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Ecology Letters (2011) 14: 886–890 At the heart of our efforts to protect threatened species, there is a controversial debate about whether to give priority to cost-effective actions or whether focusing solely on the most endangered species will ultimately lead to preservation of the greatest number of species. By framing this debate within a decision-analytic framework, we show that allocating resources solely to the most endangered species will typically not minimise the number of extinctions in the long-term, as this does not account for the risk of less endangered species going extinct in the future. It is only favoured when our planning timeframe is short or we have a long-term view and we are optimistic about future conditions. Conservation funding tends to be short-term in nature, which biases allocations to more endangered species. Our work highlights the need to consider resource allocation for biodiversity over the long-term; ‘preventive conservation’, rather than just short-term fire-fighting.
LETTER
When should we save the most endangered species?
Howard B. Wilson,
1
* Liana N
Joseph,
2
Alana L. Moore
3
and
Hugh P. Possingham
4
1
The University of Queensland,
St Lucia, QLD 4072, Australia
2
Wildlife Conservation Society,
2300 Southern Boulevard, The
Bronx, NY 10460, USA
3
University of Melbourne, Parkville,
Victoria 3010, Australia
4
The University of Queensland,
St Lucia, QLD 4072, Australia
*Correspondence: E-mail:
h.wilson1@uq.edu.au.
Abstract
At the heart of our efforts to protect threatened species, there is a controversial debate about whether to
give priority to cost-effective actions or whether focusing solely on the most endangered species will
ultimately lead to preservation of the greatest number of species. By framing this debate within a decision-
analytic framework, we show that allocating resources solely to the most endangered species will typically not
minimise the number of extinctions in the long-term, as this does not account for the risk of less endangered
species going extinct in the future. It is only favoured when our planning timeframe is short or we have a
long-term view and we are optimistic about future conditions. Conservation funding tends to be short-term
in nature, which biases allocations to more endangered species. Our work highlights the need to consider
resource allocation for biodiversity over the long-term; Ôpreventive conservationÕ, rather than just short-term
fire-fighting.
Keywords
Anti-triage, decision theory, endangered species, time-frames.
Ecology Letters (2011)
INTRODUCTION
Conservation budgets are limited and inadequate to conserve the
worldÕs biodiversity and there is increasing pressure for prudent
investment (Balmford et al. 2003; Hoffmann et al. 2010). However,
conservation practitioners and the public alike are often polarised
as to what constitutes the wise use of a limited budget. On one
side, proponents of triage, the process of prioritising the allocation
of limited resources to maximise conservation returns, claim that
resources are limited and the threatened species problem is
sufficiently large that, to maximise the number of species that we
save, the management of species must be prioritised based on
concepts of cost-efficiency (Weitzman 1998a; Possingham et al.
2002; Bottrill et al. 2008; McCarthy et al. 2008; Joseph et al. 2009;
Schneider et al. 2010). This may, under certain circumstances, result
in the decision to not invest in managing highly endangered
species. Iconic or charismatic species, for example, often receive a
disproportionate amount of spending (Male & Bean 2005; Christie
2006), whereas the majority of threatened species receive no, or
very little, funding (Male & Bean 2005). This represents an
opportunity cost; a large number of species could be individually
managed with the money that has been allocated to a few.
Resigning some endangered species to extinction is, however,
socially and politically unpalatable. The alternative point of view is
that this is a defeatistsÕstrategy and that allows policy makers to
give up on highly threatened species that may be expensive to
manage (Mittermeier et al. 1998; Pimm 2000; Marris 2007;
Jachowski & Kesler 2009). The adversaries of the triage philosophy
propose that focusing on the most urgent species now will
maximise our chances of saving the greatest number of species in
the long-term.
These two philosophies are not mutually exclusive. Focusing on the
most urgent species may also be the most cost-effective strategy. Here,
we uncover the conditions under which spending money on the most
endangered of all threatened species may succeed in conserving the
greatest number or nearly the greatest number of species. To do this
we place the debate within a decision-analytic framework, where we
model a set of species and determine the optimal strategy for
allocating resources for a range of conditions. We show that allocating
resources solely to the most endangered species will typically not
minimise the number of extinctions in the long-term as this does not
account for the risk of less endangered species going extinct in the
future. It is only favoured when our planning time frame is short or
we have a long-term view and we are optimistic about future
conditions.
MATERIALS AND METHODS
We defined a model in which every species is in one of three states:
extinct, endangered or recovered. Species that have gone extinct stay
extinct indefinitely, species in the recovered category remain recovered
indefinitely. At every time step, a species iin an endangered state can
(in this order): recover with probability r
i
if management intervention
is enacted at a cost h
i
; recover by chance with a low generic probability
q; or go extinct with probability, p
i
. After each time step, any species
still in an endangered state goes through the same process. The
recovery by chance or serendipitous event can represent a multitude
of different possibilities; including a reduction of anthropogenic
pressures on that species, technical advances or evolving immunity to
a disease. This has been proposed as one argument for focusing
resources on highly endangered species, namely that urgency is a
catalyst for scientific innovation (Pimm 2000) and that scientists
should retain hope for breakthroughs that could lead to recovery
(Jachowski & Kesler 2009).
The probability of species ibeing extant at time t,A
i,t
, is the sum of
being in states endangered or recovered at t. This probability will
depend on the species parameters p
i
,qand r
i
. No management is when
r
i
= 0. So, the increase in the probability of being extant or benefit B
i,t
at time tas a consequence of spending on recovery is: B
i,t
=A
i,t
(p
i
,
q,r
i
))A
i,t
(p
i
,q, 0). The benefit to species iafter ttime steps is:
Ecology Letters, (2011) doi: 10.1111/j.1461-0248.2011.01652.x
2011 Blackwell Publishing Ltd/CNRS
Bi;t¼ðriþð1riÞqÞ1ð1riÞtð1qÞtð1piÞt
1ð1riÞð1qÞð1piÞ

þð1riÞtð1qÞtð1piÞt
qi
1ð1qÞtð1piÞt
1ð1qÞð1piÞ

ð1qÞtð1piÞt:
ð1Þ
The first quantity in equation (1) is the probability of recovery via
intervention alone plus recovery via serendipity if intervention fails
(r
i
+(1 )r
i
)q), summed over all time steps up to time t(multiplied by
the factor in square brackets). The second quantity is the probability
of being in an endangered state at time t, which is the probability of
not having recovered or died: (1 )r
i
)
t
(1 )q)
t
()p
i
)
t
. The third and
fourth quantities are the same except for the case where no resources
are spent on recovery (i.e. r=0).
The cumulative cost at time tis:
Ci;t¼hi
1ð1riÞtð1qÞtð1piÞt
1ð1riÞð1qÞð1piÞ

ð2Þ
and the cost-effectiveness, R
i,t
, is the benefit divided by the cost.
When t=1:R
i,1
=(1)q)(p
i
c
i
), where c
i
=h
i
r
i
, which is the
expected total cost of a successful recovery (the cost of a recovery
programme divided by the likelihood of success). As t޴:R
i,¥
=
(1 )q)(1 c
i
)+(qh
i
)(1 )[1 )(1 )r
i
)(1 )q)(1 )p
i
)] [1 )(1 )q)
(1 )p
i
)]). Two key parameters were estimated for 32 endangered
species from New Zealand (Joseph et al. 2009), the probability of
extinction, p
i
and the expected total cost of a successful recovery,
c
i
(= h
i
r
i
). These parameters spanned a range of values from highly
endangered, but expensive to recover, to a smaller probability of
extinction, but less costly to recover (Fig. 1). The data for the 32
endangered species are listed in table 1 in Joseph et al. 2009, from
which we also use the cost (=h
i
), the probability of success (=r
i
) and
the benefit, B
i
. The annual probability of extinction used here, p
i
,is
calculated as 1 )(1 )p
i,50
)
150
, where p
i,50
is the probability of
extinction within 50 years (=B
i
). The recovery probability, r
i
, equals
the probability of success, although we assume here that the whole
recovery plan can be enacted in 1 year.
We wished to determine how to allocate resources between these
species solely to maximise the number of species extant at time
horizon t
H
, for a given budget. We also explored a different objective
function; maximise the total number of species alive in every year up
to time horizon t
H
. This places value on a species being alive for some
time, even if they are not alive at the time horizon. An objective such
as this may be particularly politically palatable, as species alive now
may ÔbenefitÕcitizens now, even if the species subsequently go extinct.
This objective function is equivalent to maximising the total number
of Ôspecies yearsÕor, equivalently, maximise the sum of the number of
species alive in each year up to time horizon t
H
. In this case, the
benefit at time tis PB
i,j
, where the sum is over j=1tot, and the cost
is the same as before (see Supporting Information). We have not
employed a discount factor, so that species alive in any year have the
same value. Whether discounting is relevant here, and what level and
type of discounting to use, is contentious for such problems with a
social concern (Heal 1998; Weitzman 1998a; Moore et al. 2008),
although there is evidence that people would rather have benefits now
as opposed to the future. None of our results would be qualitatively
changed if a discount factor was employed, although there would be
more emphasis on keeping species alive in the short-term.
RESULTS
Consider a fixed allocation of resources, i.e. the cost-efficiency of
directing resources solely at one species when compared with another.
Maximising the total number of species extant at t
H
for a fixed budget,
is achieved by spending on those species with the highest cost-
effectiveness, R
i,t
. When we ignored the possibility of fortuitous
serendipitous events (i.e. q=0) and we considered only one time step
(i.e. t
H
=1), then R
i,1
=p
i
c
i
(Materials and Methods). When the
timeframe was short, the benefit gained was the probability of
extinction (without management) divided by the expected cost, and
the optimal strategy was to allocate resources to the species with the
highest p
i
c
i
(Fig. 1a), i.e. species that have high extinction probabil-
ities and low expected recovery cost. In the short-term, at least for
species with equal cost, the benefit was weighted to species that are
more endangered, as there is little benefit to recovering a species with
a low probability of extinction as it would be very likely to survive
even without management. However, even for short-time horizons,
when there are differential costs between species, allocating resources
based on risk of extinction alone will not maximise the number of
species extant.
As the time horizon of the planning process increased, the optimal
strategy was to allocate resources to the species with the lowest expected
cost of recovery (Fig. 1b). When r
i
= 1 (and q=0) and species only
differed in the cost of recovery, then R
i,t
=[1 )(1 )p
i
)
t
]h
i
. When t
is large, even species with a low risk of extinction were likely to become
extinct within the timeframes considered and R
i,t
converged to 1 h
i
,
converging quicker for higher p
i
(when r
i
1, then R
i,t
converged to
1c
i
, Materials and Methods). As the time horizon increased, species with
a high probability of extinction, but also high cost became relatively less
cost-effective. There was a switch to spending on less endangered and
easier to recover species, and a focus on maximising the total number of
recovered species as opposed to minimising the number of short-term
extinctions (Fig. 1c). When this switch occurred depended on the
precise distribution of costs and extinction probabilities (see also Hartig
& Drechsler 2008). Spending on less endangered species meant a short-
term loss for a long-term gain; in the short-term, there would be
relatively fewer species extant when compared with spending on more
endangered species, whereas at longer time periods, there would
be relatively more species extant (Fig. 2). A focus on a longer planning
horizon changed some of the allocation of resources away from the
more endangered New Zealand species to the less endangered, but
cheaper to recover species (Fig. 1d). The extent of this difference
(i.e. which species are funded) between short- and long-time horizon
strategies depends on the precise specifics of species costs and
probabilities of extinction.
When there was optimism about the future, i.e. q>0, for short-
time horizons the optimal allocation between species remained the
same, but the benefit gained was weighted by the probability of no
serendipitous event; R
i,1
=(1)q)p
i
c
i
(Materials and Methods). For
longer time horizons, there were benefits to keeping as many species
extant as possible in the hope that they will recover. The result is a
species allocation intermediate between short (Fig. 1a) and long
(Fig. 1b) time horizons (Fig. 3a). An objective function that seeks to
maximise the total number of species alive in every year up to time
horizon t
H
also results in allocating resources to more endangered
species in a very similar way to optimism about the future (Fig. 3b).
When resources can be switched from one species to another
dynamically with time, determining the optimal solution required
2H. B. Wilson et al. Letter
2011 Blackwell Publishing Ltd/CNRS
Stochastic Dynamic Programming (Supporting Information).
We found very similar results to when looking at a fixed allocation
of resources; namely, when there was a long time to the time horizon,
then resources were spent on less endangered, but cheaper to recover
species, but as the time horizon approached, resources were switched
to spending on more endangered, but expensive to recover species.
The only scenarios when resources were directed first at highly
endangered, expensive species were when the original time horizon
was short or when the budget was very large compared with the cost
of recovering all species (so that all species could be recovered).
DISCUSSION
Our results highlight two basic strategies: for short time horizons,
minimise the number of extinctions in the short-term by allocating
resources to the species with the highest ratio of the probability of
extinction to cost; for long-time horizons, recover as many species as
possible by allocating resources based on the lowest expected cost of
recovery. Allocating resources to the most endangered species will not
typically maximise the number of species saved, as this does not take
into account the risk of less-endangered species going extinct in the
future. This result has parallels in the dynamic conservation planning
literature (e.g. Naidoo et al. 2006), although conservation planning also
incorporates concepts such as dependencies and complementarity,
and in reserve site selection studies that include the likelihood of
unprotected land parcels being converted to alternative uses other
than conservation (Costello & Polasky 2004; Meir et al. 2004; Harrison
et al. 2008); analogous to an unrecovered species going extinct here.
Allocating resources to the most endangered species will be closer to
optimal when: (1) the time-period considered is short; (2) we are
optimistic about the future conditions for management of biodiversity;
(3) if the conservation resources are large relative to the number of
threatened species; and (4) if we value species that are alive now even if
they then go extinct. Conditions (1) and (2) do not act synergistically
though, as optimism over future conditions is only beneficial when
considering long time-scales. More generally, these conditions are
unlikely as: (1) long time-frames must be considered if species are to be
conserved in perpetuity; (2) the threats to biodiversity are increasing and
conservation efforts for threatened species are not sufficient (Stokstad
2010), despite major gains in conservation spending and international
(a)
(c)
(b)
(d)
Figure 1 The allocation of resources for strategies with different time horizons. (a) Contour plots of lines of equal cost-effectiveness for a 1-year time horizon with no species
recovery by chance. All points (or species) that fall on the same line have equal cost-effectiveness, species below the line are more cost-effective and species above are less cost-
effective. (b) A 100-year time horizon with no species recovery by chance. (c) Schematic showing how the allocation of funds moves from more endangered, but expensive to
recover species when only a short-time horizon is considered (the area under the straight diagonal line with hatching at 45
o
) to less endangered, but cheaper to recover species
when a longer time horizon is considered (the area under the curve with hatching at 135
o
). A linear scale for the probability of extinction is used to more clearly show the
differences. Species in the cross-hatched area in the bottom right are allocated resources under both time horizon scenarios. The graph assumes a uniform distribution of
species across the parameter space, so that the total area hatched under each curve is proportional to the total number of species-allocated resources (there is an equal budget
for both strategies). (d) The New Zealand species allocated resources under a fixed budget of $80 million. All species under the curves are funded. The straight line assumes a
planning horizon of 1 year and the curve a 100-year planning horizon. The points on graphs a, b and d are 32 endangered species from New Zealand (Joseph et al. 2009), and
the expected recovery cost is in NZD$M.
Letter Saving endangered species 3
2011 Blackwell Publishing Ltd/CNRS
targets for protected areas; and (3) resources for conservation are grossly
inadequate (Balmford et al. 2003; Hoffmann et al. 2010).
There are other arguments for directing resources to highly
endangered species not considered here. These principally include
that citizens often place greater value on charismatic species; many of
the most endangered species are large animals with large ranges, and
so conservation of their habitat spills over into conservation benefits
for other species, and conservation budgets focused on the most
charismatic will tend to grow with time. Assigning a cultural,
economic or ecological value to a species is a notoriously difficult
task. However, if each species was assigned a value or weighting, w
i
,
then these can be simply included within our framework by weighting
the cost-effectiveness of each species, R
i,t
, i.e. R
i,t
(new)=w
i
R
i,t
,
exactly as in the NoahÕs Ark framework (Weitzman 1998b). The result
is that more resources would be directed to the more valued species.
Some endangered species will indeed act as umbrella species, but this
is not a trait restricted solely to charismatic species. Furthermore,
many conservation actions are species-specific and site-specific, as
endangered species often do not overlap in range and do not
necessarily require the same management actions. Finally, growing
conservation budgets are also not restricted to charismatic species
(Joseph et al. 2011). Consequently, some of these issues will direct
more funding to highly endangered species, whereas others are not
restricted to highly endangered species or may not applicable. None of
them invalidate the general results presented here.
One last point concerns uncertainty and risk. A possible justification
for spending on highly endangered species is that protecting species
that are most likely to go extinct now is a risk-averse strategy.
By keeping more species alive in the short-term, it provides the best
environment to take advantage of future unseen events. We have
attempted to look at this through the use of a probability of future
unseen events helping to recover a species by chance, which results in
a greater weighting of resources to more endangered species.
However, there are clearly more issues around uncertainty than
addressed here.
Conservation funding tends to be short-term in nature, which biases
allocations to more endangered species. However, our results show
that, as in medicine (Messonnier et al. 1999), more emphasis should be
Figure 2 The number of species extant under different resource allocation
scenarios. An $80 million budget is allocated in year 1 based on three different
allocation scenarios for the New Zealand species, and each curve then represents
the number of species extant each year over the next 100 years. (a) The full line
allocates resources to the species with the highest cost-effectiveness assuming a
100-year planning horizon (typically species with low expected recovery costs).
(b) The dotted, light line allocates resources assuming a planning horizon of only
1 year (species that have high extinction probabilities and low expected recovery
costs; the highest p
i
c
i
first). (c) The dashed, heavy line (lowest) allocates resources
to the most endangered species first (highest probability of extinction first). In each
year, species still in the endangered state go extinct with probability p
i
. The curves
are the average over 1000 simulations. The variances around these curves are very
small, so for clarity are not shown.
(a)
(b)
Figure 3 Contour plots of lines of equal cost-effectiveness. (a) The effects of
positive events in the future. The full lines assume a time horizon of 100 years and
no species recovery by chance, and the dotted lines assume a time horizon of
100 years and a probability of recovery by chance of 0.05 each year. The effect of
serendipity is to allocate more resources to species with a high probability
of extinction and high recovery cost at the expense of species with a lower
probability of extinction and lower recovery cost. (b) The effect of a different
objective function. All the lines are for a time horizon of 100 years with no species
recovery by chance. The full lines are for an objective function which maximises the
number of species alive at 100 years. The dotted lines are for an objective function
that maximises the total number of species alive in every year up to 100 years. The
effect of valuing extent species even if they do not survive to the time horizon is to
allocate more resources to species with a high probability of extinction and high
recovery cost at the expense of species with a lower probability of extinction and
lower recovery cost, as in (a). The expected recovery costs are in NZD$M and the
diamond points are 32 endangered species from New Zealand.
4H. B. Wilson et al. Letter
2011 Blackwell Publishing Ltd/CNRS
placed on long-term Ôpreventive conservationÕrather than short-term
Ôfire-fightingÕ. Allocating resources to the most endangered of all
threatened species, regardless of cost, may be a logical consequence of
short-term thinking and great optimism about the future.
ACKNOWLEDGEMENTS
We thank Richard Fuller and Madeleine Bottrill for helpful comments.
The work was supported by the Centre for Applied Environmental
Decision Analysis, a Commonwealth Environmental Research Facility
Hub funded by the Australian Government Department of
Environment, Water, Heritage and the Arts.
AUTHORSHIP
HPP designed the study; HBW and AM contributed to the research,
modelling and analysis of data; HBW and LNJ wrote the paper.
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online
version of this article:
Appendix S1 Derivation of the benefit function with the alternative
objective function and details of the the stochastic dynamic
programming.
As a service to our authors and readers, this journal provides
supporting information supplied by the authors. Such materials are
peer-reviewed and may be reorganized for online delivery, but are not
copy edited or typeset. Technical support issues arising from
supporting information (other than missing files) should be addressed
to the authors.
Editor, Stephen Polasky
Manuscript received 21 March 2011
First decision made 1 May 2011
Manuscript accepted 9 June 2011
Letter Saving endangered species 5
2011 Blackwell Publishing Ltd/CNRS
... even after the immediate threats have been averted. Genomic erosion is manifested as: (1) a loss of genetic diversity, (2) an elevated realised load (that is, the component of genetic load whose fitness effects is expressed 9 , and which is caused by an increased number of homozygous loci with recessive deleterious alleles), (3) a mismatch between genetic adaptations and the prevailing environmental conditions (i.e., maladaptation), and (4) genetic introgression due to hybridisation. All four aspects of genomic erosion can reduce individual fitness and undermine viability of populations, both in the short-and long-term 8,29,37,38,39,40 . ...
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Many species are facing unprecedented population size declines and deterioration of their environment. This exposes species to genomic erosion, which we define here as the damage inflicted to a species' genome or gene pool due to a loss of genetic diversity, an increase in expressed genetic load, maladaptation, and/or genetic introgression. The International Union for Conservation of Nature (IUCN) bases its extinction risk assessments on direct threats to population size and habitat. However, it does not assess the long-term impacts of genomic erosion, and hence, it is likely to underestimate the extinction risk of many species. High-quality whole genome sequence data that is currently being generated could help improve extinction risk assessments. Genomic data contains information about a species' past demography, its genome-wide genetic diversity, the incidence of genetic introgression, as well as the genetic load of deleterious mutations. Computer modelling of these data enables forecasting of population trajectories under different management scenarios. In this Perspective, we discuss the threats posed by genomic erosion. Using evolutionary genomic simulations, we argue that whole-genome sequence data provides critical information for assessing species extinction risk and recovery potential. Genomics-informed assessments of the extinction risk complement the IUCN Red List, and such genomics-informed conservation is invaluable in guiding species recovery programs in the UN's Decade on Ecosystem Restoration and beyond.
... Currently prioritisation is usually based on threat level or extinction risk (Wilson et al., 2011), net benefits to biodiversity , climate factors (Gilbert et al., 2020) or cost-effectiveness (Martin et al., 2018;Carwardine et al., 2019), often on the basis of expert opinion (Hagerman et al., 2010;Runge et al., 2011;Hagerman and Satterfield, 2013;Carwardine et al., 2019). Alternatively, priorities emerge from government without a clear explanation (e.g. ...
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While the imminent extinction of many species is predicted, prevention is expensive, and decision-makers often have to prioritise funding. In democracies, it can be argued that conservation using public funds should be influenced by the values placed on threatened species by the public, and that community views should also affect the conservation management approaches adopted. We conducted on online survey with 2400 respondents from the general Australian public to determine 1) the relative values placed on a diverse set of 12 threatened Australian animal species and 2) whether those values changed with the approach proposed to conserve them. The survey included a contingent valuation and a choice experiment. Three notable findings emerged: 1) respondents were willing to pay $60/year on average for a species (95% confidence interval: $23 to $105) to avoid extinction in the next 20 years based on the contingent valuation, and $29 to $100 based on the choice experiment, 2) respondents were willing to pay to reduce the impact of feral animals on almost all presented threatened species, 3) for few species and respondents, WTP was lower when genetic modification to reduce inbreeding in the remaining population was proposed.
... This places a premium on identifying conservation priorities (Myers et al. 2000). Setting priorities is an essential step for biodiversity conservation, with the ultimate goal of optimizing resources in space and time (Wilson et al. 2011). Prioritization systems primarily focus on the identification of target species to which allocate the limited resources commonly available (Mace et al. 2007). ...
Chapter
The Himalaya, one of the global biodiversity hotspots, harbors a rich diversity of medicinal flora. The Jammu, Kashmir and Ladakh regions, located in the northwestern side of the Himalaya, represent a wide elevational gradient with diverse habitats teeming with valuable biological resources, including wealth of medicinal plant species. It is in this context that the present chapter provides an updated systematic synthesis of medicinal flora of Jammu, Kashmir and Ladakh Himalayas. A total of 1123 plant species belonging to 564 genera in 137 families have been documented which are used for medicinal purposes in these regions. However, this rich resource of medicinal plants is currently facing various threats in their natural habitats. Therefore, as a step towards conservation prioritization, 100 medicinal plant species have been identified that need immediate conservation action for their sustainable utilization. Hopefully, the present systematic synthesis on the medicinal flora of these three Himalayan regions will guide the evidence-based and target-orientated conservation policy and practice.
... Like many other management interventions, supplementation is currently more likely to occur for threatened species at risk of imminent extinction, given the high cost and risk of unintended consequences (Brichieri-Colombi and Moehrenschlager 2016, Wilson et al. 2011). However, there is considerable empirical evidence demonstrating that such interventions are more likely to be successful at earlier stages of species decline (Gri th et al. 1989). ...
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Tasmanian populations of the eastern quoll Dasyurus viverrinus, which represent the last wild stronghold of this species after its extirpation from the Australian mainland, have experienced declines of more than 50% over the past three decades. In this pilot study, we investigate the feasibility of supplementing wild populations with captive-bred individuals to attempt to reverse observed declines. Our results are encouraging, in that we recorded high initial survival and low initial dispersal of captive-bred individuals relative to previous release attempts in mainland Australia. Further work is ongoing to determine long-term survival of released individuals and the genetic and population-level impacts on local populations. Our preliminary results support the use of population supplementation as an effective conservation action, which allows for early intervention to address species declines while simultaneously testing hypotheses about their underlying causes.
... Like many other management interventions, supplementation is currently more likely to occur for threatened species at risk of imminent extinction, given the high cost and risk of unintended consequences (Brichieri-Colombi and Moehrenschlager 2016, Wilson et al. 2011). However, there is considerable empirical evidence demonstrating that such interventions are more likely to be successful at earlier stages of species decline (Gri th et al. 1989). ...
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Full-text available
Tasmanian populations of the eastern quoll Dasyurus viverrinus, which represent the last wild stronghold of this species after its extirpation from the Australian mainland, have experienced declines of more than 50% over the past three decades. In this pilot study, we investigate the feasibility of supplementing wild populations with captive-bred individuals to attempt to reverse observed declines. Our results are encouraging, in that we recorded high initial survival and low initial dispersal of captive-bred individuals relative to previous release attempts in mainland Australia. Further work is ongoing to determine long-term survival of released individuals and the genetic and population-level impacts on local populations. Our preliminary results support the use of population supplementation as an effective conservation action, which allows for early intervention to address species declines while simultaneously testing hypotheses about their underlying causes.
... If mining commences at a vent, the rapid impacts could mean that any endemic species will likely be extinct before they are listed in a more threatened category (Niner et al., 2018). A precautionary approach to IUCN Red List assessments provides greater opportunity for policy makers to establish appropriate protection for the species before disturbance, ensuring more proactive and preventative conservation rather than reactive "fire-fighting" measures (Wilson et al., 2011;Walls, 2018;Le Breton et al., 2019). The implementation of effective conservation measures would lead to a genuine change in the IUCN Red List status of a species. ...
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Hydrothermal vents are rare deep‐sea oases that house faunal assemblages with a similar density of life as coral reefs. Only approximately 600 of these hotspots are known worldwide, most only one‐third of a football field in size. With advancing development of the deep‐sea mining industry, there is an urgent need to protect these unique, insular ecosystems and their specialist endemic faunas. We applied the IUCN (International Union for the Conservation of Nature) Red List criteria to assess the extinction risk of vent‐endemic molluscs with varying exposure to potential deep‐sea mining. We assessed 31 species from 3 key areas under different regulatory frameworks in the Indian, West Pacific, and Southern Oceans. Three vent mollusc species were also examined as case studies of different threat contexts (protected or not from potential mining) to explore the interaction of local regulatory frameworks and IUCN Red List category assignment. We found that these assessments were robust even when there was some uncertainty in the total range of individual species, allowing assessment of species that have only recently been named and described. For vent‐endemic species, regulatory changes to area‐based management can have a greater impact on IUCN Red List assessment outcomes than incorporating additional data about species distributions. Our approach revealed the most useful IUCN Red List criteria for vent‐endemic species: criteria B and D2. This approach, combining regulatory framework and distribution, has the potential to rapidly gauge assessment outcomes for species in insular systems worldwide. This article is protected by copyright. All rights reserved
... It may also be valuable for managers seeking to develop shortterm conservation plans to use priority schemes for timescales closer to midcentury, as several inland species ranked higher for immediate habitat loss due to urbanization by 2025 than species experiencing habitat loss from SLR by 2025. Additionally, efforts to prevent population declines or extinction of rare species may benefit more from long-term planning than short-term triage, meaning that vulnerability metrics for longer time horizons are optimal (Wilson et al. 2011). Differing conservation timelines and goals will mean that managers need multiple lines of evidence in order to make informed decisions and appropriately allocate resources. ...
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Effective management of wildlife populations benefits from an understanding of the long-term vulnerability of species to anthropogenic stressors. Exposure to potential habitat change is one measure of vulnerability that wildlife managers often use to assess and prioritize individual species or groups of species for resource allocation or direct management actions. We used species distribution models for 15 species occurring in the coastal plain ecoregion of Georgia to estimate the current amount and distribution of potential habitat and then predict exposure to changes in habitat due to inundation from sea level rise (using the Sea Level Affecting Marshes model) and urban growth (using the Slope Land-use Excluded Urban Topology Hillshade Growth model) for four future time points. Our results predict that all focal species were likely to experience some exposure to habitat change from either sea level rise or urbanization, but few species will experience high exposure to change from both stressors. Species that use salt marsh or beach habitats had the highest predicted exposure from sea level rise (25–69%), while species that use more inland habitats had the highest predicted exposure to urban growth (10–20%). Our models are a resource for managers considering tradeoffs between prioritization schemes under two future stressors. Results suggest that managers may need to prioritize species (or their habitats) based on the predicted magnitude of habitat loss, while also contextualizing prioritization with respect to the current amount of available protected habitat and species global vulnerability.
... Many factors influence the intensity of opportunistic exploitation, but we conclude that the factors most critical to predicting depletion rate are profitability of capturing the common species and abundance of the common species. Conservation budgets are insufficient to conserve all of the world's biodiversity, and there is increasing pressure for triage investment (Balmford et al., 2003;Wilson et al., 2011). Giving resources to the most endangered or charismatic species will not usually maximize the number of species saved (Balmford et al., 2003). ...
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Extinction rates are increasing globally, and direct exploitation is an important driver. Many pathways have been proposed to explain how exploitation can lead to extinction. One of these proposed but understudied multispecies pathways is opportunistic exploitation, which occurs when a highly valuable but rare species is encountered and targeted during exploitation of a less valuable, but more common, target species. Using individual-based simulations of exploiters in a two-species spatial model, we contribute evidence which supports that opportunistic exploitation increases depletion when compared to single-species exploitation, and is as detrimental to the more valuable, rare species as the anthropogenic Allee effect (where price increases with rarity) and the Allee effect (where population growth declines at low abundance). The most important factors affecting the impact of opportunistic exploitation are gross revenue and abundance of the more common, less valuable species, while ease of capture and growth rate of the more common, less valuable species are less important. Thus, valuable but rare species are most at risk when harvested alongside low-value abundant species; this information is relevant for managers focused on protection of rare species in multispecies systems.
... 2,3 Ever increasing demand of medicinal plants along with the habitat destruction, the world is experiences the principal challenge of minimizing loss of biodiversity 4,5 by conservation efforts. Further, few conservationists have tried prioritization of conservation efforts 6,7 due to higher number of extinction rate. 8,9 Number of medicinal plant species is now described under different threat categories 10 and in the immediate future, many species may warrant the declaration of a threatened status until adequate scientific data are available. ...
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The communication assesses the high-value medicinal plants reported in Pindari Valley, Nanda Devi Biosphere Reserve, Uttarakhand, using a score-based method for prioritization and conservation. A total of 42 high-value medicinal plants were assessed, prioritized and scored on the basis of rapid threat assessment. Maximum threat was recorded for Aconitum heterophyllum followed by Picrorhiza kurrooa and Nardostachys jatamansi given their limited number of individuals observed in the study area as well as high utilization patterns. Minimum threat status was recorded for Epilobium angustifolium, where the species was found in higher density in its natural habitat. Among the recorded species, 64% were observed growing in grassland/alpine pastures and open/alpine slopes. 55% of species were native/endemic to Himalaya and 48% were extracted by the inhabitants. Underground portions (roots/rhizomes/tubers) of 40% of the species were utilized leading to destruction in natural habitat. Out of 42 medicinal plants, 16 species have been prioritized for conservation and recognized in different threat categories and most of these species are collected from natural habitat without scientific knowledge. Conclusion of the study might helpful for identifying threatened plants in the region so as to initiate sustainable use and conservation practices of high-value medicinal plant resources.
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Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.
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Context: Because human and financial resources are limited, health efforts must focus on prevention strategies that yield the most benefit for the investment. Many current strategies identified in the literature offer opportunities to promote health at a reasonable cost.
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Summary • Factors that have been considered when deciding how to invest resources in conservation of species include the efficacy and cost of management, the importance of the species, the level of threat, and the timeframe over which results are to be achieved. However, it is unclear how each of these different factors should be weighted and combined when making a decision. • We examine how the probabilities of species changing in IUCN Red List categories are influenced by expenditure of resources. We use these relationships to determine optimal investment strategies, using Australian birds as a case study. • The optimal level of investment in different species depends critically on whether managers wish to minimize the number of extinct species or a weighted average of all threatened species, and on the available budget. The level of investment should not necessarily reflect the level of threat. In our case study, the timeframe of management had little influence on the investment decision. • Our results show that extinctions of Australian birds can be largely avoided over the next 80 years given current expenditure, but greater investment in conservation is required to reduce the number of threatened species. • Synthesis and applications. The most efficient allocation of resources to conserve species is difficult to determine intuitively; therefore, this decision demands the use of formal decision theory. The influence of the particular management objective on the optimal decision means that this feature needs careful consideration. Our approach can be used to determine the level of investment that is required to reduce the number of threatened species.
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Using data for 25,780 species categorized on the International Union for Conservation of Nature Red List, we present an assessment of the status of the world's vertebrates. One-fifth of species are classified as Threatened, and we show that this figure is increasing: On average, 52 species of mammals, birds, and amphibians move one category closer to extinction each year. However, this overall pattern conceals the impact of conservation successes, and we show that the rate of deterioration would have been at least one-fifth again as much in the absence of these. Nonetheless, current conservation efforts remain insufficient to offset the main drivers of biodiversity loss in these groups: agricultural expansion, logging, overexploitation, and invasive alien species.
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Since passage of the Endangered Species Act in 1973, over 1300 endangered and threatened species have been protected in the USA and its territories. Most species continue to face a significant risk of extinction, but the status of many species is improving. Here we present analyses of federal agency reports to the United States Congress (1988–2002) that describe differences in species status and show which variables are correlated with improving or declining status. We found that 52% of species showed repeated improvements or were not declining over this time. Species status improves over time, with only 35% still declining 13 years or more after protection. Taxonomy, funding by US Fish and Wildlife Service and National Oceanic and Atmospheric Administration, and agency assessment of risk of extinction and potential to recover were significantly correlated with status.
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Prioritization of conservation efforts for threatened and endangered species has tended to focus on factors measuring the risk of extirpation rather than the probability of success and cost. Approaches such as triage are advisable when three main conditions are present: insufficient capacity exists to adequately treat all patients, patients are in a critical state and cannot wait until additional capacity becomes available, and patients differ in their likely outcome and/or the amount of treatment they require. The objective of our study was to document the status of woodland caribou (Rangifer tarandus) herds in Alberta, Canada, with respect to these three conditions and to determine whether a triage approach might be warranted. To do this we modeled three types of recovery effort – protection, habitat restoration, and wolf control – and estimated the opportunity cost of recovery for each herd. We also assessed herds with respect to a suite of factors linked to long-term viability. We found that all but three herds will decline to critical levels (<10 animals) within approximately 30 years if current population trends continue. The opportunity cost of protecting all ranges by excluding new development, in terms of the net present value of petroleum and forestry resources, was estimated to be in excess of 100 billion dollars (assuming no substitution of activity outside of the ranges). A habitat restoration program applied to all ranges would cost several hundred million dollars, and a provincial-scale wolf control program would cost tens of millions of dollars. Recovery costs among herds varied by an order of magnitude. Herds also varied substantially in terms of their potential viability. These findings suggest that woodland caribou in Alberta meet the conditions whereby triage should be considered as an appropriate conservation strategy.
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Threatened species lists are designed primarily to provide an easily understood qualitative estimate of risk of extinction. Although these estimates of risk can be accurate, the lists have inevitably become linked to several decision-making processes. There are four ways in which such lists are commonly used: to set priorities for resource allocation for species recovery; to inform reserve system design; to constrain development and exploitation; and to report on the state of the environment. The lists were not designed for any one of these purposes, and consequently perform some of them poorly. We discuss why, if and how they should be used to achieve these purposes.
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We analyze the problem of choosing sites through time to include in a network of biological reserves for species conservation. When sites cannot all be protected immediately, and excluded sites are threatened by development, planning should factor in both expected biodiversity benefits of sites and development risk. We formulate this problem as a stochastic dynamic integer-programming problem. We find that the timing of selections is critical; conservation budgets available up front yield significantly greater biodiversity protection. We also compare results using optimal and heuristic algorithms. The theory is applied to vertebrate and development threat data from southwestern California.