The effect of climate change on avian offspring production: A global meta-analysis.

Climate change affects timing of reproduction in many bird species, but few studies have investigated its influence on annual reproductive output. Here, we assess changes in the annual production of young by female breeders in 201 populations of 104 bird species (N = 745,962 clutches) covering all continents between 1970 and 2019. Overall, average offspring production has declined in recent decades, but considerable differences were found among species and populations. A total of 56.7% of populations showed a declining trend in offspring production (significant in 17.4%), whereas 43.3% exhibited an increase (significant in 10.4%). The results show that climatic changes affect offspring production through compounded effects on ecological and life history traits of species. Migratory and larger-bodied species experienced reduced offspring production with increasing temperatures during the chick-rearing period, whereas smaller-bodied, sedentary species tended to produce more offspring. Likewise, multi-brooded species showed increased breeding success with increasing temperatures, whereas rising temperatures were unrelated to reproductive success in single-brooded species. Our study suggests that rapid declines in size of bird populations reported by many studies from different parts of the world are driven only to a small degree by changes in the production of young.

Circumpolar analysis of the Adélie Penguin reveals the importance of environmental variability in phenological mismatch.

Evidence of climate-change-driven shifts in plant and animal phenology have raised concerns that certain trophic interactions may be increasingly mismatched in time, resulting in declines in reproductive success. Given the constraints imposed by extreme seasonality at high latitudes and the rapid shifts in phenology seen in the Arctic, we would also expect Antarctic species to be highly vulnerable to climate-change-driven phenological mismatches with their environment. However, few studies have assessed the impacts of phenological change in Antarctica. Using the largest database of phytoplankton phenology, sea-ice phenology, and Adélie Penguin breeding phenology and breeding success assembled to date, we find that, while a temporal match between Penguin breeding phenology and optimal environmental conditions sets an upper limit on breeding success, only a weak relationship to the mean exists. Despite previous work suggesting that divergent trends in Adélie Penguin breeding phenology are apparent across the Antarctic continent, we find no such trends. Furthermore, we find no trend in the magnitude of phenological mismatch, suggesting that mismatch is driven by interannual variability in environmental conditions rather than climate-change-driven trends, as observed in other systems. We propose several criteria necessary for a species to experience a strong climate-change-driven phenological mismatch, of which several may be violated by this system.

The influence of historical climate changes on Southern Ocean marine predator populations: a comparative analysis.

The Southern Ocean ecosystem is undergoing rapid physical and biological changes that are likely to have profound implications for higher-order predators. Here, we compare the long-term, historical responses of Southern Ocean predators to climate change. We examine palaeoecological evidence for changes in the abundance and distribution of seabirds and marine mammals, and place these into context with palaeoclimate records in order to identify key environmental drivers associated with population changes. Our synthesis revealed two key factors underlying Southern Ocean predator population changes; (i) the availability of ice-free ground for breeding and (ii) access to productive foraging grounds. The processes of glaciation and sea ice fluctuation were key; the distributions and abundances of elephant seals, snow petrels, gentoo, chinstrap and Adélie penguins all responded strongly to the emergence of new breeding habitat coincident with deglaciation and reductions in sea ice. Access to productive foraging grounds was another limiting factor, with snow petrels, king and emperor penguins all affected by reduced prey availability in the past. Several species were isolated in glacial refugia and there is evidence that refuge populations were supported by polynyas. While the underlying drivers of population change were similar across most Southern Ocean predators, the individual responses of species to environmental change varied because of species specific factors such as dispersal ability and environmental sensitivity. Such interspecific differences are likely to affect the future climate change responses of Southern Ocean marine predators and should be considered in conservation plans. Comparative palaeoecological studies are a valuable source of long-term data on species' responses to environmental change that can provide important insights into future climate change responses. This synthesis highlights the importance of protecting productive foraging grounds proximate to breeding locations, as well as the potential role of polynyas as future Southern Ocean refugia.

Changes in seed dispersal processes and the potential for between-patch connectivity for an arid land daisy.

Dispersal is a major and critical process in population biology that has been particularly challenging to study. Animals can have major roles in seed dispersal even in species that do not appear specifically adapted to animal-aided dispersal. This can occur by two processes: direct movement of diaspores by animals and modification of landscape characteristics by animals in ways that greatly influence dispersal. We exploited the production of large, persistent dispersal structures (seed heads, henceforth) by Erodiophyllum elderi (Asteraceae), a daisy from arid Australia, to further understand secondary dispersal. Seed head dispersal on and off animal tracks in eight E. elderi patches was monitored for 9.5 months by periodically recording the location of marked seed heads. Sites were located inside a reserve that excludes sheep but not kangaroos, and in a nearby area with both kangaroos and sheep. The distance moved and likelihood of seed head movement was higher in areas with sheep, and especially along animal tracks. There was clear evidence that seed heads were channeled down animal tracks during large rainfall events. Seed head dispersal away from patches occurred to a limited extent via their physical contact with sheep and potentially via wind dispersal. Thus, the advantages of this study system allowed us to demonstrate the two postulated effects of herbivores on dispersal via direct movement of seed heads, and two distinct indirect effects through landscape modification by herbivores from the creation of animal tracks and the denudation of vegetation.

Author Correction: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project.

Automated time-lapse cameras can facilitate reliable and consistent monitoring of wild animal populations. In this report, data from 73,802 images taken by 15 different Penguin Watch cameras are presented, capturing the dynamics of penguin (Spheniscidae; Pygoscelis spp.) breeding colonies across the Antarctic Peninsula, South Shetland Islands and South Georgia (03/2012 to 01/2014). Citizen science provides a means by which large and otherwise intractable photographic data sets can be processed, and here we describe the methodology associated with the Zooniverse project Penguin Watch, and provide validation of the method. We present anonymised volunteer classifications for the 73,802 images, alongside the associated metadata (including date/time and temperature information). In addition to the benefits for ecological monitoring, such as easy detection of animal attendance patterns, this type of annotated time-lapse imagery can be employed as a training tool for machine learning algorithms to automate data extraction, and we encourage the use of this data set for computer vision development.