From the beginning of the 20th Century,the management of most ecosystems on the planet includes statistical analysis of data of game harvesting, in order to study and record game populations. Depending on each case, the most significant results of this type of analysis can generate: density indicators (Grotan et al. 2005, Mysterud & Ostbye 2006, Imperio et al. 2010), abundance indicators (Cattadori et al. 2003), as well as indicators of population dynamics, trends and demographic rates (Willebrand & Hornell 2001, Cattadori et al. 2003, Hornell 2005),amongst other things.

Data concerning game population development, which have been recorded using the same methodology for many consecutive years, in conjunction with the study and analysis of environmental parameters, comprise the key to understanding and identifying the mechanisms which bring about changes in populations (Royama 1992, Turchin 2003, Ranta et al 2006, Imperio et al 2010). However, a fundamental concern, expressed repeatedly since 1970, is to what extent the recorded data on harvesting really reflects the condition of a game population, since it is probable that the low density of specific populations is underestimated or the high density of populations is over estimated, as a result of changes in hunting endeavour (Gilpin 1973, Weinstein 1977, Winterhalder 1980, Lambin et al 1999). However, the worldwide scientific community upheld the validity and singularity of using data from harvesting, citing a plethora of significant papers. Briefly, the published scientific papers which respond to this concern, as well as proving the validity of using harvesting data, operate on 2 axes and deal with the following:

Α). Firstly, precise readings of a population are not possible in nature, and only estimates of their size can be made (Krebs 1999). In addition, studies which aim to monitor changes and trends in the population of a species with direct recordings in the countryside over a long period, whether in game or more generally in fauna, are very rare (Fryxell et al 1999, Cattadori et al 2003). This is because budget, human effort and technical dynamics which are spatio-temporally necessary in the countryside, render such studies prohibitively unwieldy and unfeasible (Lancia et al 1994). Consequently, indirect methods of recording populations are frequently used, such as recording droppings, emetic pellets, audio recordings, recording particular signs which different species leave in their habitat, photography of fauna using a photoelectric cell and, of course, harvesting data (Mayle et al 2000, Welander 2000, Engeman et al 2001, Wilson & Delahey 2001, Engeman 2005, cevedo et al 2006, Acevedo & Villanueva 2006, Acevedo et al 2008; 2010). Of all these indirect methods, the most common, effective and frequently used in long term studies of game population dynamics is that of harvesting data (Cattadori et al 2003, Acevedo et al 2008, Ranta et al 2008).

There are two reasons for this. The first is that it is only hunters who have been active in the countryside for so many years, long before specialist scientists started studying wild life. It is hunters, therefore, who have used this renewable natural resource for centuries, comprising the populous social group which has most frequent interaction with the countryside and nature and has specialized in using this natural resource with reliability in relation to its administration. In consequence, the only data of game populations derive from records kept during hunting activity in various parts of the world, as hunting is a legitimate global activity with a century’s old tradition.

Some scientific papers will now be referred to as they are impressive for the volume of harvesting data which is analysed and also for how far back this collection of data goes: By studying the number of white geese (Chen rossii) which have been harvested from 1918 until today in North America, conclusions have been drawn about changes in population, the areas they have moved to, reproduction and the age structure of the population (Moser 2001). Populations of Caribou (Rangifer tarandus) have been studied from harvesting of the species in North America and Greenland from the beginning of the 20th century until today (Forchhammer et al 2002) while similarly, in Southern Italy from 1878 until today the populations of 5 species of ungulates have been studied using the same method: Fallow Deer (Dama dama), roe deer (Capreolus capreolus), wild boar (Sus scrofa), deer (Cervus elaphus) and antelope (Boselaphus tragocamelus) (Imperio et al 2010). The Red grouse (Lagopus lagopus) has been studied in Norway through its harvesting from 1940 (Hornell 2005), and harvesting data for the Canadian Lynx (Lynx Canadensis) and the American Hare (Lepus americanus) have been studied in Canada since 1930 (Cattadori 2003). The Wood Grouse (Tetrao urogallus), Black Grouse (Tetrao tetrix) and Hazel Grouse (Bonasia bonasia), have been studied through harvesting data since 1960 in Finland (Ranta et al 2008), and since 1960, the population of the Common Eider (Somateria mollisima) has also been studied in Denmark (Christensen 2005). In addition, special European studies using harvesting data have been conducted and these studies have indicated population trends of specific species all over the Palaearctic. In particular, simultaneous studies were carried out on the factors which influence deer harvesting spatiotemporally (Cervus elaphus) in 11 different countries (Milner et al 2006), as well as the population dynamics of the ferret (Martes martes) in all Scandinavian countries (Helldin 2000). The studies referred to are the most significant ones chosen from all studies carried out globally using harvesting data relating to population dynamics of game species.

The second reason for using an indirect method of monitoring game populations through harvesting data, which is the most effective and frequently used for the implementation of studies on population dynamics, is its constant and unimpeachable methodology. Apart from the fact that harvesting data are older than any other, as they derive from all hunting areas in every country, thereby covering all areas inhabited by a species, they are also always recorded in the same manner and with the same amount of effort. In addition, hunters are the only social group which consistently goes about its activity in the countryside with passion and respect and are therefore in a position to observe game populations and provide data on harvesting with a guaranteed methodological approach.

Β). In the first category of scientific publications referred to above, the uniqueness of harvesting data and their enduring stable methodology were presented, as well as the reason for their wide geographical origin. The second axis presents scientific papers which prove that harvesting data accurately reflect the state of a game population.

A strictly scientific approach showing how accurate an index is requires the index to be linearly associated with the true rate of abundance, density and population trends, depending on each case being studied (Gibbs 2000, Imperio et al 2010). On the one hand, as has already been mentioned, direct records of game populations in the countryside and, more generally, of fauna populations over a long period of time are rare (Fryxell et al 1999, Cattadori et al 2003). On the other hand, the few long term records of populations which have been carried out through observation in the countryside have also led to the creation of abundance, density and population trend indicators, in the absence of a precise knowledge of the population (Krebs 1999). Consequently, the only way to examine whether harvesting data reflects the true state of a population is to compare indicators deriving from harvesting data with indicators deriving from direct observation in the countryside, being particularly careful to ensure that they are taken from the same time frame and the same geographical area (Cattadori et al 2003, Imperio et al 2010).

At the beginning of 2010, a paper published in the scientific journal Wildlife Biology (Imperio et al 2010) carried out a comparison of harvesting data with records of population in the countryside. The authors state that apart from their data, no other recorded data exists on large populations of ungulates with direct records of numbers in their natural state for so many consecutive years (37 to 51 years depending on which of the 5 species were being studied), or for harvesting data. This is because the region of Castelporziano in Southern Italy, where the study was carried out, is protected by special legislation. Throughout the region, population records have been kept for decades and harvesting records for even longer, almost since the beginning of the century. The authors show that for the five ungulates which were studied (Fallow Deer, Roe Deer. Wild Boar, Deer, Antelope) , the indicators which result from harvest analysis , using specific statistical adjustment, show a high correlation with population counts and are therefore believed to be valid for descriptions of abundance, density and trends in game populations.

A similar study was carried out by researchers using data from 92 different Red Grouse populations in the United Kingdom, for the years 1977 to 2000 (Cattadori et al 2003). Data were provided for a total of 92 independent populations based on records in the countryside for 30 consecutive years, as well as detailed harvesting data. In this instance as well, it was shown that recordings taken in the countryside showed high spatiotemporal correlation with harvesting data, thereby supporting the validity of harvesting data. It is worth noting that this particular paper relating to populations of Red Grouse was published in 2003 in the scientific journal OIKOS, which is regarded as one of the foremost ecological journals in the worldwide scientific community.

To sum up, there is no doubt that the use of harvesting data is a very useful tool for recording abundance, density and population trends in game species. In addition, apart from analyzing basic demographic population trends by studying harvesting data, other matters can be researched at the same time. For example, with parallel recording of the habitats of game and other parameters, the non-living factors which influence harvesting and population trends can be studied (Willebrand & Hornell 2001, Christensen 2005, Santilli & Gallardi 2006). The impact made by predators and density dependence factors on game populations can also be studied (Fryxell et al 1999) and a contribution to the study of epidemiology of certain species can be made (Acevedo et al 2005; 2007), to name but a few applications.

The most significant benefit of all, however, is how harvesting data, their organization and collection from hunting organizations in every country, together with their analysis and findings, comprise the strongest administrative measure for sustainable hunting activity and the conservation of the environment.



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