Kin recognition and adjustment of reproductive effort in zebra finches

The differential allocation theory predicts that females should invest more in offspring produced with attractive partners, and a number of studies support this prediction in birds. Females have been shown to increase reproductive investment when mated to males showing elaborated sexual traits. However, mate attractiveness might also depend on the interaction between male and female genotypes. Accordingly, females should invest more in offspring sired by individuals that are genetically dissimilar or carry superior alleles. Here, we show in zebra finches (Taeniopygia guttata) that pairs of unfamiliar genetic brothers and sisters are less likely to reproduce in comparison with randomly mated pairs. Among the brother–sister pairs, those that attempted to breed laid smaller clutches and of lower total clutch mass. Our results provide the first experimental evidence that females adjust their reproductive effort in response to the genetic similarity of their partners. Importantly, these results imply a female ability to assess relatedness of a social mate without prior association.     

Data-Mining Discovery of Pattern and Process in Ecological Systems

ABSTRACT Most ecologists use statistical methods as their main analytical tools when analyzing data to identify relationships between a response and a set of predictors; thus, they treat all analyses as hypothesis tests or exercises in parameter estimation. However, little or no prior knowledge about a system can lead to creation of a statistical model or models that do not accurately describe major sources of variation in the response variable. We suggest that under such circumstances data mining is more appropriate for analysis. In this paper we 1) present the distinctions between data-mining (usually exploratory) analyses and parametric statistical (confirmatory) analyses, 2) illustrate 3 strengths of data-mining tools for generating hypotheses from data, and 3) suggest useful ways in which data mining and statistical analyses can be integrated into a thorough analysis of data to facilitate rapid creation of accurate models and to guide further research.     

Environmental decision support systems: A new approach to support the operation and maintenance of horizontal subsurface flow constructed wetlands

This paper describes the development and operation of an Environmental Decision Support System (EDSS) to improve the operation and maintenance of horizontal subsurface-flow constructed wetlands (EDSS-maintenance). Constructed wetlands (CWs) allow wastewater treatment in a sustainable manner since they involve low energy consumption, low construction and functioning costs and low environmental impact. However, operation and maintenance activities are essential to guarantee reliability in CWs performance. The definition of operation and maintenance protocols depends on several quantitative and qualitative aspects such as wastewater treatment plant configuration, CW design, influent characteristics, sensitivity of the receiving media, etc. Bearing this in mind and considering the limited technical knowledge about CWs, the need for a new tool to support CW performance is clear. In this sense, EDSSs offer a new approach because they can tackle problems of complex and uncertain systems. The EDSS-maintenance provides operation and maintenance manuals specifically defined for every CW. To achieve it, the required knowledge was implemented within a rule-based system, which forms the backbone of the EDSS. Several features presented in this paper demonstrate how the EDSS-maintenance provides a proper platform to support the necessary collaborative work in the ecological engineering problem of horizontal subsurface flow CWs operation and maintenance.     

Honeybees Use Celestial and/or Terrestrial Compass Cues for Inter‐Patch Navigation

Foraging honeybees (Apis mellifera) are well known to fly straight from the hive, their primary hub, to distal goals as well as between familiar feeding sites. More recently, it was shown that a distal feeding site may be used as a secondary hub. If not fully satiated, the foraging bee may decide to depart the first feeding site in a new compass direction straight to one of many other feeding sites (inter‐patch foraging). Using a recently developed recording method, we discovered that the chosen departure direction at a secondary hub can be guided exclusively by either celestial or terrestrial compass cues. Given our data, we draw two theoretical inferences. First, the bees must be capable of learning and remembering multiple, spatially distinct, navigation vectors between the hive and among multiple feeding sites. Second, this documented and useful representation of multiple navigation vectors between multiple, identified target locations logically implies composite place‐vector mapping, stored in long‐term memory.     

A generalist brood parasite modifies use of a host in response to reproductive success

Avian obligate brood parasites, which rely solely on hosts to raise their young, should choose the highest quality hosts to maximize reproductive output. Brown-headed cowbirds (Molothrus ater) are extreme host generalists, yet female cowbirds could use information based on past reproductive outcomes to make egg-laying decisions thus minimizing fitness costs associated with parasitizing low-quality hosts. We use a long-term (21 years) nest-box study of a single host, the prothonotary warbler (Protonotaria citrea), to show that local cowbird reproductive success, but not host reproductive success, was positively correlated with the probability of parasitism the following year. Experimental manipulations of cowbird success corroborated that female cowbirds make future decisions about which hosts to use based on information pertaining to past cowbird success, both within and between years. The within-year pattern, in particular, points to local cowbird females selecting hosts based on past reproductive outcomes. This, coupled with high site fidelity of female cowbirds between years, points to information use, rather than cowbird natal returns alone, increasing parasitism rates on highly productive sites between years.     

Priority threat management of invasive animals to protect biodiversity under climate change

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one‐sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost‐effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost‐effectiveness was relatively unaffected by including climate change into decision‐making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.