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2004). Likewise, the mechanisms important for biological recovery are not that
well understood, and many factors such as habitat connectivity, dispersal abilities,
food availability and species interactions may singly or in concert be important
(see below), as may the influence of other drivers such as climate change or
nutrient enrichment. In addition, detection of recovery or restoration success
may also depend on the response variable selected, such as the choice of indicator
type (chemical, biological), choice of habitat (stream, lake; pelagic, benthic)
(Wright 2002; Johnson
et al
. 2006a, b; Stendera & Johnson 2008) and choice of
metric (e.g. diversity, taxonomic composition) (Johnson & Hering 2009), as well
as many site-specific factors.
Differences in site-specific characteristics, such as latitude, altitude, catchment
characteristics, can result in lag responses that differ among sites, resulting in
high levels of uncertainty and confounding interpretation of the efficacy of
restoration. For instance, Wright (2002) postulated that lags in recovery from
acidification might increase with trophic level and vary with water-retention
times. To test the first assumption, Stendera and Johnson (2008) evaluated the
recovery rates of different biological components and habitats over 16 years in
10 boreal lakes recovering from acidification. Expectations were that chemical
recovery would be quicker than biological recovery and that biological responses
would vary among organism groups and trophic levels. Recovery times were
expected to be shorter for phytoplankton than for littoral invertebrates because
of shorter generation times and higher recolonization and dispersal rates of
phytoplankton. Littoral invertebrate assemblages were expected to respond more
quickly than sublittoral or profundal assemblages. Finally, sublittoral and
profundal assemblages, although not directly affected by surface-water chemistry,
were expected to respond more to changes in food (bottom-up) and/or predation
(top-down), resulting in relatively long lag times.
Stendera and Johnson (2008) showed that measuring biological recovery from
acidification often requires the use of holistic and multiple assessment approaches.
Several measures showed significant, positive trends over time that supported
expectations of biological recovery (Table 9.2). For instance, taxonomic diversity
of phytoplankton assemblages, but not taxonomic composition, showed early
signs of recovery related to pH increase. Significant trends were, however, also
noted for non-acidified reference lakes. Recovery trends of benthic invertebrate
assemblages were more equivocal. Littoral invertebrate taxon richness and
diversity increased in both acidified and reference lakes, whereas sublittoral and
profundal invertebrate assemblages of both lake groups showed clear negative
trends. The authors suggested that sublittoral and profundal assemblages might
be influenced by factors other than lake acidity, such as coincident changes in
habitat quality (e.g. ambient O
2
and temperature).
Interestingly, it was anticipated that communities in reference boreal lakes
would be fluctuating around a long-term mean (Fig. 9.6), but they did not,
implying the influence of some other driver. A gradual shift in baseline conditions
brought about by the effects of global warming might be one explanation for the
long-term trends noted in both the reference and acidified lakes. For example, a
shift in spring temperatures caused by warmer winters in the early years of the
study might have caused changes in the timing or duration of summer stratification.
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