Sustainability of hunting, population densities, intrinsic rates of increase and conservation of Papua New Guinean mammals: A quantitative review

Biological Conservation 143 (2010) 1850–1859

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Sustainability of hunting, population densities, intrinsic rates of increase and conservation of Papua New Guinean mammals: A quantitative review Richard Cuthbert * Beacon Ecology, 84 Nottingham Road, Belper, Derbyshire, DE56 1JH, United Kingdom Royal Society for the Protection of Birds, The Lodge, Sandy, Bedfordshire, SG19 2DL, United Kingdom

a r t i c l e

i n f o

Article history: Received 15 November 2009 Received in revised form 29 March 2010 Accepted 7 April 2010 Available online 20 May 2010 Keywords: Marsupialia Papua New Guinea Demography Hunting Conservation

a b s t r a c t New Guinea’s mammalian fauna consists of a unique assemblage of relatively small sized (0.5–13.5 kg) marsupial mammals, the hunting of which provides a major source of protein for local communities. However, the impact of hunting and the influence of the marsupial life-history strategies on the sustainability of hunting are unknown. Anthropological studies of subsistence hunting and published life-history data for Australasian marsupial mammals were quantitatively reviewed to determine the major sources of game and annual harvest, and estimate intrinsic rates of population increase (rmax) and population densities. These data were used to estimate extraction versus maximum sustainable production (MSP) and make a preliminary estimate of the sustainability of hunting. There were significant negative relationships between increasing body size and decreasing rmax and decreasing population densities, which were further influenced by phylogeny and diet, and appear very similar to relationships found for placental mammals in Afrotropical and Neotropical forests. The estimated biomass of mid-sized marsupial mammals (923 kg/km2) in Papua New Guinea is also comparable with densities of placental mammals in other evergreen tropical forests. Intrinsic rates of increase ranged from 0.28 for tree-kangaroos (Macropodidae) and 0.29 for cuscus (Phalangeridae), up to 5.14 for bandicoots/echymipera (Peroryctidae). Estimated population densities ranged from 0.4–4.0 animals/km2 for long-beaked echidna (Zaglossus sp.) to 150–340 animals/km2 for ringtails (Pseudocheridae). Extraction rates of game in three studies averaged 23.5 ± 9.9 kg/km2/year, with cuscus and bandicoot species numerically comprising the main game, although cuscus are the most important source of protein. Rates of extraction in Papua New Guinea versus rates of production demonstrate that long-beaked echidna, tree-kangaroos and cuscus are likely to be hunted unsustainably. In contrast hunting of bandicoots and ringtails was lower than maximum production levels, and the high intrinsic rate of increase of bandicoots means that they can potentially provide a sustainable source of protein, in preference to scarcer and intrinsically slower breeding species. Ó 2010 Published by Elsevier Ltd.

1. Introduction Unsustainable hunting of wildlife is well established as a major threat to biodiversity in tropical forests (Robinson and Bodmer, 1999). While people have lived and hunted in tropical forests for tens of thousands of years exploitation of ‘‘bushmeat” and ‘‘wild meat” (Milner-Gulland and Bennett, 2003) is estimated to have increased in recent years (Robinson and Bodmer, 1999), due to a combination of increasing human populations, changing hunting technology and an absence of alternative sources of protein (Robinson and Bennet, 2000). As a result, hunting has been considered a more serious threat to the conservation of tropical biodiversity * Address: Beacon Ecology, 84 Nottingham Road, Belper, Derbyshire, DE56 1JH, UK. Tel.: +44 (0) 1767 693085. E-mail address: [email protected] 0006-3207/$ - see front matter Ó 2010 Published by Elsevier Ltd. doi:10.1016/j.biocon.2010.04.005

than deforestation (Redford, 1992). To date, most studies on the impact of hunting have been undertaken in South America, Africa and Asia. Studies from Australasia and Melanesia are rare or lacking all together. New Guinea, comprising the nation of Papua New Guinea (PNG) and the Indonesian province of West Papua, is the second largest island in the world and a priority area for biodiversity conservation (Mittermeier et al., 1998; Stattersfield et al., 1998; Myers et al., 2000). Over 65% of New Guinea is covered by tropical rainforest forming one of the world’s largest remaining forest tracts (Mittermeier et al., 1998). The population of West Papua and PNG total over 8.3 million people with a high proportion (87%) living in rural areas (PNG-NSO, 2000) and following a relatively traditional subsistence lifestyle. In these areas hunting of wildlife as a source of wild meat (as opposed to hunting and sale of wildlife for bushmeat; Milner-Gulland and Bennett, 2003), has and continues to provide a vital source of food and protein to local

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communities (Dwyer, 1985; Dwyer and Minnegal, 1991; Hide et al., 1984; Morren, 1986; Mack and West, 2005). Attempts to assess the impact of hunting in the tropical forests of Africa and South America have been able to draw on a considerable body of research relating to hunting pressure (e.g. reviews by Redford and Robinson, 1987; Alvard et al., 1997; Fa et al., 2002), the intrinsic rate of increase of hunted species (Robinson and Redford, 1986a) and the relationship between body-size, diet and population density of hunted species (Robinson and Redford 1986b, 1991; Fa and Purvis 1997). Hunting is of particular conservation significance for mammals (Alvard et al., 1997; Robinson and Bodmer, 1999), with larger bodied species most at risk due to their preferential capture by hunters (Bodmer et al., 1997) and the general association between increasing body size and decreasing reproductive rates and population densities (Hennemann, 1983; Damuth, 1991; Robinson and Redford, 1986a,b). In contrast, relatively few studies have investigated hunting in New Guinea and these are often from an anthropological perspective. Additionally, very few detailed studies have been undertaken on the distribution and ecology of New Guinea’s marsupial mammals. Unlike African, Asian and Neotropical forests, the mammalian fauna of New Guinea is dominated by relatively small-sized (most less than 2 kg in mass), arboreal and nocturnal marsupial mammals (Menzies, 1991; Flannery, 1995). How these ecological traits are likely to affect the potential impact and sustainability of hunting in New Guinea is unknown, and data on the intrinsic rate of increase of marsupial mammals and the relationship between body-size, diet and population density have not been tested. Such information is critical for the conservation management for a number of species in New Guinea where hunting is a concern: of the 12 species of tree-kangaroo (Dendrolagus sp.) present in New Guinea three are listed as Critically Endangered, four as Endangered and four as Vulnerable and in all cases hunting is listed as one of the principal threats. Similarly, all three species of long-beaked echidna (Zaglossus sp.) and the black-spotted cuscus (Spilocuscus rufoniger) are Critically Endangered with over-hunting reported as the main threat (IUCN, 2010). This paper makes the first quantitative estimate of reproductive rates and population densities of the abundant game species in PNG. Information from hunting studies is used to determine the main species of game and assess the potential scale of hunting. Using these estimates, this study assesses the sustainability of hunting in PNG, and identifies for which species conservation action and management is most urgently required.

2. Methods 2.1. Game species Game species were restricted to a subset of ‘‘mid-size game animals” that are reported as frequently hunted within the region (Flannery, 1995; Whitehead, 2000) and consequently, ecological and harvest parameters were estimated for mammals from nine major groups, representing six families of marsupials, one monotreme and one eutherian mammal (Table 1). These groups were determined on the basis of phylogeny, body size, diet, behaviour and the principal habitat(s) where each group is found. While a simplification, this approach is defendable in that some hunting studies did not always identify mammals to the species level and because ecologically equivalent congeners are replaced across different habitats and altitudinal ranges in New Guinea (Flannery, 1995). Moreover, insufficient data were available from New Guinea or Australasian mammals to provide demographic and population density at a species or generic level. While the selected nine groups simplify the actual situation, each group in actual fact consists of a relatively small number of genera, with just one genera included in the cuscus, striped possum, ringtail and tree-kangaroo groups and two genera for the echidna and fruit bats (Table 1). While the bandicoots and wallabies are both represented by three genera and the quolls (Dasyuridae) by four, data within Flannery (1995) and individual species accounts indicate similar life-history characteristics within each of these groups suggesting that generalities can be made for these confamilials. Small mammals and birds were not included in the analysis, despite the likely importance of small game as a source of protein (Mack and West, 2005), because very little information was available on the hunting of birds (with the exception of Healey, 1986), most hunting studies do not report ‘‘a large, but unknown, number of small mammals” (Dwyer, 1982a). In addition, the impact of hunting (from a conservation perspective) is likely to be greater on larger-sized species, which is the focus of this review. Hunting of cassorwary (Casaurius sp.) and wild pigs (Sus scrofa) were also not included in this review due to the limited data available on hunting of these species (reported in only five of the 16 studies reviewed). Taxonomy follows Flannery (1995) and the main habitat and diet of each group was summarised from Flannery (1995) and Strahan (1995). Following Robinson and Redford (1986a) and Fa and Purvis (1997), each species group was assigned to one of six dietary categories: herbivore/ browser, frugivore/herbivore, frugivore/granivore, frugivore/omnivore, insectivore/omnivore and carnivore.

Table 1 The nine major groups of mid-sized game in Papua New Guinea and number of genera represented, with information on body mass, dietary category and principal habitats. Family

Species group (genera)

Mass (g)

Diet

Habitat

Tachyglossidae Dasyuridae Peroryctidae Phalangeridae Petauridaec Pseudocheridae Macropodia Macropodia Pterpodidae

Echidna (2) Quoll (4) Bandicoota (3) Cuscus (1) Striped possum (1) Ringtail (1) Tree-kangaroo (1) Wallaby (3) Fruit bat (2e)

1550–7800 200–630 690–960 780–3800b 450–490 730–1770 8030–13 440 1500–5480d 320–620

Insectivore/Omnivore Carnivore Frugivore/Omnivore Frugivore/Herbivore Insectivore/Omnivore Herbivore/Browser Herbivore/Browser Herbivore/Browser Frugivore/Granivore

Primary Primary/Secondary Primary/Secondary Primary Primary/Secondary Primary Primary Primary/Secondary Primary/Secondary

a ‘‘Bandicoot” refers to the Echymipera, Peroryctes and Microperoryctes species in the family Peroryctidae, as opposed to the Permelidae the main family of Australian bandicoots, which is only represented by one species (Isodon macrourus) with a restricted range in the Trans Fly grasslands, PNG. b The black-spotted cuscus (Spilocuscus rufoniger) with a body mass of ca. 5500–6500 g and very restricted geographic distribution is not included in the analysis. c As well as three species of striped possum (Dactylopsila sp.) the Petauridae includes two gliders (Petaurus abidi and Petaurus breviceps), which are not included as midsized game. d Body mass of wallabies is restricted to forest dwelling species and does not include the agile wallaby (Macropus agilis) which has a restricted range in the Trans Fly grasslands, PNG. e While the flying foxes Pterpodidae consist of 20 species from 8 genera, the reviewed hunting studies indicate that just two species are commonly hunted; the greater flying fox (Pteropus neohibernicus) and the great bare-backed fruit bat (Dobsonia magna).

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female age of first reproduction, b annual birth rate of female offspring, and w the age of last female reproduction (estimated from maximum longevity). Where possible a, b and w were estimated for wild populations, however, w often had to be estimated from captive individuals. For each species group the mean and range of rmax were estimated by using the mean and lower and upper ranges of a, b and w available from related species. The principal sources of life-history data were Strahan (1983, 1995), Lee and Cockburn (1985), Flannery (1995) and Menkhorst (1996) and original sources in the scientific literature (Appendix A). Estimates of rmax were available for 35 Australasian species. Because New Guinea’s forest wallabies are small (Table 1), demographic estimates from Australian wallaby species were restricted to those with a body mass <5.5 kg.

2.2. Hunting data Data on hunting were obtained from published hunting studies, as well as unpublished data obtained by the author. A total of nine studies were available from PNG where information from hunters over defined periods provided data on the actual and proportionate numbers of the different species captured. Considerable differences exist in the duration and scale of these studies (Table 2) reflecting the relative paucity of information available for this region. An additional seven studies within PNG were available where hunting rates were estimated on the basis of the collection of skulls that are often retained as trophies (Pernetta and Hyndman, 1982; Morris, 1985; Hyndman, 1984; Gorecki and Pernetta, 1989 and three data sources therein). These studies only provide information on the relative proportion of different species hunted and may be biased due to the cultural significance attached to prey items. For example, tree-kangaroo and ringtails are prized and their skulls are retained (Gorecki and Pernetta, 1989) whereas skulls of smaller common species such as bandicoots are often broken and consumed (personal observation). Consequently, while data derived from the collection of hunting trophies are an important source of information, it is likely to be less representative in comparison to longer-term hunting studies. These data were used to determine species captured, the principal sources of game, the relative contribution of each group to the biomass of game provided, and to estimate (where possible) annual extraction rates expressed as kg of game/km2/year. Several anthropological studies report in detail on the hunters and hunting methods utilised in the region (e.g. Dornstreich, 1973; Morren, 1986; Gorecki and Pernetta, 1989; Whitehead, 2000). While differences exist between regions and different ethnic groups, in general most studies report that hunting is principally (but not exclusively) undertaken by men, traditional methods (e.g. bows, traps and snares) are frequently utilised (Mack and West, 2005), the use of dogs is important in many instances, animals are hunted opportunistically (e.g. while tending gardens) as well as on specific multi-day hunting trips, and almost all available prey (ranging in size from nestling Passerines to wild-pigs and cassowary) are hunted.

2.4. Population density Published data from 23 Australasian species and the data of Robinson and Redford (1986a) and Fa and Purvis (1997) for Neotropical and Afrotropical mammals, were used to generate linear regressions between log10(body mass) and log10(population density) for the five trophic levels represented by the nine groups of game. Data on density are reported at the scale of the study site (i.e. ecological densities) and were included in the analysis if they were obtained from line transects methods, from intensively studied populations with census data, and from radio-tracking studies where data on territorial overlap were estimated. Separate regression analyses were undertaken for Australasian species and for the combined Neotropical, Afrotropical and Australasian dataset. Because the maximum body mass of Neotropical and Afrotropical mammals greatly exceeds the mass of most New Guinea mammals, species used in the regression analysis were restricted so that the body masses of Neotropical and Afrotropical mammals were no larger than one order of magnitude greater than the maximum mass of Australasian mammals within each dietary category. The resulting regression equations were used to estimate population densities of hunted species. Standing biomass of game was calculated from the average body mass and the estimated population density of hunted species. A similar approach for estimating population densities in hunting studies based upon allometric relationships was undertaken by Robinson and Redford (1991) and has been utilised for assessing the sustainability of harvesting cassowary species (Casuarius) in Papua New Guinea (Johnson et al., 2004). Such an approach can be criticised as population densities can vary widely (Peres, 2000) and this parameter will generate

2.3. Intrinsic rate of increase Intrinsic rate of increase (rmax) was estimated from published estimates of demographic values for New Guinea and related Australasian mammals using Cole’s (1954) iterative equation, where: 1 = ermax + bermax be rmax (a) be rmax (w+1). Parameters are: a

Table 2 Frequency of capture of mid-sized mammals from hunting studies of different ethnic groups within Papua New Guinea indicating% of captures, overall mean% ± SD of capture for all nine hunting studies, overall mean% ± SD of representation from seven trophy studies and the total sample size of animals, number of species and duration (months) of each study. Sources of data are: Etolo (Dwyer, 1982a); Yawio & Yuro (Hide et al., 1984); Seltaman (Whitehead, 2000); Purari Delta (Liem, 1983); Miyanmin (Morren, 1986); Wopkaimin (Hyndman, 1984); Gadio Enga (Dornstreich, 1973), Pawaia & Gimi (Mack and West, 2005) and Gimi (Cuthbert unpublished data). Species group

Etolo

Yawio & Yuro

Seltaman

Purari Delta

Miyanmin

Wopkaimin

Gadio Enga

Pawaia & Gimi

Gimi

Hunting studies (n = 9)

Trophy studies (n = 7)

Echidna Quoll Bandicoot Cuscus Striped possum Ringtail Tree-kangaroo Wallaby Fruit bat

0.4% 2.9% 23.3% 30.0% 3.5% 25.0% 1.3% 9.2% 4.6%

1.0% 0.3% 48.3% 23.2% 4.1% 8.4% 1.5% 4.5% 8.8%

0.3% 0.1% 5.2% 51.3% 2.9% 14.6% 1.7% 23.9% 0.0%

0.0% 0.0% 10.4% 68.1% 1.4% 0.0% 0.0% 2.1% 18.1%

2% 4% 66% 21% 2% 0% 4% 2% 0%

0% 0% 0% 30% 2% 25% 0% 0% 43%

0% 0% 9% 91% 0% 0% 0% 0% 0%

5.9% 0.0% 28.6% 39.9% 0.0% 7.3% 5.1% 8.4% 4.8%

1.0% 2.2% 44.7% 23.0% 0.0% 7.3% 1.8% 12.8% 7.2%

1.2 ± 1.9% 1.0 ± 1.5% 26.2 ± 22.6% 42.0 ± 24.0% 1.7 ± 1.5% 9.7 ± 9.9% 1.7 ± 1.8% 7.0 ± 7.7% 9.6 ± 13.7%

0.1 ± 0.3% 0.5 ± 0.9% 14.3 ± 16.1% 32.1 ± 11.6% 0.3 ± 0.5% 32.5 ± 24.4% 2.7 ± 2.7% 12.9 ± 18.5% 4.6 ± 7.8%

N of samples N of species Study duration

1560 25 12

717 24 16

158 16 36

144 – 3

53 8 2

56 12 3

22 – 8

354 37 3

127 12 3

3108

2904

–

–

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the largest error in harvest estimates (Robinson and Redford, 1991), however detailed studies of the population densities of New Guinea’s mammals remain very scare and without using this approach no assessment would have been possible.

sity (from the guild specific regression analysis) and capture rates of game. Selectivity was calculated as: (U A)/ (U + A), where A is availability and U is utilisation.

3. Results 2.5. Analysis and harvest model 3.1. Game species and selection The sustainability of hunting was estimated by the maximum sustainable production (MSP) method of Robinson and Redford (1991). MSP (kg/km2/year) was calculated as: P = 0.6K  (Rmax 1)  F, where P is the maximum production of a species, K is carrying capacity (estimated from the trophic specific regressions of body mass and population density), Rmax is the finite rate of population increase (where Rmax = ermax), and F is a mortality factor that varies from 0.2, 0.4 and 0.6 for long, medium and short-lived species respectively (Robinson and Redford, 1991). For the purpose of this analysis, long, medium and short-lived species were defined as those with a maximum longevity of >15 years, 5–10 years and <5 years respectively. Using the available estimate of rmax and population density (the average value from the Australasian and combined data-sets), MSP (expressed as kg/km2/year) was compared to extraction rates (kg/km2/year) for the three hunting studies where harvest rates could be estimated. Where extraction rates exceed MSP hunting will clearly be unsustainable, however following Robinson and Redford (1991) and Fa et al. (2002) harvesting is considered unsustainable when harvest rates exceed 20% of MSP. Annual extraction rates could only be estimated for three studies where data was available on annual harvest rates as well as information on the area of land hunted (Hide et al., 1984; Dwyer, 1985; Morren, 1986). Source-sink dynamics (as would occur if non-hunted areas surrounded the sites where extraction rates were estimated) were not considered in the analysis, as while much of PNG still consists of sparsely population forest areas almost all of this land is owned and managed by local communities with boundaries of different clan lands strongly contested. Consequently, I have assumed that the three studies where extraction rates could be estimated were surrounded by neighbouring land hunted at a similar extraction rate. Ivlev’s selectivity index was used to test whether large-bodied species are preferentially hunted, based on the body mass, estimated population den-

Data from nine hunting studies indicates that cuscus and then bandicoots numerically comprise the principal sources of game, together accounting for nearly 70% of captures (Table 2; Fig. 1). In contrast, tree-kangaroos, striped possums, quolls and echidna are rarely taken with species in these groups combined on average accounting for less than 6% of all game captured in hunting studies. While the proportion of each group varies from study to study, the major difference between studies was in the relative take of cuscus and bandicoots, ranging from a ratio of 10:1 for the Gadio Enga and Seltaman (Dornstreich, 1973; Whitehead, 2000), to a ratio of 1:3 for the Miyanmin (Morren, 1986) and 1:2 for the Yawio and Yuro (Hide et al., 1984). Data from eight hunting studies where cuscus and bandicoots were both captured (i,e. excluding Wopkaimin; Hyndman, 1984) shows that the proportion of cuscus and bandicoots captured was strongly negatively correlated (r2 = 0.79, P < 0.01); indicating that in different areas these two groups of species appear to replace each other as the principal source of game. Data from the seven studies where game were recorded through the collection of trophies showed similarities to data obtained from hunting studies (Table 2), however there are significant differences between the two data-sets with proportionally more ringtails and wallabies in trophy collections and an under-representation of bandicoots and fruit bats (Table 2). Data from eight hunting and trophy studies where there was a detailed breakdown of species captured (Gorecki and Pernetta, 1989; Cuthbert unpublished data; Dwyer, 1982a; Gorecki and Pernetta, 1989; Hide et al., 1984; Morren, 1986; Morris, 1985; Whitehead, 2000) report 35 different mid-sized species captured as game (>50 species in total). Within groups, one or two species dominate as the principal species captured. The lesser forest wallaby (Dorcopsulus vanheurni) comprised 87% of all wallabies captured

0.6 0.53

0.5

0.4

0.3

0.2 0.13

0.12

0.1

0.10

0.07

0.03 0.02

0 Cuscus

Bandicoot

Ringtail

Fruit bat

0.00 Wallaby

Striped possum

Treekangaroo

Echidna

0.00 Quoll

Fig. 1. Average proportion of captures (filled bars) from nine hunting studies (see Table 2) and the average proportion of total biomass captured (line and data values) of each group.

R. Cuthbert / Biological Conservation 143 (2010) 1850–1859

3.2. Intrinsic rate of increase Estimates of rmax ranged from 0.28 and 0.29 for tree-kangaroos and cuscus respectively, up to 5.14 for bandicoots (Table 3). Data from 35 Australasian species (34 marsupials and one monotreme) indicates a significant negative relationship between rmax and body size (Regression slope = -0.24 ± 0.05, F1,33 = 21.1, p < 0.001; Fig. 2). Exclusion of echidna from the data-set made no difference to the significance of this relationship (Regression slope = 0.23 ± 0.05, F1,32 = 19.6, p < 0.001). Phylogeny influenced rmax, with bandicoots having a greater rmax value than expected for their body mass, whereas cuscus and wallabies species both have lower rates of rmax (Fig. 2). Within families, where there is limited power due to sample size available, there was only a significant relationship between body mass and rmax for quolls (Regression slope = 0.14 ± 0.03, F1,15 = 21.2, p < 0.001).

1.0

Quoll Bandicoot Cuscus Ringtails Wallabies Striped possum Echidna

0.8 0.6

Log 10 r max

(n = 6 wallaby species and 278 records), the coppery ringtail (Pseudocheirus cupreus) formed 86% of all ringtails (n = 5 species, 1635 records), the spiny bandicoot (Echymipera kalubu) comprised 46% of bandicoots (n = 5 species, 920 records) and ground cuscus (Phalanger gymnotis), northern common cuscus (Phalanger orientalis) and silky cuscus (Phalanger sericeus) comprised 32%, 27% and 22% respectively (n = 7 species, 1525 records). Game species reported captured of conservation significance (based upon the IUCN Red List 2010) include the Western long-beaked echidna (Zaglossus bruijnii) and black-spotted cuscus both Critically Endangered, Goodfellow’s tree-kangaroo (Dendrolagus goodfellowi) Endangered, Doria’s tree-kangaroo (Dendrolagus dorianus) Vulnerable, the dusky padamelon (Thylogale bruijni) and New Guinea pademelon (Thylogale bruni) both Vulnerable. The estimated biomass of each group (from the average proportion captured in the nine hunting studies) indicates that cuscus species are the most important source of animal protein providing 53% of biomass (Fig. 1) followed by wallabies (13%), bandicoots (12%) and tree-kangaroos (10%). The relatively large size of wallabies and tree-kangaroos mean that they provide a disproportionately high proportion of biomass in comparison to numbers captured. Ivlev’s selectivity index indicates was no indication that large-bodied species were preferentially hunted over small species, (Regression slope = 0.114 ± 0.067, F1,22 = 2.95, p = 0.10).

0.4 0.2 0.0 -0.2 -0.4 -0.6 -0.8 0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Log 10 Body Mass (g) Fig. 2. Relationship between (log 10) body mass and the (log 10) intrinsic rate of increase (rmax) for Australasian marsupial mammals (n = 34 species) and one monotreme (short-beaked echidna Tachyglossus aculeatus) and the overall fitted linear regression line.

Quoll Bandicoot Cuscus Ringtail Tree-kangaroo & wallaby Afrotropical & Neotropical

4.0

log 10 Density (numbers/km2)

1854

3.0 2.0 1.0 0.0 -1.0 0.0

1.0

2.0

3.0

4.0

5.0

6.0

Log10 Body Mass (g)

3.3. Population density and standing biomass

Fig. 3. Relationship between body mass and population density for 6 groups of Australasian marsupial mammals and the fitted regression line (solid line) for 25 Australasian species and the regression line (dashed) for 162 species of Afrotropical and Neotropical mammals. Body mass data for Neotropical and Afrotropical mammals were restricted to be no larger than one order of magnitude greater than the maximum mass of Australasian mammals within the same dietary categories (see Methods) and the regression lines are fitted across the resulting ranges.

Data for 23 Australasian species indicates a significant negative relationship between population density and body size (Regression slope = 0.49 ± 0.17, F1,22 = 8.90, p < 0.01; Fig. 3), with an overall

regression equation of: Log10 Population Density = 3.13 (0.49  Log10 Body Mass). There was no significant differ-

Table 3 Estimated mean and range (in parentheses) of age at first reproduction (a), annual birth-rate of female offspring (b), age of last reproduction (w), calculated intrinsic rate of increase (rmax) and population densities (animals/km2) estimated from the diet specific regressions of Australasian species and the diet specific regressions of the combined Neotropical, Afrotropical and Australasian data-set. There was no significant regression relationship between body mass and population density for carnivores (Table 3), so population density for quolls (in parentheses) was derived from the Western quoll Dasyurus geoffroii (Oakwood 2002). Species group

Echidna Quoll Bandicoot Cuscus Striped possum Ringtail Tree-kangaroo Wallaby Fruit bat

A

1.0 1.0 0.3 2.2 1.2 1.3 2.2 1.3 1.5

b

(0.3–0.3) (1.3–3.0) (0.8–2.0) (0.8–2.0) (1.5–3.0) (0.37–2.0) (1.0–2.0)

0.5 2.7 4.4 0.5 1.5 0.8 0.5 0.8 1.0

W

(2.4–3.3) (2.5–7.3) (0.5–0.5) (0.5–2.0) (0.4–1.5) (0.3–0.6) (0.5–1.5) (1.0–1.0)

31.0 (21.0–50.0) 3.9 (3.1–5.0) 2.8 (2.0–3.5) 12.5 (11.0–17.0) 6.5 (5.0–7.0) 5 (4–6) 18 (14–20) 9.4 (3.9–14.0) 16.3 (15.0–20.0)

rmax

0.41 1.30 5.14 0.29 0.81 0.50 0.28 0.55 0.56

Population density/km

(1.20–1.46) (2.94–7.97) (0.22–0.39) (0.21–1.22) (0.08–1.02) (0.19–0.40) (0.13–1.66) (0.48–0.69)

2

Australasian

All data

0.4 (2.3) 57 – 18 337 7 43 –

4.3 – – 44 20 153 32 68 109

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Table 4 Regression analysis of body mass against population density for Australasian marsupials and the combined (mass restricted) Afrotropical, Neotropical and Australasian data set, indicating the slope, standard error of the slope, intercept, r2, probability and sample size of species. Dietary category

Slope

s.e. of slope

Intercept

r2

p

N

Australasian marsupials All dietary categories Frugivore/omnivore Herbivore/browser Insectivore/omnivore

0.53 1.33 1.80 1.42

0.18 0.43 0.41 0.34

3.24 5.63 8.08 5.04

0.29 0.71 0.69 0.85

<0.01 <0.05 <0.005 <0.05

24 6 9 5

Combined data-set All dietary categories Carnivore Frugivore/granivore Frugivore/herbivore Frugivore/omnivore Herbivore/browser Insectivore/omnivore

0.52 0.19 0.57 1.01 0.30 0.72 0.57

0.05 0.58 0.15 0.21 0.17 0.25 0.13

3.11 0.65 3.53 5.11 2.35 4.40 2.81

0.38 0.14 0.53 0.50 0.06 0.26 0.37

<0.001 0.76 <0.001 <0.001 0.09 <0.01 <0.001

187 7 41 24 54 23 37

ence in either the slope or intercept (testing regression slopes t1,183 = 0.01, p = 0.99; testing regression intercepts t1,184 = 0.07, p = 0.94) of the regression lines derived from Australasian marsupials or from the (restricted mass) Afrotropical and Neotropical mammals data-set (Fig. 3). There were significant negative relationships between body mass and population density within certain dietary categories, both for data from Australasian marsupials and for the combined dataset (Table 4). Estimated densities range from 0.4 to 4.0 animals/km2 for the echidna, up to 150–340 animals/km2 for ringtails (Table 3). Using the best available estimate of population density (derived from the Australasian marsupial data unless this were non-significant or not available) and the mean body mass of each species group, standing biomass of mid-sized game in New Guinea is estimated to be 923 kg/km2.

game for the Yawio/Yuro and Miyanmin (3.8 and 10.3 kg/km2/year and 26% and 45% of total harvest respectively), with wallabies (7.0 kg/km2/year and 19%), cuscus (6.2 kg/km2/year and 17%) and ringtails (6.1 kg/km2/year and 17%) being the major game for the Etolo. Comparison of extraction versus production rates (kg/km2/ year) indicates that long-beaked echidnas and cuscus are likely to be unsustainably harvested in all three studies (Fig. 4), with extraction rates close to or beyond the estimated MSP for two hunting studies, and greater than 20% MSP for all three studies (Fig. 4; extraction rates that exceed 20% of MSP are considered unlikely to be sustainable). Hunting of tree-kangaroos is also great than 20% MSP for the two studies where data were available. In contrast, extraction rates for all other species is less than the MSP and bandicoots are hunted at rates far below estimated MSP (Fig. 4).

3.4. Annual harvest and sustainability of harvest

4. Discussion

For the Etolo, Yawio/Yuro and Miyanmin total extraction of game was estimated to be 35.7, 14.5 and 22.6 kg/km2/year respectively. By mass, bandicoots were the most important source of

As well as predicting the impact of hunting on New Guinea’s mammals, the results of this study provides the first evidence for a relationship between body size and population densities and intrinsic rates of increase for Australasian marsupial mammals. Despite the limited sample sizes, the estimated relationships are similar to those reported for a far wider range of (principally) placental mammals across different habitats and continents (Hennemann, 1983; Peters and Raelson, 1984; Damuth, 1991). For Afrotropical and Neotropical forest mammals the relationship between population density and body mass is linear, with an estimated regression slope of 0.54 (Fa and Purvis, 1997) and with population density strongly influenced by trophic level (Robinson and Redford, 1986a; Fa and Purvis, 1997). The relationship for marsupial mass is similar; with an estimated regression slope of 0.49 and significant relationships between body mass and population density within three dietary categories. Similarly, the relationship between body size and intrinsic rates of increase of Australasian marsupial and monotreme mammals is comparable to that found by Hennemanm (1983) for a far more diverse group of mammals, with estimated regression slopes of 0.24 and 0.26 respectively. These results suggest analogous ecological processes may be affecting population densities and life-history parameters of both placental and marsupial mammals. The biomass of midsized marsupial mammals in New Guinea estimated by this study (923 kg/km2) is also broadly comparable with other studies of mammalian biomass within evergreen tropical forests,

Log10 Extraction (kg/km2/year)

1.5 1.0 0.5 0.0 -0.5 Echidna Bandicoot Striped possums Tree-kangaroos Fruit bats

-1.0 -1.5

Quoll Cuscus Ringtails Wallabies

-2.0 -1.0 -0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Log10 Production (kg/km2/year) Fig. 4. Relationship between estimated production and extraction rates from three studies in Papua New Guinea, using data from the Etolo (Dwyer, 1982a), Yawio & Yuro (Hide et al., 1984) and Miyanmin (Morren, 1986), indicating where production equals extraction (solid line) and where extraction is 20% of the estimated production (dashed line) considered sustainable for long-lived taxa (Robinson and Redford, 1991).

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despite the relatively small size of most of the game species in comparison with some species in Africa and the neotropics. Four studies from South America report biomasses ranging from 891 to 2264 kg/km2 (average 1410 kg/km2) and one study from West Africa estimates biomass at 1050 kg/km2 (Robinson and Bennet, 2000, Table 2.1). The analysis suggests considerable variation between population densities of different species, ranging from 0.4 to 4 individuals/km2 for the long-beaked echidnas, to 150–340/ km2 for ringtails. Accurate estimation and variation in population densities is important, as this parameter will generate the largest error in harvest estimates and resulting estimates of sustainability (Robinson and Redford, 1991). The very low densities estimated for the large-sized (7–8.6 kg) long-beaked echidnas appear plausible, as most studies report that this species is very scarce, even in areas with very low or no hunting pressure (Morren, 1986; Flannery, 1995). Results from radio-tracking studies of the Western long-beaked echidna (Z. bruijnii) in a near pristine area of unhunted primary forest confirm this, with individual home ranges covering very large areas of up to 168 hectares (Opiang, 2009). Studies of mountain cuscus (Phalanger carmelitae), silky cuscus (Phalanger sericeus) and coppery ringtail (Pseudochirops cupreus) (Salas 2002) suggest densities of between 59 and 70 animals/km2 for cuscus and 135 animals/km2 for the coppery ringtail (assuming no overlap between animals of the same sex and extensive overlap between the sexes). These values broadly agree with the densities derived from the relationship between body mass and diet, with estimated densities of 44/ km2 for cuscus and 150–340/km2 for ringtails. Similarly, body size derived densities for tree-kangaroos (7–32/km2) are comparable with those found from studies of Bennet’s tree-kangaroo (Dendrolagus bennetianus) and Lumholtz’s tree-kangaroo (Dendrolagus lumholtzi), with estimated densities of 19 and 78 animals/ km2 respectively (Flannery et al., 1996; Newell, 1999a). Thus, while there is uncertainty and likely some error in deriving densities from body mass and feeding guild relationships, even from Australian rainforest habitats (Kanowski et al., 2001), the results appear reasonable where comparisons can be made. Hunting returns indicate that numerically cuscus and bandicoots are main source of game, although all mid-sized game animals are captured, including species of conservation concern, such as long-beaked echidnas and tree-kangaroos. The estimates of maximum sustainable production versus annual extraction rates as indicated in Fig. 4 are the first quantifiable estimates of the sustainability of hunting in PNG, with the data indicating that species of long-beaked echidna, tree-kangaroos and cuscus are most at risk from over-hunting. These conclusions are supported by previous work, which has identified both long-beaked echidnas and tree-kangaroos as particularly vulnerable to hunting pressure (George, 1979; Flannery, 1995). The potential vulnerability of cuscus was not identified by George (1979), but this study suggests that this group is also vulnerable, as well as providing the main source of wild meat in people’s diet. Some caution should be applied to the generality of these results today, as many of the hunting studies that this review is based upon were undertaken >30 years ago (e.g. Dornstreich, 1973; Dwyer, 1982b; Hide et al., 1984; Morren, 1986) and changes in lifestyle and hunting practises may have subsequently altered. While changes are indeed likely in communities where agriculture or other development has altered the landscape and lifestyles, in forested areas (which still comprise >65% of New Guinea’s area; Mittermeier et al., 1998) hunting methods, hunt-

ers and the species hunted appear little altered to studies from 20–30 years ago (Mack and West, 2005; authors own observations). Mack and West’s (2005) work in the Eastern Highlands Province found that hunting yielded an estimated daily intake of 23 g per person, a value very similar to that found by Hide et al. (1984) who reported a daily intake of 22 g in a neighbouring Simbu province. These two studies at least, suggest that consumption of wildlife has not dramatically changed in the last 20 years. As well as identifying which groups of mammal are likely to be vulnerable to hunting, the results also indicate which species are most likely to be sustainably harvested. This is vital, because wildlife still provides an essential source of protein for many people in New Guinea (Hide et al., 1984; Dwyer, 1985; Dwyer and Minnegal, 1991; Mack and West, 2005). The results of this study indicate that cuscus, bandicoots and ringtails are numerically the most important game animals, while cuscus provide the main biomass of wild meat, with wallabies, bandicoots and treekangaroos also providing important sources of protein. However, this study suggests that only bandicoots and ringtails are likely to provide a sustainable harvest: primarily because of the relatively high population densities of these species, and for bandicoots their high intrinsic rate of increase. Suitable caution should be applied to these conclusions, as while the Maximum Sustainable Production method is commonly used in hunting studies (e.g. Robinson and Bennet, 2000 and references within) its use has been criticised as insufficiently precautionary (Milner-Gulland and Akcakaya, 2001). While alternative approaches may have been preferable (Slade et al., 1998; Milner-Gulland and Akcakaya, 2001; Vliet and Nasi, 2008), the detailed information necessary for a more a complex analysis is not yet available for Papua New Guinea. The primary aim of this paper was to make a preliminary assessment on the impact of hunting and quantify the vulnerability of different animal groups. Further research on the demography and population density of species and the sustainability of hunting are clearly required within the region. In summary, the results of this study provide a first analysis of the impact of hunting in Papua New Guinea. The data, while preliminary, suggest that certain species are likely to be very vulnerable to hunting, whereas others can be hunted at higher rates. Consequently, if conservation in PNG is to be married with the needs of local people to harvest wildlife for food, then the high reproductive rate and population density of bandicoots, and the high population density of ringtails will be more likely to provide a sustainable harvest in comparison to more vulnerable species with intrinsically slow rates of reproduction and low population densities.

Acknowledgements I am grateful to Andy Mack, Debra Wright, Ross Sinclair and Matthew Denny for encouragement with this review and comments on previous drafts and to Robin Hide for providing details of harvest data from his study. Comments from Martin R. Nielsen and two anonymous reviewers improved an earlier version of this paper. The work was made possible after funding from the British Ecological Society, Fauna and Flora International and the Rufford Foundation, and was undertaken with the assistance and support of the Wildlife Conservation Society – Papua New Guinea Program and the University of Canterbury, New Zealand.

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Appendix A Information in the appendix includes the family and species name, body mass based upon the average or mid-point of the reported range for female mass, a female age of first reproduction, b annual birth rate of female offspring, w the age of last female reproduction, rmax intrinsic rate of increase, population density (animals per km2) and sources of reference. Family

Species

Mass (g)

a

B

w

rmax

Density km2

Reference

Tachyglossidae Tachyglossidae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Dasyuridae Peramelidae Peramelidae Peramelidae Peramelidae Peramelidae Phascolarctidae Vombatidae Vombatidae Acrobatidae Potoroidae Potoroidae Potoroidae Potoroidae Pseudocheridae Pseudocheridae Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Macropodia Phalangeridae Phalangeridae Phalangeridae Petauridae Petauridae Petauridae Petauridae Petauridae Petauridae Burramyidae Burramyidae Burramyidae

Tachyglossus aculeatus Zaglossus bruijnii Dasyurus maculatus Dasyurus viverrinus Dasyuros geoffroii Dasyuros hallucatus Dasycercus cristicauda Sarcophilus harrisii Parantechinus apicalis Parantechinus bilarni Phascogale tapoatafa Planigale gilesi Antechinus rosamondae Antechinus leo Sminthopsis crassicaudata Sminthopsis dolichura Planigale tenuirostris Sminthopsis griseoventer Isodon macrourus Isodon obesulus Permales gunni Permales bourgainville Permales nasuta Phasolarctos cinereus Vombatus ursinus Lasiorhinus latifrons Acrobates pygmaeus Potorous tridactylus Bettongia penicillanta Bettongia gaimardi Potorous longipes Pseudocheirus peregrinus Pseudocheirus occidentalis Dendrolagus bennetianus Dendrolagus inustus Dendrolagus lumholtzi Lagorchestes conspicillatus Lagostrophus fasciatus Macropus antilopinus Macropus dorsalis Macropus eugenii Macropus fuliginosus Macropus rufus Petrogale assimilis Trichosurus vulpecula Trichosurus caninus Aliurops ursinus Petaurus breviceps Petaurus gracilis Petaurus australis Petaurus norfolcensis Petauroides volans Gymnobelideus leadbeateri Cercartetus nanus Cercartetus caudatus Burramys parvus

1550 7800 4000 880 850 400 78 6000 58 23 156 7 25 36 15 12 6 16 849 528 927 220 706 6500 26,000 25,500 12 1020 1300 1660 1700 875 1000 9300 11,375 6525 3050 1600 17,500 6500 5500 27,500 26,500 4300 2500 3500 10,000 98 365 575 230 1300 128 24 30 42

1 1 1 1 1 1 0.9 2 0.9 1 1 0.6 1 1 1 0.7 0.3 1 0.3 0.3 0.3 0.3 0.3 2 2 3 1 1.5 0.6 – – 1 0.8 – 1.5 – – 2 – 1 0.8 – 1.5 1.5 1.3 3 – 1 1.3 2 – – 0.8 0.5 0.5 1

0.5 0.5 2.5 2.4 2.5 3.3 4 1.4 4 2.3 3.2 3.8 4 4.3 5.4 3.6 3 4 7.3 2.9 4.8 2 – 0.4 0.4 0.5 3.5 1.2 1.7 – – 1.5 0.6 – 0.4 – – 0.5 – 0.7 0.5 – 0.5 0.8 0.5 0.5 – 2 1.6 0.5 – – 1.5 4.3 2.3 2

36 31 4 4 5 3.1 7 7.5 2.5 1.8 3 5 3 1.6 1.5 3.2 3 2.5 2.4 3.5 2 – – 18 15 20 3 7 5 – – 6 4 – 20 – – 6.5 – 12.5 14 – 20 13 11 17 – 7 5 7 – – 7 4 3.2 12

0.41 0.41 1.25 1.21 1.25 1.46 1.79 0.57 1.78 1.07 1.41 2.45 1.6 1.59 1.8 2.01 3.34 1.59 6.07 4.28 5.5 – – 0.27 0.25 0.26 1.5 0.61 1.38 – – 0.91 0.38 – 0.3 – – 0.26 – 0.56 0.43 – 0.35 0.49 0.39 0.24 0.3 1.08 0.83 0.27 – – 1.02 3.15 1.93 1.1

– – – – 2.3 – – – – – – – – – – – – – 102 62 – – 82 – 25 – – – – 13 24 260 – 19 – 78 24 – 18 – – 1.4 – 86 70 23 2.3 77 24 10 122 235 – – – 650

17, 31 8, 34 1, 31, 36 31, 36, 45 31, 36, 46 31, 35, 36 45 46 45 45 31, 38, 46 31, 45 45 28 31 11 46 46 13 4 16, 26 5, 6, 16, 30, 42, 45, 48 42, 44, 46 31, 40, 45 26, 31, 46 31, 45 45 26, 46 26, 31, 46 26, 31, 46 26, 31, 46 31, 46 26, 31 47 9 8, 9 9 32, 33, 46 46 45 25, 45 6, 46 26, 45 23, 26, 46 17, 26, 45 23, 46 17, 19, 25, 26, 31, 45 26, 31, 45 27 20, 37, 47 20, 21 14, 18, 24, 26, 31, 39, 46 26, 37, 44 3 26, 45 26, 31, 46 26, 45 31 (continued on next page)

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Appendix A (continued) Family

Species

Mass (g)

a

B

w

rmax

Density km2

Reference

Pteropodidae Pteropodidae Pteropodidae Pteropodidae

Pteropus poliocephalus Dobsonia magna Pteropus conspicillatus Pteropus alecto

600 317 623 615

1 2 1 1

1 1 2 –

17.5 – 16 –

– – – –

– – – –

17 8 15 2, 49

References to Appendix: 1. Belcher and Darrant (2004); 2. Bonaccorso (1998); 3. Comport et al. (1996); 4. Copley et al. (1990); 5. Duffy (1991); 6. Duffy (1994); 7. Evans (1996); 8. Flannery (1995); 9. Flannery et al. (1996); 10. Friend (1990); 11. Friend et al. (1997); 12 Gemmell (1986); 13. Gemmell (1990); 14. Goldingay and Kavanagh (1990); 15. Hall (1983); 16. Heinsohn (1966); 17. Hennemann (1983); 18. Henry and Suckling (1984); 19. How and Hillcox (2000); 20. Jackson (2000a); 21. Jackson (2000b); 22. Johnson and Delean (1999); 23. Johnson (1998); 24. Kavanagh (1984); 25. Kerle (1998); 26. Lee and Cockburn (1985); 27. Lee (2000); 28. Leung (1999); 29. Lobert and Lee (1990); 30. Mallick et al. (2000); 31. Menkhorst (1996); 32. Newell (1999a); 33. Newell (1999b); 34. Nowak (1991); 35. Oakwood (2000); 36. Oakwood (2002); 37. Quin (1995); 38. Rhind (2002); 39. Russel (1984); 40. Salas 2002; 41. Scott et al. (1999); 42. Seebeck (1979); 43. Short et al. (1998); 44. Smith (1984); 45. Strahan (1983); 46. Strahan (1995); 47. Suckling (1984); 48. Todd et al. (2002); 49. Vardon and Tidemann (2000).

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