 2006). Hence harvesting is also used as a tool (in lack of sufficient numbers of predators) to regulate or control wildlife populations, especially large ungulates (R. Andersen et al., 2009). Whether the management goal is to avoid overharvesting or limit numbers, wildlife and fish management has applied several different harvest models and regulations through history. The purpose of these models is primarily to suggest (or calculate) sustainable quotas and obtain stable population dynamics.

We will describe and discuss how some central harvest principles and models for recreational fishery and wildlife has developed and how management has adopted them. But first, we briefly consider some important aspects of harvest theory.

Harvest theory

The scientific literature leaves no doubt that uncontrolled harvesting has had devastating effects on fish and game populations. Restrictions such as imposing and reducing bag-limits, eliminating year-round hunting and fishing, restricting legal  weapon or fishing gear, and limiting daily or  weekly hunting and fishing  hours, was designed to reduce or eliminate risk of overharvesting (Connelly et al., 2005). Successful and modern harvest strategies consist of three important components; population ecology, economy and society.

The first component in finding successful management strategies, is to have a good understanding of the population dynamics when a population is not harvested (Aanes, Engen, Saether, Willebrand, & Marcstrom, 2002), but knowledge about the populations response on harvest is also essential. Population models must include parameters such as demographic rates (growth rates), immigration, emigration and density regulation mechanisms to give a realistic description of the population dynamics. Species with different population dynamics and lifespan may require different management models and approaches. Theory on population dynamics often refers to r- and K-selected species. Given the equation (1), describing populations with constant growth rate in relation to the theoretical carrying capacity (Lotka, 1932; Volterra, 1926):

                (1)    

Where r- is the intrinsic or per capita growth rate, K is the (theoretical) carrying capacity, N is the number of individuals and ∆ (t or N) is the change in time and number of individuals. The growth rate is defined as the change in numbers over time. If the species has high reproductive capacity (e.g. small rodents Microtus spp. and ptarmigan Lagopus spp.) and numbers can vary to a large extent between years, then the species selects for high reproductive capacity (r), but if the reproductive capacity is lower, e.g. ungulates as moose (Alces alces), numbers are usually more stable between years, then the species selects for approaching the carrying capacity (K). These differences in population dynamics may require different management approaches.
In the early years of game management, focus was to maximize the outcome (according to Leopolds definition of game management). The term Maximum Sustainable Yield (MSY) was introduced (mainly for species with density-dependent growth rates). MSY has its roots from agricultural thinking and economic theory, but was in these settings applicable to ecological principles as well (Figure 1).

Figure 1. Principles for harvest levels in relation to the theory of maximum sustainable yield (MSY). Modified from Ricker (1954).

N is the population size in relation to the carrying capacity (K, where N=100). K/2 is the inflection point, where the recruitment curve starts to “slow down”, approaching the populations carrying capacity. K/2 gives the theoretical maximum growth rate, the point at which the most production occurs. Line h illustrates the effect of harvest in relation to two different population sizes with equal recruitment rates (figure 1). At low population size, any harvest quota (situation H1:N< k/2) might be unstable, but at high population density, any harvest quota (situation H2: N>K/2) and up to carrying capacity (K) will be stable. In conservation biology, the harvesting at high (right side of k/2) or low levels (left side of k/2) are known as soft and hard selection impact, regarding genetic traits (Figure 1). 

It gets complicated: Adding more diverse societal goals

Later advances and critique of the MSY because fish and game was common-pool resources, led to modification of the MSY-concept to Optimum Sustainable Yield (OSY) (Aas, 1991). OSY is defined as the amount of fish or game that:

1. Gives in total, the largest use as a whole, with emphasis on produced weigh of food, recreational opportunities.
2. Is defined from MSY for the fish or game resources, modified out of relevant economic-, ecological- or societal factors, modified from Ditton (1977).

OSY can be described as the MSY, modified by economical or political (societal) reasons. Note that recreational opportunities are on the same footing than produced weight of food. Management agencies today generally develop their objectives within the frames of OSYs instead of MSY. The transition from MSY to OSY was an important shift in way of thinking, by including wider societal interests including broader human dimension perspectives. By managing after the principles of OSY, the two latter components in a modern, successful management strategy was included. Now we will discuss the traditions and histories of harvest management for fish and game. Hereafter, we use the term “harvest model” as a model or strategy that:

1. Limits or defines the proportion of the population that can be harvested (within limits of sustainability or other objectives), and/or
2. Defines (proportions of) specific size-, age- and/or sex classes that should be harvested from a given population.

A key, underlying question is: Are there differences in how the two sectors of (recreational) fishing and hunting management have approached harvest management and are there lessons to be learned between the two traditions? 

Harvest management in recreational freshwater fishery

“Gamefish are too valuable to be caught only once”     Lee Wulff (1939).

In England, during Queen Elisabeth’s reign (1558-1603) the following minimum size limits were set by law: 10 inches (appr. 25 cm) for pike (Esox lucius), 16 inches for salmon (Salmo salar), 8 inches for trout (Salmo trutta) and 12 inches for barbel (Barbus barbus) and it was illegal to take, possess, or sell any undersized fish or fish caught out of season (Wright 1858, cited in Policansky 2002). On the River Thames, by the 1890 bylaw No. 7, required that “No person shall fish for pike with any device or tackle that does not admit of the pike taken therewith being returned to the water without injury” (Wheeley, 1897), cited in Policansky (2002). The law implicitly required Catch & Release to some extent (hereafter C&R) if an angler catches a fish too large or small, or is out of season, or is of a species that is totally protected, the law required it to be released alive and unharmed. The British seems to be the first practice voluntary and regulatory C&R. The tradition of releasing fish in America appears to be established in the last third of the twentieth century. Lee Wulff (1905-1991) was one of the pioneers of recreational fishing in America and considered as the father of the C & R movement, although there was others angler-authors before him advocating angling conservation ethics and C&R fishing (Radonski, 2002). Wulff’s book “Handbook of freshwater fishing (1939) is considered as one of the classic works of recreational fishing, where the principles of C&R fishing are described.

Increased popularity of recreational fishing led to declining populations of popular fish species worldwide. Fish stocking was, and still is in some cases, commonly used as a mitigation attempt to sustain heavily exploited fish populations or populations affected by hydropower installations in rivers and lakes. The solution of growing fish in hatcheries and dumping them in lakes and streams met opposition amongst subgroups of fishermen who preferred to fish for wild fish. Also, to reduce costs of running hatcheries was a major factor. As the knowledge of biodiversity and the need to conserve native species and populations increased, these findings drove the hatchery-resistance further. Anti-attitudes for fishing on stocked fish populations emerged with time and, as a consequence, the voluntary C&R – option became more pronounced among certain groups of fishers (Bryan, 1977). A new norm was emerging. The early regulations were based on minimum size, and/or slot- limits or daily quotas. Increasing demand and competition in recreational fishing, especially in trophy streams (e.g. rivers containing large-sized fish), further drove the C&R idea. Anglers became more ecologically sensitive and instead of quitting angling, the best solution was to “recycle” the fish. C&R has become a worldwide practice, but also a commonly used management tool for regulating harvest in recreational fishery, recently also in Scandinavia, cfr. Stensland, Aas, and Mehmetoglu (2013).

Management of closed populations (ponds and smaller lakes) can be less challenging than management of complex watercourses especially those with migratory populations. The productivity, in terms of produced biomass, can differ substantially, often depending on the harvest rate. Both production and harvest rate can be expressed as biomass (metric kg produced or harvested / area unit). The landowners are responsible for management of the resource when it comes to inland freshwater species. Recreational fishing regulations can be selective for species, certain life-stages (fish migrating to spawning grounds or aggregating in foraging areas) or length classes. 

The toolbox

Important management tools and regulations for fishery management includes: licenses and permits, size limits, creel or bag limits, only C&R fishing, seasonal restrictions and closures, area restrictions and closures and gear restrictions . All regulations have the potential to reduce total fishing mortality, but these regulations might also aim to help reach other objectives for the fishery, such as enhance angler benefits, reduce social conflicts, and ensure justice/fairness among groups. Although they are of varying effectiveness, it is possible to influence the sizes and kind of fish that are caught in relation to season. Except from rivers containing anadromous salmonids such as Atlantic salmon (Salmo salar), sea trout (Salmo trutta) and Arctic char (Salvelinus alpinus), there are not many examples from Norway of harvest models where productions estimates and thresholds of the total harvest for recreational inland fisheries, as we find in the commercial fisheries. Some exceptions are the long term studies of the lakes Øvre Heimdalsvatn (Jensen, 1977), Femunden (O.T. Sandlund et al., 2004; O. T Sandlund & Næsje, 1989) and Sølensjøen (Museth, Sandlund, & Borgstrøm, 2007). Most regulations in inland waters are restrictions on minimum size and the individual fishermen’s off-take on a daily or seasonal basis, without any restrictions on number of permits sold or modeling of the annual production.  The only examples, beneficial to recreational fishing, is from some lakes with stunted populations of common whitefish (Coregonus lavaretus) or Arctic char, where population reduction (by removal of small individuals) are done by strong harvest using bend-net like fish traps (storruse).

C&R is one of a set of management tools available for fishery managers and must be viewed in that context, although C&R often is derived from other regulations, such as minimum size limits or daily limits. There are two types of C&R; voluntary (the individuals own choice, driven by norms) and mandatory (through regulations).

Crowding of fishermen on places famous for large or abundant wild fish has been recognized as a problem in many waters. Limitations on licenses and permits can be a helpful tool to avoid such crowding. There are also common in rivers containing salmonids to restrict the number of permits on a specific water/stretch or pool at the same time, often on day by day basis or for a longer time span.
Size limits on fish are normally a defined minimum size, e.g. only allowed to take fish with length more than 30 cm, but upper limits can also be implemented. An example of the latter is from the eastern Canada where a federal legislation enacted in 1984 requiring anglers to release all Atlantic salmon larger than 63 cm fork-length (Wilkie et al., 1996) to maintain angling in declining populations. Any fish outside the defined size-limits must be released, which can be seen as a mandatory C&R regulation.  Restrictions with both minimum and maximum lengths are usually termed “slot-limits”. The basic idea with slot-limit regulations was to provide protection for individuals during their growth- and reproductive phase, so they not were removed from the population.

Creel or bag limits are restrictions on the number of fish that can be taken. These terms must not be confused with daily quotas or limits, since a creel or bag limit also can be set for a longer time period, a season or a week. In many Norwegian salmon rivers, there are now common to have a daily limit of fish that can be taken (1-2 salmon/day), combined with an annual quota of, say 10 fish per year, to reduce the total harvest rate. Some variations on seasonal quotas can be that only 3 salmon larger than a given measure (e.g. 80 cm) can be taken. More information will be provided when describing conservation limits later.

Seasonal restrictions (and closures) are set to avoid overharvesting. In Box 1, fishing rules for the popular Søndre Rena river where trout and grayling are popular species is shown. There are combinations of restrictions with minimum and maximum size and daily limits per species, gear restrictions and also differences in daily limits for catch of wild and stocked trout.

Area restrictions and closures can also be implemented. In a highly popular salmon river in Norway, the River Alta, only fly fishing (gear restriction) is allowed after midsummer (23rd of June) and throughout the season. In addition, in the two upper zones of Alta (Sautso and Sandia), C&R fishing only is allowed. All fishing is exclusive by only 1 rod per stretch at time, but anglers can share the rod. Before midsummer, there are no restrictions on gear, number of rods (but only locals can fish) or fishing area. Fishing in a defined area close downstream hydropower dams during spawning season for certain species are often prohibited. Other restrictions can be that only fly fishing is allowed or restrictions on hook size, only use of barbless hooks etc.

BOX 1. Fishing rules for Glomma, Søndre Rena m/Løpsjøen to Storsjødammen, Åsta, Julussa og Søre Osa to Valmendammen in Åmot municipality: Restrictions on numbers and size: Søndre Rena, upstream Løpet power station: Trout: No limits on numbers or size of stocked trout from the hatchery (adipose fin are cut). Allowed to keep 1 wild trout per fisherman/day. Wild trout of length ≥40 cm shall be released. Grayling: Only 1 grayling per fisherman/day. Grayling of length ≥40 cm shall be released. Søndre Rena downstream Løpet power station: Trout: No limits on numbers or size of stocked trout from the hatchery  (the adipose fin are cut). Allowed to keep 3 wild trout per fisherman/day. Wild trout of length ≥40 cm shall be released. Grayling: Allowed to keep 3 grayling per fisherman/day. Grayling of length ≥40 cm shall be released. Glomma: Minimum catchable size for trout and grayling  is 25 cm. Fish below minimum length/ over maximum length shall be released also if harmed. Gear restrictions: Søndre Rena: • Use of baitfish is not allowed. • Barbless hook shall always be used (or hook where the barb is crimped and deactivated). • Use of worms in Søndre Rena is only allowed if circlehooks is used.

Game management

The Norwegian history of influential game laws describes pretty well the development of regulations for harvesting game in Norway. The most efficient way of reducing harvest is to ban it, but history shows that that is difficult, even for ruling kings (box 2). Through the first half of the 20th century in Norway, different regulations were implemented by law, and most of them concerning hunting seasons. The game act of 1981 sets a new milestone in Norwegian game management. The purpose of regulations changes from a harvest and resource based management (1800-1900’s) to a conservation based management. The principle was now protection, “unless otherwise prescribed by statutory law or by administrative decision issued in pursuance thereof” (The Norwegian wildlife act 1981). In United States there were initially 5 standard regulatory components that comprise hunting regulations in the 20th century: (1) timing of the season and opening date, (2) season length, (3) sex/age –specific harvest designation, (4) bag limit/quotas (day or season), (5) legal hunting/harvesting devices.

Although the ecological systems of fish and game are very different, there are many similarities in the regulatory actions applied in the management. Regulations of time (Opening date, season length and season closure) are probably the most common management action applied to both fish and game. Especially the seasonal closures during spawning or breeding periods are regarded as important management actions and such closures are often regulated in the national legislation. Regulations of devices and gear are also widespread for both fish and game.

The regulations were adjusted through the years according to contemporary understanding of the abundances of game (Connelly et al., 2005). By regulating hunting periods only, as in Norway, without actually knowing how many animals that are harvested there was a great possibility for the harvest to become unsustainable. The American strategy could also be unsustainable if the number of hunters were limitless.

Quotas or bag-limits were first introduced in Norway for ungulates in 1951. The quota was given according to the size of an area (ex. 3000 daa equals one moose), so in theory it was possible to estimate a total quota for all of Norway. This is in fact a good strategy if population estimates forms the basis of the area requirement. However, for distinct age-structured populations such as ungulates, the sex and age of harvested individuals also plays an important role and biased (for instance strong harvest of productive females) harvest may be unsustainable.  With the aim of increasing the productivity in the ungulate populations a more nuanced and selective harvesting strategy (sex- and age-specific quotas) were introduced in 1967 (R. Andersen et al., 2009). This regime together with other factors (predator extinctions, climate- and agriculture- changes) coincides with a considerable increase in moose bag statistics, and later red deer (Cervus elaphus) bag records (Figure 2). Moose harvest changed from a rather marginal economic activity to an almost industrial-like meat industry. Today, regulations are also used as tools to reduce damage caused by ungulates like game-vehicle collisions, damage to crops and forests and over-browsing/grazing. This ungulate example is the only example from the history of Norwegian game management where specific harvest models are applied at a large scale.

A major goal for successful management of harvested populations is to find harvesting strategies/models that are sustainable (Aanes et al., 2002). Sustainability is a multidimensional concept with ecological, economic and social dimensions. Wildlife ecology has primarily focused on biological and ecological aspects such as population dynamics and harvest rates. Economic and cultural aspects are seldom considered, but the transition from MSY to OSY has brought wider societal aspects into account in some cases (i.e. areas with lots of game-vehicle collisions or crop damage). Harvesting should occur in a way that not affects the populations’ viability or reproductive success the next year or in the long run.

Small game hunting – sustainability?

One definition of sustainable harvesting is “a yield that can be taken year after year, without jeopardizing future yields” (Sinclair et al., 2006). The current regime in Norwegian game management is aiming to be sustainable, at least according to the wildlife act of 1981 and the biodiversity act of 2009. As we have discussed, there is high control of details in ungulate harvest management, cfr. selective harvest and quotas regulated by the wildlife act. Small- game management with the exception of hunting seasons is however delegated to each landowner without any details controlled by the authorities. Increased knowledge and acceptance of the negative effects of overexploitation on small game populations have led to development of harvest restrictions, such as bag-limits, narrower hunting periods (locally initiated) and controlling hunting effort (Willebrand, Hornell-Willebrand, & Asmyhr, 2011), which is practiced in Sweden and now also in the two northernmost counties in Norway (Nordland and Finnmark) for a highly popular upland small game specie; willow ptarmigan. We will in the section on harvest models for game go deeper into the details on the moose harvest strategy and into different harvest models that are applied to and/or possibly can be applied to willow ptarmigan harvest.

Figure 2: A model of sex-and age specific harvest was introduced for large ungulates in 1967 and resulted in a significant increase in population size and harvest rates in the following years. Source: (Ree, 2008; Statistics Norway, 2011).

BOX 2. Milestones in Norwegian game management 1200-today The first known regulations of game in Norway are written in Magnus Lagabøter’s law of 1274. One important regulation was the prohibition to pursue moose (Alces alces) on skis, probably because this was efficient and that moose was regarded as threatened. Later, King Christian IV of Denmark’s law for Norway of 1604 contained regulations of moose and red deer harvest. Landowners were only allowed to bag two individuals on their own land. The moose restriction was repealed in 1688 due to viable populations. In the start of 1700s, there were huge concerns about the population viability of moose (again) and wild reindeer (Rangifer tarandus) which previously harvest not had been regulated. In 1726, there was implemented a seasonal closure in hunting season between December 10th to May 15th for moose and reindeer in the eastern parts of Norway because of overexploitation. From 1730, the Danish king sent a legislative decree about prohibition of shooting or trapping big game in pitfalls. Pitfall methods were efficient, but also very important for farmers at that time. Only three years later, the same king sent a new decree to ban all harvest of small game (hare and grouse species) during breeding season. After massive pressure on the king, all kinds of regulations were annulled a few years later. A period without regulations and high density of guns in the populations caused unsustainable harvest levels. Despite new protections of moose in 1770, all big game populations were low towards the turn of the century.  Through the 1800’s, hunting for food became less important, and recreational harvesting was introduced.  Even though game populations were extremely low, there was a lack of motivation in the society to regulate the populations. A more scientific approach turned out to characterize the management later in the 1800’s. The biologist (and hunter) Halvor Rasch designed the first “real” game act in Norway. He acknowledged the “human right” to hunt, but also the need to regulate the increasingly more efficient hunters. The law was carried out by the Swedish king in 1845. Hunting periods for important game species such as moose, red deer, hare and grouse was settled based on “important zoological principles”. The law of Rasch in 1845 and the decision about land owners exclusive rights to hunting in 1899 sets the foundation of modern game management in Norway. Many of the principles applied in the 1800’s were present until late 1900’s when the wildlife act of 1981 adopted(Source: Andersen et al. 2009).

Harvest models for game

In this section we will concentrate on management and different harvest strategies/models applied to, two important game species in Norway, willow ptarmigan and moose. The population dynamics of the species is very different, with large temporal variation in willow ptarmigan abundances (Kvasnes, Storaas, Pedersen, Bjork, & Nilsen, 2010) and less variable moose abundances. The differences partly due to different reproductive strategies (willow ptarmigan is r-selected and moose k-selected), thus causing willow ptarmigan populations more exposed to stochastic variability and moose populations to be easier controlled by harvest. This difference has also resulted in quite different management strategies.

Moose management in Norway is in many ways a success assessed against the overall goals and objectives set for this resource. The moose populations in general are relatively healthy and produce many tons of meat for human consumption and the harvest is of significant economic importance, especially for landowners (R. Andersen et al., 2009). However, high densities of moose in many parts of Norway are also a concern for forestry and for traffic safety, as well as for animal welfare. Management has acknowledged that different ages and sexes have different demographic value and that this knowledge should be used when estimating and composing quotas. Quotas are set to percentages of calves (assumes 1:1 sex ratio), adult females and adult males. For instance if there is need to reduce the population to a lower level because of over-browsing or to reduce moose collisions it is possible to adjust the adult female proportion up for a faster reduction in productivity. As an important basis for the quota-decisions are the moose observations from previous years. These observations are used to measure the effects of different harvest regulations.  The Norwegian management strategy for moose is even more flexible if combined with goal-oriented management plans over several years because then the quota can be distributed over the whole period.

Willow ptarmigan management in Norway is extremely diverse and less knowledge based. Apart from the national seasonal harvest limits, all responsibility is given to the landowner independent of size of the estate.  Harvesting rather unrestricted within the seasonal limits has historically been regarded as an activity that only takes out a doomed surplus of the populations (Pedersen & Karlsen, 2007). This view is still present among many hunters and landowners, but an increasing majority in these groups is now getting more convinced that hunting of willow ptarmigan have the potential to be unsustainable. This change in understanding is partly due to the obvious reduction in annual harvest bag. Despite stable number of hunters the annual bag has never been as low as in 2012. But scientists were one step ahead on the “worry-scale” and provided new knowledge about the effects of hunting already during the 1990’s (Kastdalen, 1992; Pedersen et al., 2004; Sandercock, Nilsen, Broseth, & Pedersen, 2011; Smith & Willebrand, 1999). The results show quite clearly that harvesting may add to the natural mortality in willow ptarmigan in contrast to the “old view” of harvesting from a surplus. The effects of hunting are probably scale-dependent as hunting pressure varies across the mountain region. The reduction in annual bag is probably also affected by factors such as bag-limits and other restrictions recent years. But there was a reason for introducing such measures!

Through history, little effort has been put into applying specific harvest strategies on small game populations in Norway.  With harvest strategies we mean, knowledge-based strategies that aim to estimate yearly quota or efforts to stabilize and/or increase the populations at/to a desired level or within some limits. Such models is applied on small game populations in Sweden (Västerbotten, Jämtland and Norrbotten countyboards  2012) and Great Britain (Hudson, 1985; Jenkins, Watson, & Miller, 1963). Three general strategies have been proposed to achieve sustainable harvest levels of vertebrate populations; constant, proportional and threshold harvesting (Sinclair et al., 2006) (Box 3). Important knowledge required before implementing harvest models is to know how the system works without hunting, how hunting affect the populations and for some models, monitoring of some sort is decisive to assess population parameters (Aanes et al., 2002). For many years, hunting areas for willow ptarmigan have been monitored before hunting season in Norway. The first efforts were mostly to evaluate the chick production, primarily to forecast the hunting season for hunters, but now area-specific density estimates and production numbers are estimated based on approved methods (H. Solvang, H. C. Pedersen, T. Storaas, P. Fossland Moa, & J. I. Breisjøberget, 2007; Thomas et al., 2010). Such estimates can form a basis for the implementation of harvest models to specific areas. 

The first efforts, to our knowledge, to implement a thoroughly considered harvest model are the introduction of hunting effort regulations on state-owned land in northern Norway.  The idea is adopted from the Swedish system and assumes some relationship between effort and harvest rate (Sinclair et al., 2006; Willebrand et al., 2011). Swedish studies has shown that a hunting pressure of three hunter days per km2 equals a harvest rate of 25%, while 5 hunter days/km2 equals 50% harvest rate (given a daily limit of 8 ptarmigan per day).  A hunting pressure less than three hunting days/km2 are considered to be sustainable, and the management action is to close the area for non-resident hunters when the number of hunting days equals 3 hunting days per km2 (in combination with a daily limit of 6 ptarmigan per day). If 55000 Norwegian ptarmigan hunters hunt in average between 10-14 days, it equals 550000-770000 hunting days in total. The area suitable for ptarmigan hunting in Norway is estimated to be 156 000 km2 (H.C. Pedersen pers.comm), giving a total national hunting pressure of 3,5 - 4,9 hunting days/km2 for ptarmigans. From an OSY perspective, it would be better to reduce the daily limit, than reduce number of hunters.  The drawback can be crowding in popular, easy accessible areas. Thus, limitations on hunter numbers may be necessary.

BOX 3. Different harvest strategies for willow ptarmigan Constant harvest strategy: A constant number of individuals are removed every year. One advantage of using a fixed quota, is that no population estimate is requires, provided that the quota is kept very small. To achieve an optimal quota (economically and sustainable), population estimates are reqired.  The risk of unsustainable harvest is considerable if harvest rates are high under low population sizes (Lande, Saether, & Engen, 1997). The strategy is also inefficient if the populations exhibit large temporal variation in abundance (Sinclair et al. 2006). Proportional harvesting: If  a constant proportion of the population is harvested each year, depending on the proportion the population will stabilize any level between extinxion threshold and unharvested population levels . This tactic may also be carried out without having population estimates available, because a fixed harvesting effort often approximately leads to harvesting a given proportion. The latter assumes that yield tracks density, the system produce a high yield when abundances are high and a low yield when abundances are low. If the harvest is not proportional to effort this strategy will require population estimates (Aanes et al. 2002). Restricted proportional harvest is a more conservative approach one may consider if population estimates are uncertain (Aanes et al. 2002). The idea is to introduce an upper limit for the proportional harvest, a maximal bag-limit. Ex. 30% harvest restricted to 200 individuals. A fixed proportional harvest have the potential to be sustainable for willow ptarmigan if harvest is restricted to 15% (Sandercock et al. 2011).     Threshold harvest or Fixed escapement harvest: The general idea is to harvest only the” surplus” of individuals above a threshold. This will make sure population never falls below the threshold. If the threshold is set at carrying capacity, no population estimates are required, but to optimize the threshold such estimates are required. This strategy may also face a fundamental practical problem; harvest may be canceled some years. For willow ptarmigan it has been suggested a threshold harvest based on reproductive surpluses above 2.5 chicks/pair (Sandercock 2011, Kastdalen 1992).

Uncertainty and controllability

Management of fish and game for recreational purposes is very much about handling uncertainty and managing people. Harvest models are developed as a tool to reduce uncertainty, but require some kind of knowledge about the managed species. Harvest models are also quite useless unless they are linked to clear, operationalized goals and objectives. If we are not able to evaluate the outcome, uncertainty comes into play and must be considered. In figure 3, we show possible management strategies under varying uncertainty and controllability of the natural resource. Without adequate knowledge about the managed species, there can be a need for quick responses to sudden changes in the population size or structure. Some possible management strategies can be derived from figure 3.

Figure 3. Some possible management strategies as a function of uncertainty about size and structure and the management’s ability to control the natural resource through management actions/regulations. Modified from Peterson, Cumming, and Carpenter (2003).

Adaptive management models have been proposed to meet these challenges given that: (1) the management goal is clearly defined, (2) the outcome can be evaluated (although there can be high degree of uncertainty) and (3) proper actions can be taken if needed (controllable). One example that can fit in here is the mid-season evaluation in Norwegian rivers containing Atlantic salmon (see description of conservation limits, described later). Adaptive management has several definitions, but common for all is the description of a process where management of natural resources improves by learning from the current management regime, a “learning while doing” approach. Williams, Szaro, and Shapiro (2009) gave the following definition of adaptive management:

“Adaptive management [is a decision process that] promotes flexible decision making that can
be adjusted in the face of uncertainties as outcomes from management actions and other events
become better understood. Careful monitoring of these outcomes both advances scientific
understanding and helps adjust policies or operations as part of an iterative learning process.
Adaptive management also recognizes the importance of natural variability in contributing to
ecological resilience and productivity. It is not a ‘trial and error’ process, but rather emphasizes
learning while doing. Adaptive management does not represent an end in itself, but rather a
means to more effective decisions and enhanced benefits. Its true measure is in how well it
helps meet environmental, social, and economic goals, increases scientific knowledge, and
reduces tensions among stakeholders.”

In situations with less uncertainty about the resource under management, a goal-orientated management regime could be more suitable (Figure 3). The situation is considered to be under optimal control, and the current Norwegian management system of ungulates such as moose, red deer and wild reindeer may fit in here.

Scenario planning is a strategic planning method to make flexible long-term plans. This is recommended in situations where the resource is considered as uncontrollable and there is high degree of uncertainty (Figure 3). Scenario planning may involve aspects of system thinking, specifically the recognition that many factors may combine in complex ways to create sometime surprising futures. This way of thinking can be relevant in situations where biological invasions of non-native species or diseases are at risk. A system thinking used in conjunction with scenario planning leads to plausible scenario story lines because the causal relationship between factors can be demonstrated. The method also allows the inclusion of factors that are difficult to formalize, such as novel insights about the future, deep shifts in values, unprecedented regulations or inventions.

The precautionary principle or precautionary approach states that if an action or policy has a suspected risk of causing harm to the public or to the environment, in the absence of scientific consensus that the action or policy is harmful, the burden of proof that it is not harmful falls on those taking the action. This principle allows policy makers and mangers to make discretionary decisions in situations where there is low uncertainty, but a possibility of harm from taking a particular course (uncontrollable) or making a certain decision when extensive scientific knowledge on the matter is lacking (Figure 3). To some extent, management of small game in Norway may fit in here.

One of the primary foundations of the precautionary principle, and globally accepted definitions, results from the work of the Rio Conference in 1992. Principle no. 15 of the Rio Declaration notes:

"In order to protect the environment, the precautionary approach shall be widely applied by States according to their capabilities. Where there are threats of serious or irreversible damage, lack of full scientific certainty shall not be used as a reason for postponing cost-effective measures to prevent environmental degradation."

This definition is important for several reasons. First, it explains the idea that scientific uncertainty should not preclude preventative measures to protect the environment. Second, the use of “cost-effective” measures indicates that costs can be considered. This is different from a “no-regrets” approach, which ignores the costs of preventative actions.

From harvest models to harvest plans

The ecological knowledge that was derived from harvest models was applied by management through gradually developing species-specific management plans or for watercourses, which also regulated directly or indirectly the harvest rates. Soon, it became clear that the demand for better data on the harvested populations was necessary to improve the controllability and reduce the uncertainty for management purposes (Cf. Figure 3). Here, we give some examples of status in recreational fishing, big game- and small game management.

Recreational freshwater fishing

Estimates of the biological production and sustainable harvest rates have been carried out for decades in marine fisheries, and for lakes and rivers subject to fishing. In Norway, harvest plans developed in the 1970s and grew more abundant later. There are now numerous examples on harvest plans for fish with restrictions on harvest rates out of the wish to maintain a certain harvest and population structure, but estimates of the overall biological production and total harvest are seldom considered or described.
In many (regulated) rivers, fish has for several decades been monitored in fish ladders related to hydropower dams or by other counting devices during their upward migration to feeding- or spawning grounds. There are examples that fishing in some instances are not allowed before a certain amount of fish has entered the river, to ensure a sufficient spawning population (Dorner, Peterman, & Su, 2009).  Voluntary or mandatory reporting of catch on a daily or weekly basis is also an important tool for managers to keep control on harvest rates. This is now a legal demand in Norwegian rivers with anadromous salmonids.

The latest progress in management of Atlantic salmon in Norway, is the adoption of the theory of a reference point (similar to a threshold), which is well established for many commercial fisheries. In leisure based fisheries for freshwater fishes, the reference point is known as a “Conservation limit” (CL), sometimes called a “Spawning target”. CL is basically the (estimated) biomass of female salmon in a river necessary to ensure the population to attain the carrying capacity (yielding maximum recruitment; the spawning target). CL estimates are based on reported catch and exploitation rates, and have been established as conservation limits for each of the 439 Norwegian salmon populations since 2008.

The introduction of CL lead to introduction of a mid-season evaluation from fishing season 2009 in rivers with defined CL. Mid-season evaluations can serve as an example of adaptive management in recreational fishery. The general fishing season for salmon starts 1st June and ends 31st August, with a few exceptions. After the first half (mid of July), fishing season are evaluated where the fishery management consider the possibility for reaching the CL based on the total catches so far in relation to fishing conditions, the biomass of females and also size groups.  Management actions shall be taken, if it is considered possible that the CL goal not will be achieved. Commonly used actions so far is to adjust the daily quota or implementing other restrictions such as only C&R of female salmon throughout the rest of the season. Season closures have to our knowledge so far not been enforced after a mid-season evaluation.

CL-models and the implementation of mid-season evaluations has also shown to improve the catch statistics and stimulated data acquisition for management purposes in many of the Norwegian salmon rivers (Forseth et al., 2013).

Big game hunting

For large ungulates (Moose, Reindeer and Red deer), there are regulations by law to develop multi-annual management plans for the managed population (hereafter: population plans). Harvest plans with 3-5 years timespan are made for smaller units within the population plan area. These are based on the population plan with clearly defined goals for population size, structure and sex- and age-distribution of the harvest. Uncertainties about the population’s performance are reduced by monitoring harvest statistics and population dynamics. For ungulates in Norway, age- and sex- structured harvest models (based on life tables) have been used for more than 2 decades. A national monitoring program for large ungulates, such as moose, red deer and wild reindeer was established in Norway in 1991. In this program, data on body condition (carcass mass), fecundity (from ovaries), reproductive rates (helicopter counts) and recruitment rates (from hunter observations) are collected annually in selected areas. In addition, hunters are reporting moose (and red deer) observations from most municipalities in Norway with moose hunting. The basic idea of this moose observation program is to provide the management with information about the variation in recruitment rates (proportion females with calf/calves, proportion females with twins), population sex structure and population density (seen moose per hunter-day). Based on this information, multi-annual harvest plans are developed, and previous population plans are evaluated in relation to the observed population development.

Small game hunting

Harvest data are commonly used as proxy for count data, especially in studies of long-term temporal and spatial patterns of population fluctuations (Ranta, Lindstrom, Linden, & Helle, 2008). For small game, there are very a few examples of harvest plans. Management of ptarmigan and other small game species in Norway have generally not, until recently, relied on research-based data and monitoring of population sizes and distribution. Since mid of the 1990, line transect counts has gradually developed as an annually monitoring program for willow ptarmigan. Now, more than 200 estates/larger hunting areas are monitored annually (H. Solvang, H. C. Pedersen, T. Storaas, Pål. Fossland Moa, & J.I. Breisjøberget, 2007). Data on density and chick production is important parameters for managers in the pre-harvest planning.

If the principles with spawning targets from management of Norwegian Atlantic salmon are transferred to grouse management, it is possible to estimate the number of birds that should remain after harvest to maximize an areas potential recruitment capacity prior to next breeding season. Thus, the focus will be on the size of the breeding population, not the proportion that can be harvested. By implementing a concurrent evaluation after the first weeks of the hunting season, managers will have the possibility to further adjust harvest levels in relation to the reference point. Mid-season evaluations for small-game species are rare, but a few examples of adjusting/restricting harvest rates after the first 2-3 weeks of the hunting season have been found the recent years in Norway. Then, it is possible to adjust the harvest rate in relation to both the population monitoring results prior to hunting season and the current harvest rate for the first weeks of the hunting season. Ringebu fjellstyre is one of the management units who have implemented this practice.

Another approach is to monitor the effort, regarding accumulated hunting pressure, expressed as hunter-days/km2. When reaching a pre-defined level, normally between 1-5 hunter-days/km2, the hunting stops. This is now the common management practice in the two northernmost counties in Norway.

Conclusions (and recommendations)

The introduction of harvest models has led to that several improvements in management of fish and game. First, the development of harvest plans, describing the management goals, and desired population structure and -size after harvest and in a long term perspective was an improvement. For small game species, often with shorter lifecycles, the lack of management plans is still clear. However, there are advances in this field as well, by approaching a more adaptive management strategy. By including mid-season evaluations in small game management, the management has become more adaptive. Managers are now somewhat able to quickly respond to sudden changes in the harvested population. Secondly, improvement of catch statistics and data acquisition for management purposes had increased substantially, especially for rivers containing salmonid species in Norway, but also for game, such as ungulates. Thirdly, population monitoring programs are now well established for many fish and game species. By implementing biological reference points, managers have defined a management goal, reduced uncertainty, and small game management is then moving towards a more goal-oriented approach, as we find for big game species. A reference point is in accordance to the Biodiversity Act intentions, and can further serve as a normative standard on a hunting terrain level (O. Andersen & Thorstad, 2013). We also conclude that recreational management of fish and game over time has approached each other in the way they manage their resources. However, there are still things to learn from each other. To our opinion, this is knowledge based, sustainable resource management.

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