130925-studie-wildlife-comeback-in-europe

Limitations of population trend data
It is important within a study such as this one, to recognise the limitations
of the data that are being used to draw inference on change in wildlife
status. Long-term wildlife monitoring programmes have repeatedly
demonstrated their worth, but are very few and far between. While several
good national and regional monitoring systems are becoming increasingly
widely applied, e.g. the Pan-European Common Bird Monitoring Scheme [1] ,
they are still restricted in species coverage and geographic scope.
To a large extent, bird monitoring remains more widely spread and
better focussed than the equivalent mammal, amphibian, reptile and fish
monitoring schemes. This lack of equivalence across vertebrate classes
is driven by the comparative simplicity of obtaining bird time series data
from one type of monitoring (whereas many different, often species-specific
techniques are required for other vertebrate classes) and the high level
of amateur interest and citizen science that enables broad-scale cost-effective
monitoring to be carried out. That avian data are frequently more
widely available is not a new observation [2] ; nevertheless little has been
achieved in replicating the success of bird monitoring for other groups.
There is also the possibility that population estimates may vary in
quality across a time series. This is minimised in the sampling scheme
that we use for individual population estimates (where the same methods
are used to generate population estimates over subsequent years), but
when combining multiple population estimates within a species, different
techniques may yield slightly different results.
There is also some evidence that long term schemes can undergo quality
improvements over time (e.g. people become more skilled in counting the
species that they are studying [3] ); obviously a desirable end point, though
one which can affect long-term population trajectories if not corrected for.
Finally, while both relative and absolute trends in abundance tell us
the trajectory that a population might be moving in, it does not give any
information about where that population is in relation to some pre-defined
target population size, or how a population is functioning in its
environment. Historic reference points are therefore important [4] , as well
as clear management goals on how monitoring and conservation action
need to be targeted for individuals of any given species.
References
1. European Bird Census Council (EBCC)
Pan-European Common Bird Monitoring
Scheme. Available from: http://www.
ebcc.info/pecbm.html.
2. Gregory, R.D., van Strien, A., Vorisek, P.,
et al. 2005. Developing indicators for
European birds. Philosophical Transactions
of the Royal Society of London B,
360: 269–288.
3. Kendall, W.L., Peterjohn, B.G. & Sauer, J.S.
1996. First-time observer effects in the
North American Breeding Bird Survey.
The Auk, 113 (4): 823-829.
4. Bonebrake, T.C., Christensen, J., Boggs,
B.L., et al. 2010. Population decline
assessment, historical baselines, and
conservation. Conservation Letters, 3:
371-378.
colonial nesting bird species, for which individual
colonies rather than distribution were mapped.
Species distributions were digitized in ArcGIS
9.3 (mammals) and 10 (birds) (ESRI), by georeferencing
existing maps where these were available,
producing new maps from range descriptions
where appropriate, and editing already existing
shapefiles provided by IUCN and BirdLife. A list of
all data sources used for the collation of distributional
information can be found in Appendix 1.
Population time series data for mammals
Time series trends for each species were drawn
from the Living Planet Database [2, 5] , which contains
data compiled from published scientific literature,
online databases, researchers and institutions,
and from grey literature (for full details see [2] ). The
following requirements had to be met in order for
abundance trend data to be included [2] :
• a measure or proxy measure of population
size was available for at least two years, e.g. full
population count, catch per unit effort, density
• information was available on how the data were
collected and what the units of measurement
were
• the geographic location of the population was
provided and lay within the defined European
boundaries
• the data were collected using the same method
on the same population throughout the time
series and
• the data source was referenced and traceable.
These data were used to evaluate overall trends in
abundance for each species. In addition, national
level estimates of current total abundance were
collated for each species.
In order to understand the nature and reasons
for abundance change, ancillary information
was collated at the population level relating
to geographic, ecological and conservation
management themes. Habitat type was coded
following the WWF biome and ecoregion classification
[6] . Countries were combined into regions
following the United Nations Statistics Division [7]
(Appendix 2). Records with missing information
on management intervention, threats and utilised
status were recoded as ‘unknown’. For threats, we
additionally combined threat levels by assigning
each record to threatened, non-threatened or
unknown categories.
Because range-wide monitoring of abundance
is comparatively rare for widespread species [8]
such as some of those presented in this study, we
tried to obtain a measure of the representativeness
of our mammal abundance data set. For this, we
calculated two different measures of coverage:
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