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Measuring habitat quality for waterbirds: a review

Quantifying habitat quality is dependent on measuring a site’s relative
contribution to population growth rate. This is challenging for studies
of waterbirds, whose high mobility can decouple demographic rates from
local habitat conditions and make sustained monitoring of individuals
near-impossible. To overcome these challenges, biologists have used many
direct and indirect proxies of waterbird habitat quality. However,
consensus on what methods are most appropriate for a given scenario is
lacking. We undertook a structured literature review of the methods used
to quantify waterbird habitat quality, and provide a synthesis of the
context-dependent strengths and limitations of those methods. Our
structured search of the Web of Science database returned a sample of
398 studies, upon which our review was based. The reviewed studies
assessed habitat quality by either measuring habitat attributes (e.g.,
food abundance, water quality, vegetation structure), or measuring
attributes of the waterbirds themselves (e.g., demographic parameters,
body condition, behaviour, distribution). Measuring habitat attributes,
although they are only indirectly related to demographic rates, has the
advantage of being unaffected by waterbird behavioural stochasticity.
Conversely, waterbird-derived measures (e.g., body condition, peck
rates) may be more directly related to demographic rates than habitat
variables, but may be subject to greater stochastic variation (e.g.,
behavioural change due to presence of conspecifics). Therefore, caution
is needed to ensure that the measured variable does influence waterbird
demographic rates. This assumption was usually based on ecological
theory rather than empirical evidence. Our review highlighted that there
is no single best, universally applicable method to quantify waterbird
habitat quality. Individual project specifics (e.g., time frame, spatial
scale, funding) will influence the choice of variables measured. Where
possible, practitioners should measure variables most directly related
to demographic rates. Generally, measuring multiple variables yields a
better chance of accurately capturing the relationship between habitat
characteristics and demographic rates.