skip to main content


Title: Multiple co‐occurring bioeconomic drivers of overexploitation can accelerate rare species extinction risk
Abstract

The unsustainable harvest of species for the global wildlife trade is a major cause of vertebrate extinction. Through the anthropogenic Allee effect (AAE), overexploitation to extinction can occur when a species' rarity drives up its market price, enabling profitable harvest of all remaining individuals. Even in the absence of rarity value, however, the harvest of other species can subsidize the overexploitation of a rare species to the point of extinction, a phenomenon termed opportunistic exploitation. These two pathways to extinction have been considered independently, but many traded species experience them simultaneously.

In this study, we develop a simple model that incorporates these mechanisms simultaneously and demonstrate that including multiple harvest strategies with market‐based feedbacks fundamentally alters rare species extinction risk and the rate at which overexploitation occurs. As a pertinent case study, we consider the harvest of ground pangolinsSmutsia temminckii.

Our results show that pangolin extinction was generally associated with high rarity value, the use of multiple harvest strategies and the simultaneous harvest of a common species that has a fast life history. Pangolin population depletion and short‐term extinction risk were greatest when harvesters used a combination of pursuit and opportunistic (i.e. multi‐species) harvest strategies.

Policy implications.Our results suggest that feedbacks between multiple financial incentives to overharvest can exacerbate the risk of extinction of rare species. As a result, continuing to address AAE and opportunistic exploitation as separate extinction pathways may insufficiently capture extinction risk for many exploited species. Criteria for assessing extinction risk or harvest sustainability of exploited species should incorporate multiple drivers of harvest pressure, with an expanded focus on including species with high rarity value that are exploited in multi‐species harvest regimes.

 
more » « less
Award ID(s):
2052616
NSF-PAR ID:
10494990
Author(s) / Creator(s):
; ;
Publisher / Repository:
John Wiley & Sons Ltd
Date Published:
Journal Name:
Journal of Applied Ecology
Volume:
60
Issue:
5
ISSN:
0021-8901
Page Range / eLocation ID:
754 to 763
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened.

    The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life‐history data, linking similar species based on phylogeny and environmental conditions.

    However, these methods cannot resolve life‐history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life‐history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi‐population data with established life‐history theory, in order to objectively determine similarity between populations based on trait correlations (life‐history trade‐offs) obtained from model fitting.

    We reconstruct 59 unobserved life‐history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross‐validation across different scenarios indicated that life‐histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically.

    Synthesis and applications. The described Bayesian hierarchical method provides access to life‐history traits that are difficult to measure directly and reconstructs missing life‐history information useful for assessing populations and species that are directly or indirectly affected by human exploitation of natural resources. The method is particularly useful for examining populations that are spatially or taxonomically similar, and the reconstructed life‐history strategies described for the principal market tunas have immediate application to the world‐wide management of these fisheries.

     
    more » « less
  2. Abstract

    Defaunation and extinction undermine the resilience and functioning of ecological communities and ecosystems. Relative to other disturbances, overexploitation for the global wildlife trade presents a unique case of trait‐based selection, as demand for specific individuals is often tied to unique morphological or aesthetic traits desired by consumers (‘market traits’). Because evolutionary history leads to species that share both market and functional traits, we posit that non‐random patterns of exploitation will result in non‐random loss of functional diversity.

    We applied a trait‐based framework to the global songbird trade for 4616 species, 148 of which are plausibly threatened by the trade. We quantified select market traits, such as unique coloration and song quality, and ecological traits related to body size, diet, and foraging strategy to assess whether the trade disproportionately threatens particular functional groups. We additionally looked for patterns of association between market traits and functional traits to assess whether selection on certain market traits could drive selection on associated functional traits.

    We found that overexploited birds are a distinct functional subset of the global songbird pool, with the trade disproportionately threatening large bodied, frugivorous, and seed eating birds. Across all songbirds, there were multiple non‐random associations between market traits and functional traits, with the strongest associations observed among trade‐threatened birds; this was consistent with our theory that consumer‐driven selection on market traits could theoretically result in selection on functional traits. However, there was mixed evidence for this hypothesis at a global scale, suggesting that disproportionate threat to functional diversity may be more likely in regions where there is heavy demand for associated market traits.

    Policy implications. Our results highlight the need for increased focus on the mechanistic drivers of trait‐based selection on the consumer side of wildlife trade, and how patterns of overexploitation can systematically affect ecological communities and ecosystem services.

    Read the freePlain Language Summaryfor this article on the Journal blog.

     
    more » « less
  3. Abstract

    A key challenge in conservation biology is that not all species are equally likely to go extinct when faced with a disturbance, but there are multiple overlapping reasons for such differences in extinction probability. Differences in species extinction risk may represent extinction selectivity, a non‐random process by which species’ risks of extinction are caused by differences in fitness based on traits. Additionally, rare species with low abundances and/or occupancies are more likely to go extinct than common species for reasons of random chance alone, that is, bad luck. Unless ecologists and conservation biologists can disentangle random and selective extinction processes, then the prediction and prevention of future extinctions will continue to be an elusive challenge.

    We suggest that a modified version of a common null model procedure, rarefaction, can be used to disentangle the influence of stochastic species loss from selective non‐random processes. To this end we applied a rarefaction‐based null model to three published data sets to characterize the influence of species rarity in driving biodiversity loss following three biodiversity loss events: (a) disease‐associated bat declines; (b) disease‐associated amphibian declines; and (c) habitat loss and invasive species‐associated gastropod declines. For each case study, we used rarefaction to generate null expectations of biodiversity loss and species‐specific extinction probabilities.

    In each of our case studies, we find evidence for both random and non‐random (selective) extinctions. Our findings highlight the importance of explicitly considering that some species extinctions are the result of stochastic processes. In other words, we find significant evidence for bad luck in the extinction process.

    Policy implications. Our results suggest that rarefaction can be used to disentangle random and non‐random extinctions and guide management decisions. For example, rarefaction can be used retrospectively to identify when declines of at‐risk species are likely to result from selectivity, versus random chance. Rarefaction can also be used prospectively to formulate minimum predictions of species loss in response to hypothetical disturbances. Given its minimal data requirements and familiarity among ecologists, rarefaction may be an efficient and versatile tool for identifying and protecting species that are most vulnerable to global extinction.

     
    more » « less
  4. Abstract

    Antarctic fur seals (Arctocephalus gazella) were commercially exploited on the subantarctic island of South Georgia for over 100 years and nearly driven to extinction. Since the cessation of harvesting, however, their populations have rebounded, and they are now often considered a nuisance species whose impact on the terrestrial landscape should be mitigated. Any evaluation of their current population requires the context provided by their historic, pre‐exploitation abundance, lest ecologists fall prey to shifting baseline syndrome in which their perspective on current abundance is compared only with an altered state resulting from past anthropogenic disturbance. Estimating pre‐exploitation abundance is critical to defining species recovery and setting recovery targets, both of which are needed for the International Union for the Conservation of Nature's recent efforts to develop a green list of recovering species. To address this issue, we reconstructed the South Georgia fur seal harvest from 1786 to 1908 from ship logbooks and other historical records and interpolated missing harvest data as necessary with a generalized linear model fit to the historical record. Using an approximate Bayesian computation framework, harvest data, and a stochastic age‐structured population model, we estimated the pre‐exploitation abundance of Antarctic fur seals on South Georgia was 2.5 million females (95% CI 1.5–3.5 million). This estimate is similar to recent abundance estimates, and suggests current populations, and the ecological consequences of so many fur seals on the island, may be similar to conditions prior to human harvest. Although the historic archive on the fur sealing era is unavoidably patchy, the use of archival records is essential for reconstructing the past and, correspondingly, to understanding the present.

    Article impact statement: Defining species recovery requires an understanding of baseline population state, which can be estimated through statistical methods.

     
    more » « less
  5. Abstract

    Increasing harvest and overexploitation of wild plants for non‐timber forest products can significantly affect population dynamics of harvested populations. While the most common approach to assess the effect of harvest and perturbation of vital rates is focused on the long‐term population growth rate, most management strategies are planned and implemented over the short‐term.

    We developed an integral projection model to investigate the effects of harvest on the demography and the short‐ and long‐term population dynamics ofBanisteriopsis caapiin the Peruvian Amazon rainforest.

    Harvest had no significant effect on the size‐dependent growth of lianas, but survival rates increased with size. Harvest had a significant negative effect on size‐dependent survival where larger lianas experienced greater mortality rates under high harvest pressure than smaller lianas. In the populations under high harvest pressure, survival of smaller lianas was greater than that of populations with low harvest pressure. Harvest had no significant effect on clonal or sexual reproduction, but fertility was size‐dependent.

    The long‐term population growth rates ofB. caapipopulations under high harvest pressure were projected to decline at a rate of 1.3% whereas populations with low harvest pressure are expected to increase at 3.2%. However, before reaching equilibrium, over the short‐term, allB. caapipopulations were in decline by 26% (high harvested population) and (low harvested population) 20.4% per year.

    Elasticity patterns were dominated by survival of larger lianas irrespective of harvest treatments. Life table response experiment analyses indicated that high harvest caused the 6% reduction in population growth rates by significantly reducing the survival of large lianas and increasing the survival‐growth of smaller lianas including vegetative reproductive individuals.

    Synthesis and applications. This study emphasizes how important it is for management strategies forB. caapilianas experiencing anthropogenic harvest to prioritize the survival of larger size lianas and vegetative reproducing individuals, particularly in increased harvested systems often prone to multiple stressors. From an applied conservation perspective, our findings illustrate the importance of both prospective and retrospective perturbation analyses in population growth rates in understanding the population dynamics of lianas in general in response to human‐induced disturbance.

     
    more » « less