A
risk assessment system for screening out
invasive pest plants
Curt
Daehler and Julie
Denslow
report
based
on the following peer-reviewed publication:
Daehler, C. C., J. S. Denslow, S. Ansari, and H. Kuo. 2004. A risk assessment
system for screening out
invasive pest plants from Hawai'i and other Pacific
Islands. Conservation Biology 18:360-368.
Summary of Findings
We tested the ability of a modified version of the Australia and New Zealand weed risk assessment system to identify pest plants in Hawai‘i and other Pacific Islands. We used information taken from outside Hawai‘i to predict the behavior (“pest” or “not a pest”) for almost 200 plant species introduced to Hawai‘i and other Pacific Islands. The screening system initially recommended further evaluation for 24% of these species, but an additional secondary screening was applied to this group, thereby reducing the rate of indecision to only 8%. To independently test the accuracy of the screening system, we compared its decisions (pest or not a pest) to opinions of 25 expert botanists and weed scientists who had substantial field experience in Hawai‘i or other Pacific Islands. We asked the experts to rate each species as “major pest”, “minor pest” or “not a pest” in native or managed ecosystems. The screening system correctly identified 95% of major pests and correctly identified 85% of nonpests. Among minor pests identified by the experts, 33% were classified as nonpests by the screening system. Use of the screening system to assess proposed plant introductions to Hawai‘i or other Pacific Islands and to identify high-risk species used in horticulture and forestry would greatly reduce future pest plant problems and allow entry of most nonpests. The screening process is objective, rapid, and cost-efficient. With minor modifications, it is likely to be useful in many parts of the world.
1)
Between
December 2001 and June 2002, approximately 200 plants were scored using the WRA
system. About half of the plants were chosen from the Maui County Planting list.
The remaining plants were taken from other planting lists for Hawai‘i or for
other parts of the Pacific.
2)
Based on
their WRA scores, species were placed into the following categories: Accept
(not likely to be a pest; WRA score < 1 ), Reject
(likely to be a pest; WRA score > 6), or Evaluate
(requires further evaluation; WRA score = 1-6). About 27% of the species fell in
the “Evaluate” category, and these species were passed through a second
screening, which resulted in a quick decision (Accept or Reject) for most
species originally in the “Evaluate” category.
Details for the second screening (used for species scoring between 1 and
6)
3)
In order
to judge reliability of the WRA scores, the same list of 200 plant species was
sent to 25 expert botanists/weed scientists who had first hand, detailed
knowledge of invasive plant or weed problems in Hawai‘i and other Pacific
Islands. Some of the experts worked primarily in native ecosystems while others
worked in managed ecosystems (e.g. agriculture or forestry plantations). These
experts were asked to rate the 200 species as “major pest”, “minor pest”
or “not a pest”, either currently or in the future.
Definitions of major, minor and not a pest
4)
WRA
decisions were compared with the responses from the 25 experts to obtain an
independent assessment of how well the WRA system worked in Hawai‘i.
5)
Of the
200 species on the survey list, 172 species were used for the final analyses.
Species that were rated by fewer than 3 of the expert surveyors were excluded.
We also excluded species native to Hawai‘i and species that were
taxonomically uncertain. The list of species NOT included in the
analysis is provided here.
After
determining WRA scores for all species and passing species in the
“Evaluate” category through a second
screen, a decision was obtained for 92% of the species on the survey
list. The assessment process
takes about 6 hours.
Species
list with WRA scores used for analysis (172 species)
Anyone who spends
time around plants develops personal opinions about whether certain plants are
desirable or not. These opinions differ widely, based on personal experiences,
and they have generated much disagreement, particularly with respect to
assessing plant invasiveness. The WRA system that we employed in this study
minimizes the role of personal opinion during the assessment process. The WRA is
based on answers to about 50 questions, each relating in a logical or scientific
(statistical) way to the risk of a plant becoming a pest. The answer to any one
question doesn’t tell you much about whether a species is likely to become
invasive, but by answering a series of independent questions, we can identify
high risk species or pests, as our results have shown. Objectivity is maintained
because
1)
The same set of questions was answered for each species.
2)
Consistent,
pre-determined criteria were established for determining when a question should be answered “yes” or “no”.
3)
For each answer, the source (reference) was recorded, allowing anyone to
evaluate the source of information used in an assessment. Anecdotal information
or information appearing to be derived from personal opinion was avoided during
the assessment process. Answers to
question in the WRA most commonly came from: scientific journal articles,
reference books, electronic databases, and the Internet.
Furthermore, because
the final assessment is based the additive contribution of each answer, changing
one answer or adding an additional answer will usually not change the decision
for an assessment. Nevertheless, if
new information comes to light after an assessment has been made, that new
information can easily be incorporated to obtain a revised WRA score.
If the WRA system “rejects” too many species that are not really
pests, then attempting to follow the recommendations of the WRA system could
potentially lead to unnecessary economic hardships. We found that most plant
species were “Accepted” using the WRA system. The
“Accepted” plants were extremely diverse and include popular landscape
plants. Although we have only assessed a sample of 200 species, most of the
“staple” species for the landscape industry that we have assessed so far
received an “accept” rating. Among our sample of 200 species, 61% had an
“accept” rating, but about 70 species on our list were forestry species already
suspected of being invasive by US Forest Service personnel. The “accept”
rate among common landscaping plants on our list was around 90%.
Let’s examine the list of species “rejected” by
the WRA system but not generally found to be pests according to the expert
surveys (Table 3).
There are two interpretations of any disagreement between the WRA results and
the expert surveys. First, the WRA may be wrong. Although information was found
that makes these species statistically likely to be invasive (thus generating a
high WRA score), there may be unknown factors or variables in Hawai‘i’s
environment that will always prevent these species from becoming pests here. For
example, Tamarix aphylla is not
thought to produce seeds in Hawai‘i. Another
interpretation is that some or many of these species with high WRA scores
(Table
3) will become invasive in the future
but are not yet recognized as pests by the expert surveys.
By far, the most economically important species on
this list are the two grasses, Paspalum
vaginatum (seashore Paspalum) and Eremochloa
ophiuroides (centipede grass). Other
species are minor forestry trees in Hawai‘i (Acacia auriculaformis,
Usually, the WRA assessments are consistent with
expert opinion (as our results have shown), but there are bound to be some cases
where “experts” disagree with a WRA assessment. In those cases, it can be enlightening to examine why as
species had a high WRA score. Let’s examine the case of Paspalum vaginatum (seashore Paspalum). Paspalum vaginatum
scored high on the WRA for several reasons. For example, it is a grass; grasses
are statistically more likely to become pests than other plant families. It has
become a serious pest of wetlands in New Zealand; it forms dense stands in
wetlands there, eliminating native species. It spreads rapidly by vegetative
reproduction. All these traits contribute to the species’ potential to become
a pest in Hawaii. Nevertheless, its
WRA score was 7, only one point above the cut-off of 6 for a rating of
“Evaluate”. Note that our WRA assessment was based on plant traits for
generic (wild) Paspalum vaginatum, and
its is possible that breeds selected for turf in Hawai‘i have specific plant
traits that will alter the answers for a number of questions on the WRA
assessment, thereby changing the score and bringing the WRA decision in line
with the expert survey results.
If the WRA score is still high, but the species is
clearly not a pest now, probably the best approach to resolve these cases is to
have a small group of objective experts with broad field experience consider the
WRA results together with their field observations, and recommend a change to
the WRA recommendation if they are reasonably confident that the species will
not be a serious pest. This same general procedure could be applied for any
species that has been “rejected” by the WRA (Table 4).
Does
the WRA “accept” too many pests?
At
the opposite end of the spectrum is the question of whether the WRA is effective
at “rejecting” most pest plants. Only 1 out of the 21 “major pests”
identified from the expert surveys was “accepted” by the WRA system:
Fraxinus
uhdei (tropical ash). For Fraxinus
uhdei, we encountered conflicting information that affected answers to some
questions in the WRA. For example, a “personal observation” found on a
webpage suggested that this tree forms dense monocultures, excluding native
species. However, an article published in a peer-reviewed scientific journal
concluded that more native plant species were found within Fraxinus
uhdei plantations than in other plantation types, suggesting that its
effect on native species was relatively low.
Similarly, an anecdotal and vague report of the species’ spreading was
found on a webpage, but a published book indicated that planted stands “reseed
themselves” but are “apparently only spreading in a few locations”.
In both, cases, the published information was favored over unconfirmed
“observations” encountered on webpages. Of course, this policy increases the
risk that very recent, accurate information will be excluded from the WRA.
As with high scoring species that do not seem to be pests, a small
committee of objective field experts could examine the WRA results while also
making use of their direct field-experience to determine if a species’ WRA
classification should be changed.
In
addition to the 1 “major pest”, the WRA “accepted” 15 species that
could be considered “minor pests” according to the expert surveys (Table
5). We are not aware of control programs specifically targeting any of these species
at this time, suggesting that these “accepted” species are not considered
high priority pests.
The
pests of native forests often have different ecological characteristics from the
pests of managed lands (e.g. agricultural fields or plantations). The
Australia/New Zealand WRA system was originally designed to identify pest plant
in both types of environment, so it is most reasonable to evaluate the
overall effectiveness of the system at identifying both pests of native forest
and pests of managed lands, as was presented in the Summary
Results. However, since some of our
expert surveyists had experience in native forests while others had experience
primarily in managed lands, it is possible to compare the WRA results with
survey results from people working in native forests (Table 2) versus people more familiar
with managed lands.
In general, the degree of agreement between the WRA decision and the
expert surveys is similar for both groups of surveyors.
An answer for each question in the WRA can potentially add or takeaway
one or more points from the total WRA score. Answers that add to the WRA score
reflect information about a species that increases the risk that it will be a
pest. It would be natural to infer that a species with a higher WRA score is a
bigger threat than one with a lower score, even if both scores fall within the
same decision region. For example, a species scoring 15 theoretically has more
potential to do greater harm than a species with a WRA score of 8, although both
would be “rejected” because their scores are > 6.
Unfortunately, we cannot make a powerful test of this idea using our data
because we did not ask our surveyists to make a quantitative assessment of the
pest status of the survey species. Instead, the survey responses were
categorical (major pest, minor pest, or not a pest).
We can convert these categories into numbers (2 = major, 1 = minor, 0 =
not a pest) and average them across surveys to obtain a pseudo-quantitative
measure of pest status for each species. However, we must use caution in
interpreting this measure. For example, if one surveyior reported that a species
is a “major pest” (score =2) and another says “not a pest” (score =0),
the average is 1 (making it “minor pest”), which might or might not be a
reasonable conclusion. In general,
converting a categorical variable into a quantitative one will also create a lot
of scatter around any predicted relationship between the two quantitative
variables. Nevertheless, when mean survey score versus WRA score was plotted, we
found significantly, positive linear regression (Figure 3).
There is a fair amount of scatter around the regression line, but on
average, a higher WRA score is predicted for species with higher expert survey
scores. This remains true when the regression is limited to smaller WRA score
intervals (e.g. 0-8 or 8-15), indicating that even within WRA classification
categories like “Reject”, higher WRA are statistically predictive of
increased pest status.
Pheloung, P. C., P. A. Williams, and S. R. Halloy. 1999. A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. Journal of Environmental Management 57:239-251.