Aim We characterized changes in reporting rates and abundances of bird species over a period of severe rainfall deficiency and increasing average temperatures. We also measured flowering in eucalypts, which support large numbers of nectarivores characteristic of the region.Location A 30,000‐km2 region of northern Victoria, Australia, consisting of limited amounts of remnant native woodlands embedded in largely agricultural landscapes.Methods There were three sets of monitoring studies, pitched at regional (survey programmes in 1995–97, 2004–05 and 2006–08), landscape (2002–03 and 2006–07) and site (1997–2008 continuously) scales. Bird survey techniques used a standard 2‐ha, 20‐min count method. We used Bayesian analyses of reporting rates to document statistically changes in the avifauna through time at each spatial scale.Results Bird populations in the largest remnants of native vegetation (up to 40,000 ha), some of which have been declared as national parks in the past decade, experienced similar declines to those in heavily cleared landscapes. All categories of birds (guilds based on foraging substrate, diet, nest site; relative mobility; geographical distributions) were affected similarly. We detected virtually no bird breeding in the latest survey periods. Eucalypt flowering has declined significantly over the past 12 years of drought.Main conclusions Declines in the largest woodland remnants commensurate with those in cleared landscapes suggest that reserve systems may not be relied upon to sustain species under climate change. We attribute population declines to low breeding success due to reduced food. Resilience of bird populations in this woodland system might be increased by active management to enhance habitat quality in existing vegetation and restoration of woodland in the more fertile parts of landscapes.
Aim Climate change is expected to increase the frequency and intensity of extreme climatic events, such as severe droughts and intense rainfall periods. We explored how the avifauna of a highly modified region responded to a 13year drought (the 'Big Dry'), followed by a two-year period of substantially higher than average rainfall (the 'Big Wet').Location Temperate woodlands in north central Victoria, Australia.Methods We used two spatially extensive, long-term survey programmes, each of which was repeated three times: early and late in the Big Dry, and in the Big Wet. We compared species-specific changes in reporting rates between periods in both programmes to explore the resistance (the ability to persist during drought) and resilience (extent of recovery post-drought) of species to climate extremes.
ResultsThere was a substantial decline in the reporting rates of 42-62% (depending on programme) of species between surveys conducted early and late in the Big Dry. In the Big Wet, there was some recovery, with 21-29% of species increasing substantially. However, more than half of species did not recover and 14-27% of species continued to decline in reporting rate compared with early on in the Big Dry. Species' responses were not strongly related to ecological traits. Species resistance to the drought was inversely related to resilience in the Big Wet for 20-35% of the species, while 76-78% of species with low resistance showed an overall decline across the study period.Conclusions As declines occurred largely irrespective of ecological traits, this suggests a widespread mechanism is responsible. Species that declined the most during the Big Dry did not necessarily show the greatest recoveries. In already much modified regions, climate extremes such as extended drought will induce on-going changes in the biota.
Landscape optimization for biodiversity requires prediction of species distributions under alternative revegetation scenarios. We used Bayesian model averaging with logistic regression to predict probabilities of occurrence for 61 species of birds within highly fragmented box-ironbark forests of central Victoria, Australia. We used topographic, edaphic, and climatic variables as predictors so that the models could be applied to areas where vegetation has been cleared but may be replanted. Models were evaluated with newly acquired, independent data collected in large blocks of remnant native vegetation. Successful predictions were obtained for 18 of 45 woodland species (40%). Model averaging produced more accurate predictions than "single best" models. Models were most successful for smaller-bodied species that probably depend on particular vegetation types. Predictions for larger, generalist species, and seasonal migrants were less successful, partly because of changes in species distributions between model building (1995-1997) and validation (2004-2005) surveys. We used validated models to project occurrence probabilities for individual species across a 12,000-km2 region, assuming native vegetation was present. These predictions are intended to be used as inputs, along with landscape context and temporal dynamics, into optimization algorithms to prioritize revegetation. Longer-term data sets to accommodate temporal dynamics are needed to improve the predictive accuracy of models.
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