SEARCH

SEARCH BY CITATION

Keywords:

  • birds;
  • body mass;
  • diet specialization;
  • extinction risk;
  • extinction-risk classification;
  • habitat loss;
  • habitat specialization;
  • lemurs;
  • range size
  • aves;
  • clasificación del riesgo de extinción;
  • especialización alimentaria;
  • especialización de hábitat;
  • lémures;
  • masa corporal;
  • pérdida de hábitat;
  • riesgo de extinción;
  • tamaño de área de distribución

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

Abstract: Much research has focused on identifying traits that can act as useful indicators of how habitat loss affects the extinction risk of species, and the results are mixed. We developed 2 simple, rapid-assessment models of the susceptibility of species to habitat loss. We based both on an index of range size, but one also incorporated an index of body mass and the other an index combining habitat and dietary specialization. We applied the models to samples of birds (Accipitridae and Bucerotidae) and to the lemurs of Madagascar and compared the models' classifications of risk with the IUCN's global threat status of each species. The model derived from ecological attributes was much more robust than the one derived from body mass. Ecological attributes identified threatened birds and lemurs with an average of 80% accuracy and endangered and critically endangered species with 100% accuracy and identified some species not currently listed as threatened that almost certainly warrant conservation consideration. Appropriate analysis of even fairly crude biological information can help raise early-warning flags to the relative susceptibilities of species to habitat loss and thus provide a useful and rapid technique for highlighting potential species-level conservation issues. Advantages of this approach to classifying risk include flexibility in the specialization parameters used as well as its applicability at a range of spatial scales.

Resumen: Se han realizado muchas investigaciones para identificar características que pueden ser indicadores útiles de cómo afecta la pérdida del hábitat al riesgo de extinción de especies, y los resultados son diversos. Desarrollamos dos modelos simples de evaluación rápida de la susceptibilidad de especies a la pérdida de hábitat. Ambos se basan en un índice del tamaño del área de distribución, pero uno también incorporó un índice de masa corporal y el otro incorporó un índice que combina la especialización de hábitat con la alimentaria. Aplicamos los modelos a muestras de aves (Accipitridae y Bucerotidae) y a los lémures de Madagascar y comparamos las clasificaciones de riesgo de los modelos con el estatus de amenaza global de UICN de cada especie. El modelo derivado de los atributos fue mucho más robusto que el derivado de la masa corporal. Los atributos ecológicos identificaron aves y lémures amenazados con una precisión promedio de 80% y a las especie en peligro y en peligro crítico con una precisión de 100% e identificaron algunas especies no enlistadas como amenazadas actualmente y que sin duda justifican ser consideradas para conservación. El análisis apropiado de información biológica, incluso medianamente cruda, puede ayudar a izar banderas de advertencia sobre las susceptibilidades relativas de las especies a la pérdida de hábitat y por lo tanto proporcionar una técnica útil y rápida para poner de relieve temas potenciales de conservación al nivel de especies. Las ventajas de este método de clasificación de riesgos incluyen la flexibilidad en los parámetros de especialización utilizados así como su aplicabilidad en un rango de escalas espaciales.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

Intensifying agricultural activity, logging, and urbanization typically result in the loss of natural habitats and their fragmentation into a series of isolated remnants, which vary in size, quality, and conservation potential, dispersed within an otherwise transformed matrix (e.g., Debinski & Holt 2000; Fahrig 2003). Intuitively, such habitat loss must have deleterious consequences for ecosystem processes and for species, as has been demonstrated for taxonomic groups ranging from insects (Didham et al. 1996; Shahabuddin & Ponte 2005) to fishes (Fagan et al. 2005), birds (e.g., Diamond et al. 1987; Kattan et al. 1994; reviewed by Turner 1996), and primates (Chiarello & de Melo 2001; Estrada et al. 2002). Nevertheless, results of other studies show weak responses to habitat loss or fragmentation in plants (Kemper et al. 2000), small vertebrates (McCoy & Mushinsky 1994), and birds (Schmiegelow et al. 1997). Thus, the effects of habitat loss vary across taxonomic groups and species, begging the question of what attributes render species resistant or vulnerable to habitat loss.

Conservationists frequently have to make decisions based on limited information. When identifying potentially threatened taxa, the time frame within which such decisions are needed may be short, and therefore the way in which available information is used may be crucial. Several life-history traits and population attributes have been used as predictors or explanations of species extinction risk, including body size, rarity, ecological and habitat specialization, matrix use, range size, and turnover rate (Mann & Pimm 2001; Henle et al. 2004; Cofre et al. 2007). Explorations of these ideas have yielded conflicting results (Dobson & Yu 1993; Gaston & Blackburn 1995; Johst & Brandl 1997; Bennett & Owens 2002), and, at present, there is no standard ecological approach for making predictions about species extinction risk apart from that used by the International Union for the Conservation of Nature (IUCN), whose input requirements result in many species being classified as data deficient (e.g., Mittermeier et al. 2006). It is clear, however, that a combination of individual and population attributes is more informative than a single variable (Davies et al. 2004).

Sensitivity of birds to habitat loss and fragmentation has been linked to body size (with contrasting results—Gaston & Blackburn 1995; Bennett & Owens 2002) and habitat specialization (Bennett & Owens 2002). Overall, habitat generalists are predicted to have more options than habitat specialists when faced with habitat loss or change. Similarly, species with broad dietary spectra may have greater resistance to habitat loss than do dietary specialists. These same conditions are likely to pertain to other, nonavian taxa.

We used 2 families of birds (Accipitridae and Bucerotidae) and the 5 families of lemurs as model taxonomic groups to explore the value of simple models in predicting extinction risk in response to habitat loss. The choice of these 3 species groups was made partly on taxonomic grounds (to encompass 2 of the major classes of vertebrates exhibiting varying degrees of mobility) and partly on the basis of range sizes and ecological diversification. The Accipitridae have a global distribution, with both continental and insular species occupying habitats ranging from semideserts to rainforest interiors: they also exhibit considerable dietary diversification. The Bucerotidae are confined to the old world, but also have continental and insular representatives. They are more conservative in habitat choice than the Accipitridae, being largely confined to woodlands and forests, and are more conservative in diet, with most species eating a mixture of fruits and invertebrates. The lemurs have the most restricted range of our groups of species, being confined to Madagascar and the Comoro Islands (our analyses were restricted to Madagascan lemurs). Like the Bucerotidae, they are also mostly confined to woodlands and forest. Most are vegetarians, but some also eat invertebrates.

We based our models broadly on a model of botanical extinction risk developed by Bond (1995) and incorporated in them range size, body mass, and ecological attributes (habitat and dietary specialization) of species. As a test of the models, we compared our classifications of species' susceptibility to habitat loss with their current global-threat status (as developed by the IUCN Species Survival Commission [BirdLife International 2004; Mittermeier et al. 2006]).

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

The models assumed as a starting point that habitats are pristine. They then predicted responses of birds and lemurs in this pristine habitat to habitat loss. The models ignored other anthropogenic impacts, such as direct persecution or contamination by agrochemicals. Within the Accipitridae, current classifications recognize 62 species within the genera Circus and Accipiter (BirdLife International 2004), but 6 Accipiter species had to be excluded from the model due to a lack of basic biological data (thus, n= 56 species; data from Del Hoyo et al. 1994, Appendix 1). (All appendices are available from http://www.fitzpatrick.uct.ac.za/phockey/habitatloss/.) Fifty-three Bucerotidae species (Del Hoyo et al. 2001; Appendix 2) and 65 lemur species (Mittermeier et al. 2006; Appendix 3) are recognized. Of the latter, adequate biological information was available for only 53 species (82%).

To generate a crude habitat-loss susceptibility index (HLSI), dietary specialization (D) and habitat specialization (H) were each ranked subjectively on a scale of 0 (extreme generalist, presumed low risk) to 1 (extreme specialist, presumed high risk). The HLSI was the product of these 2 values and thus itself ranged from 0 to 1. By way of example, a raptor eating “almost exclusively birds” (e.g., Rufous-chested Sparrowhawk [Accipiter rufiventris]) was treated as more specialized than a species hunting “mostly birds but some rodents” (e.g., Tiny Hawk [A. superciliosus]), which in turn was more specialized than a “generalist predator of small mammals, lizards and birds” (e.g., Shikra [A. badius]). We ranked habitat specialization on a scale linked to the diversity of habitats used by each species and assumed specialization is linked to the likely strength of the response of species to the loss of any one habitat type (Henle et al. 2004). For example, a raptor confined to forest interior (e.g., Nicobar Sparrowhawk [A. butleri]) was considered more specialized than one that uses both forest interior and forest edge (e.g., Red-thighed Sparrowhawk [A. erythropus]), which itself is more specialized than a species using forest interior, edge, and surrounding open habitat (e.g., Slaty-mantled Sparrowhawk [A. luteoschistaceus]; Appendix 1).

To link susceptibility to habitat loss at the individual level with global vulnerability of the species, we plotted HLSIs against a crude range-size index (RSI) for each species. The breeding range of each species was ranked at intervals of 0.05 along a scale from 0.05 (highly range restricted, usually taxa endemic to islands) to 1.0 (species with the most extensive ranges; i.e., the Accipitridae, Northern Goshawk [A. gentilis] and Eurasian Sparrowhawk [A. nisus]; Bucerotidae, African Grey Hornbill [Tockus nasutus]; and lemurs, Rufous Mouse Lemur [Microcebus rufus] and Aye-aye [Daubentonia madagascariensis]). The RSI of each species was calculated as 1—size of breeding range. Thus, a species with a very small range (e.g., 0.1) has a large RSI (0.9 = 1–0.1). The purpose of plotting RSI against HLSI was not to determine (or expect) a statistical relationship between the 2 indices, but rather to categorize relationships between indices along a gradient of increasing extinction risk. The model could not predict the absolute strength of this risk, merely its direction.

For the purpose of simplicity, and following Bond (1995), we divided the model into 3 categories (weak, medium, and strong responses to habitat loss, equating to low, medium, and high extinction risk, respectively) spaced equidistantly along both axes based on the largest value on each axis. Readers with expert knowledge of some of the taxa included in our analyses may disagree with some of the ranking scores that we have allocated. By their very definition, these rankings are fuzzy because they are not empirical sensu stricto, with the exception of the body-mass indices. Nevertheless, we sought to develop a rapid-prediction technique to indicate where as yet unidentified conservation concerns might lie.

To evaluate whether model outputs bore an acceptable resemblance to reality, the global conservation status (as determined from criteria developed by the IUCN Species Survival Commission; BirdLife International 2004; Mittermeier et al. 2006) of each species was compared with the model's predictions of risk for the same species. The IUCN assigns threat status primarily according to population trends and numbers. Thus, although range size is one of the IUCN threat category indicators, the primary criteria used in assessing threat are not the same as those used in our models (i.e., IUCN threat categories can be used as a semi-independent standard for assessing the models' robustness).

It has been proposed that susceptibility to habitat loss may be linked to body size (with larger species expected to be more susceptible because of larger spatial requirements; Gaston & Blackburn 1995). To test whether this is true for the taxonomic groups we examined, an index of body mass was substituted for the HLSI, scaled from 0 (smallest) to 1 (largest). To calculate these figures, we used the mean mass for each species and scored the heaviest species as 1, with other species scored as a proportion of this maximum.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

Susceptibility on the Basis of Range Size and Body Mass

Among Accipitridae, on the basis of body mass, only 57% of threatened (vulnerable and endangered) and 50% of near-threatened taxa were classified correctly as being at medium or high risk, and 76% of least-concern taxa were classified correctly as being at low risk (Fig. 1a; Table 1). For Bucerotidae, predictions were on average better: 91% of near-threatened and 77% of least-concern taxa were classified correctly (Fig. 2a; Table 1). Nevertheless, predictions were considerably poorer for threatened (vulnerable, endangered, and critically endangered) taxa (50%), although data on the mass of species were available for only 4 of the 9 threatened taxa. For lemurs, the model was considerably worse (Fig. 3a). Although all 6 least-concern species were classified correctly, only 12 of 39 (31%) threatened species were classified correctly as being at medium to high risk (Table 1).

image

Figure 1. Vulnerability models for Accipitridae on the basis of (a) a combination of range size and body mass and (b) a combination of range size and a combined index of habitat and dietary specialization (habitat-loss susceptibility index). Some overlapping points have been marginally displaced for clarity but remain within the same risk category.

Download figure to PowerPoint

Table 1.  The relationship between International Union for the Conservation of Nature (IUCN) threat-status categories (BirdLife International 2004;Mittermeier et al. 2006) and predictions of risk.a
GroupStatusbEcologyBody mass
NLRMRHRNLRMRHR
  1. aValues refer to the number of species falling in each category. Highlighted cells are those in which the greatest concordance is expected between the 2 parameters, assuming acceptable robustness of the model.

  2. bAbbreviations: N, number of species; LR, low risk (as defined in the model); MR, medium risk; HR, high risk; IUCN status categories: LC, least concern; NT, near threatened; V, vulnerable; E, endangered; CR, critically endangered; DD, data deficient.

AccipitridaeLC4540 5 0453310 2
NT 4 0 4 0 4 211
V 5 212 5 320
E 2 020 2 020
BucerotidaeLC3223 8 1312452
NT12 7 5 011 173
V 5 122 4 202
E 2 020 0no mass data 
CR 2 011 0no mass data 
LemursLC 64 2 0 6600
DD 7 5 2 0 7 700
V16 880151320
E16 0151161060
CR 8 026 8 431
image

Figure 2. Vulnerability models for Bucerotidae on the basis of (a) a combination of range size and body mass and (b) a combination of range size and a combined index of habitat and dietary specialization (habitat-loss susceptibility index). Some overlapping points have been marginally displaced for clarity but remain within the same risk category.

Download figure to PowerPoint

image

Figure 3. Vulnerability models for lemurs on the basis of (a) a combination of range size and body mass and (b) a combination of range size and a combined index of habitat and dietary specialization (habitat loss susceptibility index). Some overlapping points have been marginally displaced for clarity but remain within the same risk category.

Download figure to PowerPoint

Susceptibility on the Basis of Range Size and Habitat and Dietary Specialization

For the Accipitridae (Fig. 1b), the ecology-based model accurately identified threat status more consistently than the mass-based model. Seventy-one percent of threatened taxa, 100% of near-threatened taxa, and 87% of least-concern taxa were correctly categorized (Fig. 1b; Table 1).

Eleven (20%) of the 56 Accipitridae species are included in the International Red Data Book (Appendix 1): all are threatened primarily by habitat loss or degradation (including by fragmentation; BirdLife International 2004). The model did, however, place 2 threatened species in the low-risk category (Fig. 1b). These 2 species, Slaty-mantled Sparrowhawk and Malagasy Marsh-Harrier (Circus macrosceles), are generalists in terms of their diet and, to a lesser extent, their habitat requirements. Thus, it could be predicted that they should be tolerant of a limited amount of habitat loss. Nevertheless, they are also range-restricted, island-group endemics, and the island groups to which they are restricted have experienced severe environmental degradation (Ferguson-Lees & Christie 2001).

Seven Accipitridae species classified as least concern fell into the medium-risk category (Fig. 1b) (i.e., they are fairly, but not very, specialized). Although these species are not currently listed as globally threatened, they might be important research or conservation focal points in the future, particularly those with very restricted ranges, such as the Pied Goshawk (A. albogularis).

For the Bucerotidae (Fig. 2b), threatened taxa were identified far better by the ecology-based model (72%) than by the mass-based model (Table 1). Although there was only a 5% difference between the classifications of the 2 models for least-concern taxa, the HLSI model correctly classified only 42% of near-threatened taxa, compared with the 91% identified by the mass-based model (Table 1).

Many hornbills are habitat specialists but dietary generalists: the model correctly identified 8 of the 9 threatened taxa as being at medium to high risk (Fig. 2b). Near-threatened taxa fell almost equally into the low- and medium-risk categories, with none being classified as high risk. One least-concern species, the Black Dwarf-Hornbill (T. hartlaubi), was classified as at high risk, largely by virtue of its strong dependence on primary evergreen and gallery forest (H= 0.8) and a diet of mostly insects (D= 0.5) (Del Hoyo et al. 2001, Appendix 2). Although not included in the IUCN listing, this species has been identified as “vulnerable to any forest alteration” (Del Hoyo et al. 2001).

Relative to the 2 bird families analyzed, a high proportion of the world's lemurs are threatened (Mittermeier et al. 2006). The ecology-based model correctly classified threatened species with 80% accuracy (compared with 31% for the body-size-based model) (Fig. 3b; Table 1). Endangered and critically endangered taxa (n= 24) were identified with 100% accuracy (Table 1). Two least-concern species, pale fork-marked lemur (Phaner pallescens) and eastern woolly lemur (Avahi laniger), were classified as being at medium risk (Table 1).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

Body Size versus Ecology as Predictors of Susceptibility

Intuitively, large-bodied species, assumed to have the greatest spatial requirements, should be most prone to suffering the effects of habitat loss. Nevertheless, this is not always the case (Johst & Brandl 1997; Figs. 1a & 3a). Overall, the ecology-based model predicted threat considerably better than did a model combining body mass and range size. In the case of hornbills, however, body mass was a reasonable predictor of threat, although this conclusion is weakened by a lack of mass data for the 3 endangered and critically endangered species (Table 1). The reason for the apparent robustness of the mass-based model in this instance is probably that the smaller hornbills (mostly African) tend to inhabit extensive, savanna-like habitats (with many having large ranges as a result) and be habitat and dietary generalists. By contrast, the larger species (mostly Asian) tend to be tropical forest specialists, with several also being island endemics (Appendix 2). In other words, there is some autocorrelation between the body mass and ecological specialization of hornbills. A link between body mass and specialization is not evident in the Accipitridae or the lemurs, with the result that body mass is a poor to very poor predictor of threat for these taxonomic groups when compared with the ecology-based model.

Many local extinctions and population decreases of raptors (e.g., Black Harrier [C. maurus]; Curtis et al. 2004) and hornbills (e.g., Rufous-headed Hornbill [Aceros waldeni]; Del Hoyo et al. 2001) have been linked to habitat loss, and, in the case of lemurs, habitat loss is the most common cause of species being accorded red-data status (Mittermeier et al. 2006). By contrast, all of 10 raptor species studied in Java demonstrate some ability to adapt to habitat loss by virtue of having broad habitat niches (Thiollay & Meyburg 1988). Some species may even benefit from a certain degree of habitat fragmentation (e.g. Black Sparrowhawk [A. melanoleucus][Malan & Robinson 2001] and Northern Goshawk [Woodbridge & Dietrich 1994]).

Seemingly similar species may respond differently to habitat loss due to subtle differences in their ecology. For example, all harriers have broadly similar nesting requirements, body sizes, and foraging methods, but some exploit human-altered habitats (e.g., Montagu's Harrier [C. pygargus][Arroyo et al. 2002] and Cinereous Harrier [C. cinereus][Figueroa & Corales 1999]), whereas others, such as the Pallid Harrier (C. macrourus; Serebryakov & Gorban 1997) are less able or unable to do so. Likewise, Accipiter species confined to forest interiors (e.g., Nicobar Sparrowhawk) are unlikely to persist in small, isolated stands of trees because they depend on deep forest habitat for both their breeding and feeding resources. By contrast, species that breed in forests but use the matrix for hunting tolerate smaller patches of forest trees in which to breed (e.g., Black Sparrowhawk; Curtis et al. 2007). These differences are accounted for in the habitat-specialization index, but the model considered only a scenario of habitat loss and could not account for habitat gain. Some forest-dwelling species, including the Rufous-chested Sparrowhawk, although predicted by the model to be potentially threatened, have undergone local range expansions by virtue of their ability to exploit plantations and the spread of alien trees (Hockey et al. 2005).

Predictions about the susceptibility of species to habitat loss are potentially confounded by the problem of separating historical and current impacts of persecution, both direct and indirect, from impacts of habitat loss. Some raptor populations have suffered dramatic decreases due to hunting (e.g., Hen Harriers [C. cyaneus] in Scotland [Etheridge et al. 1997] and large eagles in South Africa [Brown 1991]) and persistent agrochemicals (Newton 1998). Hunting and collection have also affected several lemur species (Mittermeier et al. 2006). The model could not account for these effects, but they can nonetheless be explained post hoc, at least for heavily persecuted species.

Threat and Range Size

Range size is one of the criteria used by the IUCN to determine threat status, with range-restricted species generally being assessed as more vulnerable than those with large ranges. In theory, a low-risk species could have a very large range and be highly ecologically specialized. Nevertheless, in all 3 taxonomic groups we examined, no species exhibited this combination of attributes (Figs. 1b, 2b, & 3b), implying, not surprisingly, that very few species are habitat and dietary specialists and widespread. By the same token, being range restricted does not automatically qualify a species as potentially threatened: the island-endemic Fiji Goshawk (A. rufitorques), for example, has a very small range, but was classified as at low risk because it is a habitat and dietary generalist (Appendix 1; Ferguson-Lees & Christie 2001). By contrast, Gundlach's Hawk (A. gundlachi), the only globally endangered species of Accipiter, is threatened because it has both a small range and a specialized diet. Again, however, the model did account for these differences.

Strengths and Weaknesses of the Model

Potentially, the ecological model's greatest weakness lies in the subjective categorization of specialization, both habitat and dietary. At the same time, however, this could be the model's greatest strength because it obviates the need for detailed, empirical information. Although habitat specialization could, in theory, be compared among species groups, dietary specialization could not: it would be very difficult to compare the dietary specialization of an herbivorous lemur with that of a carnivorous hawk. Nevertheless, the model was designed for cross-species comparisons within species groups, with risk rankings being relative within these groups.

The finest ranking resolution we attempted for diet and habitat was 0.1 along a gradient from 0 to 1. Nevertheless, because rankings were subjective, many were made on the basis of poor-quality information, and it is unlikely that individual experts will independently arrive at identical rankings of specialization across all species within any species group. Nevertheless, the collective wisdom of, for example, taxon working groups should minimize this problem.

There are 2 important points regarding the flexibility and application of the technique. First, the technique is flexible in terms of the input parameters. For some species groups, the axes of specialization we chose may have been inappropriate. In an analysis of brood-parasitic cuckoos (Cuculidae), for example, host specificity may be a more appropriate parameter than dietary specialization because they are all insectivorous. Second, given that much conservation action is still geopolitically defined, the method also has the advantage over international red data books in that it can be used to assess risk at any spatial scale, from local to provincial, national, regional, continental, or global.

For the species groups we used as examples, the model identified threatened taxa (status of vulnerable or worse) with 71–89% (average 80%) accuracy and endangered and critically endangered taxa with 100% accuracy. Given that habitat loss and fragmentation have major impacts on hawks, harriers, hornbills, and lemurs, the model's ability to identify threatened taxa with this level of accuracy suggests it has value. The greatest accuracy is likely to result when the species included in a model such as ours do not have too great a variability in their diets and habitat choice. When the hawk and harrier model was expanded to include 211 Accipitridae species, its accuracy in predicting threatened taxa fell to 67%. But it is perhaps unreasonable to expect a more robust result if piscivorous sea-eagles, scavenging kites, and crab- and bird-hunting hawks are compared simultaneously because the issue of assigning dietary specialization rankings would be greatly complicated.

Because the analyses necessarily start with the premise that habitats are pristine, the outputs have the potential to raise early-warning flags for taxa whose habits and habitats predispose them to threat in the face of future habitat loss. Any least-concern species identified by the model as falling within or near the high-risk zone (e.g., Black Dwarf-Hornbill) are probably not of least concern. Similarly, data-deficient species classified as being at risk should at least be flagged as requiring urgent status assessment. Conservation planners should not underestimate the value of using basic biological data in simple applications such as this one as an aid. That even such basic data do not exist for 12% of Accipiter species (most of which are on the IUCN Red List; Appendix 1) and 18% of lemur species (all of which are classified as data deficient or vulnerable; Appendix 3) is, in itself, a cause for concern.

Because the model was specifically geared at predicting effects of future habitat loss, it could not account for other impacts such as persecution or poisoning. And it seems unlikely that any other model structure based on ecology could do so effectively. In addition, where species have already experienced habitat loss on a massive scale, even if these species are not super specialists, the model may not identify threat status well simply because the losses are of such magnitude that they have swamped more subtle ecological responses. This is the most likely explanation as to why the status of 2 globally threatened Accipitridae was classified incorrectly.

Taxonomic Limits to the Model's Applicability

We have only attempted to apply our model to terrestrial vertebrates, and this may represent the limits to its applicability in its present form. It is highly debatable whether it would work for a group such as lycaenid butterflies, many of which have apparently highly fragmented ranges and larval development strategies that range from insectivory to obligate ant mutualisms. Indeed, any species group whose members are dominated by microhabitat specialists, species with obligate mutualisms, and species with highly fragmented ranges is unlikely to be a suitable candidate for our model. Nevertheless, weaknesses and limitations apart, we suggest that even the fairly crude analyses performed here demonstrate a useful technique for developing straw men for assessing the need for conservation action, at least for terrestrial vertebrates. The technique may be of particular value as an adjunct to rapid assessment and inventory work because it provides a reasonably reliable estimate of the conservation risk of individual species at a spatial scale appropriate to the questions posed.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited

This study was funded by the South African Department of Science and Technology, through the National Research Foundation. We thank S. Stoffberg for assistance in producing the figures and 2 anonymous referees for comments on an earlier draft.

Literature Cited

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Literature Cited
  • Arroyo, B., J. T. Garcia, and V. Bretagnolle. 2002. Conservation of the Montagu's Harrier (Circus pygargus) in agricultural areas. Animal Conservation 5:283290.
  • Bennett, P. M., and I. P. F. Owens. 2002. Evolutionary ecology of birds: life histories, mating systems and extinction. Oxford University Press, New York .
  • BirdLife International. 2004. Threatened birds of the world. CD rom. BirdLife International, Cambridge , United Kingdom .
  • Bond, W. J. 1995. Assessing the risk of plant extinction due to pollinator and disperser failure. Pages 131146 in J. H.Lawton and R. M.May, editors. Extinction rates. Oxford University Press, New York .
  • Brown, C. J. 1991. Declining Martial Polemaetus bellicosus and Tawny Aquila rapax Eagle populations and causes of mortality on farmlands in central Namibia. Biological Conservation 56:4962.
  • Chiarello, A. G., and F. R. De Melo. 2001. Primate population densities and sizes in Atlantic forest fragments of northern Espirito Santo, Brazil. International Journal of Primatology 22:379396.
  • Cofre, H. L., K. Böhning-Gaese, and P. A. Marquet. 2007. Rarity in Chilean forest birds: which ecological and life-history traits matter Diversity and Distributions 13:203212.
  • Curtis, O. E., R. E. Simmons, and A. R. Jenkins. 2004. Black Harrier Circus maurus of the Fynbos Biome, South Africa: a threatened specialist or an adaptable survivor Bird Conservation International 14:233245.
  • Curtis, O. E., P. A. R. Hockey, and A. Koeslag. 2007. Competition with Egyptian Geese Alopochen aegyptiaca overrides environmental factors in determining productivity of Black Sparrowhawks Accipiter melanoleucus. Ibis 149:502508.
  • Davies, K., C. R. Margules, and J. F. Lawrence. 2004. A synergistic effect puts rare, specialized species at greater risk of extinction. Ecology 85:265271.
  • Debinski, D. M., and R. D. Holt. 2000. A survey and overview of habitat fragmentation experiments. Conservation Biology 14:343355.
  • Del Hoyo, J., A.Elliott, and J.Sargatal, editors. 1994. Handbook of the birds of the world. Volume 2. Lynx Edicions, Barcelona .
  • Del Hoyo, J., A.Elliott, and J.Sargatal, editors. 2001. Handbook of the birds of the world. Volume 6. Lynx Edicions, Barcelona .
  • Diamond, J. M., K. D. Bishop, and S. Van Balen. 1987. Bird survival in an isolated Javan woodland: island or mirror Conservation Biology 1:132142.
  • Didham, R. K., J. Ghazoul, N. E. Stork, and A. J. Davis. 1996. Insects in fragmented forest: a functional approach. Trends in Ecology & Evolution 11:225260.
  • Dobson, F. S., and J. Yu. 1993. Rarity in Neotropical forest mammals revisited. Conservation Biology 7:586591.
  • Estrada, A., A. Mendoza, L. Castellanos, R. Pacheco, S. Van Belle, Y. Garcia, and D. Munoz. 2002. Population of the Black Howler Monkey (Alouatta pigra) in a fragmented landscape in Paleneque, Chiapas, Mexico. American Journal of Primatology 58:4555.
  • Etheridge, B., R. W. Summers, and R. E. Green. 1997. The effects of illegal killing and destruction of nests by humans on the population dynamics of the Hen Harrier Circus cyaneus in Scotland. Journal of Applied Ecology 34:10811105.
  • Fagan, W. F., C. Aumann, C. M. Kennedy, and P. J. Unmack. 2005. Rarity, fragmentation, and the scale dependence of extinction risk in desert fishes. Ecology 86:3441.
  • Fahrig, L. 2003. Effects of habitat fragmentation on biodiversity. Annual Review of Ecology and Systematics 34:487515.
  • Ferguson-Lees, J., and D. A. Christie. 2001. Raptors of the world. Christopher Helm, London .
  • Figueroa, R. A., and E. S. Corales. 1999. Food habits of the Cinereous Harrier (Circus cinereus) in the Argaucanía, southern Chile. Journal of Raptor Research 33:264267.
  • Gaston, K. L., and T. M. Blackburn. 1995. Birds, body-size and the threat of extinction. Philosophical Transactions of the Royal Society of London: B 347:205212.
  • Henle, K., K. F. Davies, M. Kleyer, C. Margules, and J. Settele. 2004. Predictors of species sensitivity to fragmentation. Biodiversity and Conservation 13:207251.
  • Hockey, P. A. R., W. R. J.Dean, and P. G.Ryan, editors. 2005. Roberts—birds of southern Africa. 7th edition. Trustees of the John Voelcker Bird Book Fund, Cape Town .
  • Johst, K., and R. Brandl. 1997. Body size and extinction risk in a stochastic environment. Oikos 78:612617.
  • Kattan, G., H. Alvarez-López, and M. Girlado. 1994. Forest fragmentation and bird extinctions: San Antonio eighty years later. Conservation Biology 8:138146.
  • Kemper, J., R. M. Cowling, D. M. Richardson, G. G. Forsyth, and D. H. McKelly. 2000. Landscape fragmentation in South Coast Renosterveld, South Africa, in relation to rainfall and topography. Austral Ecology 25:179186.
  • McCoy, E. D., and H. R. Mushinsky. 1994. Effects of fragmentation on the richness of vertebrates in the Florida Scrub habitat. Ecology 75:446457.
  • Malan, G., and R. E. Robinson. 2001. Nest-site selection by Black Sparrowhawks Accipiter melanoleucus: implications for managing exotic pulpwood and sawlog forests in South Africa. Environmental Management 28:195205.
  • Mann, L. L., and S. L. Pimm. 2001. Beyond eight forms of rarity: which species are threatened and which will be next Animal Conservation 4:221229.
  • Mittermeier, R. A., et al. 2006. Lemurs of Madagascar. Conservation International, Washington, D.C.
  • Newton, I. 1998. Population limitation in birds. Academic Press, San Diego, California .
  • Schmiegelow, F. K. A., C. S. Machtans, and S. J. Hannon. 1997. Are boreal birds resilient to forest fragmentation? An experimental study of short-term community responses. Ecology 78:19141932.
  • Serebryakov, V. V., and I. Gorban. 1997. Pallid Harrier Circus macrourus. Page 152 in W. J. M.Hagemeijer and M. J.Blair, editors. The EBCC atlas of European breeding birds—their distribution and abundance. A. D. Poyser, London .
  • Shahabuddin, G., and C. A. Ponte. 2005. Frugivorous butterfly species in tropical forest fragments: correlates of vulnerability to extinction. Biodiversity and Conservation 14:11371152.
  • Thiollay, J., and B.-U. Meyburg. 1988. Forest fragmentation and the conservation of raptors: a survey on the island of Java. Biological Conservation 44:229250.
  • Turner, I. M. 1996. Species loss in fragments of tropical rain forest: a review of the evidence. Journal of Applied Ecology 33:200209.
  • Woodbridge, B., and P. J. Dietrich. 1994. Territory occupancy and habitat patch size of Northern Goshawks in the southern Cascades of California. Pages 8387 in W. M.Block, M. L.Morrison, and M. H.Reiser, editors. The Northern Goshawk: ecology and management. Studies in avian biology 16. Cooper Ornithological Society, Camarillo , California .