Territory quality and plumage morph predict offspring sex ratio variation in a raptor

Parents may adapt their offspring sex ratio in response to their own phenotype and environmental conditions. The most significant causes for adaptive sex-ratio variation might express themselves as different distributions of fitness components between sexes along a given variable. Several causes for differential sex allocation in raptors with reversed sexual size dimorphism have been suggested. We search for correlates of fledgling sex in an extensive dataset on common buzzards Buteo buteo, a long-lived bird of prey. Larger female offspring could be more resource-demanding and starvation-prone and thus the costly sex. Prominent factors such as brood size and laying date did not predict nestling sex. Nonetheless, lifetime sex ratio (LSR, potentially indicative of individual sex allocation constraints) and overall nestling sex were explained by territory quality with more females being produced in better territories. Additionally, parental plumage morphs and the interaction of morph and prey abundance tended to explain LSR and nestling sex, indicating local adaptation of sex allocation However, in a limited census of nestling mortality, not females but males tended to die more frequently in prey-rich years. Also, although females could have potentially longer reproductive careers, a subset of our data encompassing full individual life histories showed that longevity and lifetime reproductive success were similarly distributed between the sexes. Thus, a basis for adaptive sex allocation in this population remains elusive. Overall, in common buzzards most major determinants of reproductive success appeared to have no effect on sex ratio but sex allocation may be adapted to local conditions in morph-specific patterns

Framework for assessing and mitigating the impacts of offshore wind energy development on marine birds

Offshore wind energy development (OWED) is rapidly expanding globally and has the potential to contribute significantly to renewable energy portfolios. However, development of infrastructure in the marine environment presents risks to wildlife. Marine birds in particular have life history traits that amplify population impacts from displacement and collision with offshore wind infrastructure. Here, we present a broadly applicable framework to assess and mitigate the impacts of OWED on marine birds. We outline existing techniques to quantify impact via monitoring and modeling (e.g., collision risk models, population viability analysis), and present a robust mitigation framework to avoid, minimize, or compensate for OWED impacts. Our framework addresses impacts within the context of multiple stressors across multiple wind energy developments. We also present technological and methodological approaches that can improve impact estimation and mitigation. We highlight compensatory mitigation as a tool that can be incorporated into regulatory frameworks to mitigate impacts that cannot be avoided or minimized via siting decisions or alterations to OWED infrastructure or operation. Our framework is intended as a globally-relevant approach for assessing and mitigating OWED impacts on marine birds that may be adapted to existing regulatory frameworks in regions with existing or planned OWED

A large-scale, multispecies assessment of avian mortality rates at land-based wind turbines in northern Germany

Grünkorn T, Blew J, Krüger O, et al. A large-scale, multispecies assessment of avian mortality rates at land-based wind turbines in northern Germany. In: Köppel J, ed. Wind energy and wildlife interactions. Berlin: Springer; 2017: 43-64

Initial (A) and best (B) models of nestlings sex in the dataset including all sampled common buzzard nestlings (n = 1678).

<p>ANOVA between initial and best model of nestling sex χ² = 21.548, df = 21, P = 0.426, ΔAIC = 19.6.</p

Generalized linear models of lifetime reproductive success, LRS (A), reproductive lifespan, longevity (B) and nestling mortality (C).

<p>Generalized linear models of lifetime reproductive success, LRS (A), reproductive lifespan, longevity (B) and nestling mortality (C).</p

Lifetime sex ratio (+SE) of (a) mothers and (b) fathers of different melanin morphs with entirely known reproductive output.

<p>Sample sizes are number of individuals of the respective class with completely known lifetime sex ratio.</p

Datasets for analysis of nestlings sex, lifetime sex ratio of females and males, lifetime reproductive success, reproductive lifespan (longevity) and mortality of nestlings.

<p>Datasets for analysis of nestlings sex, lifetime sex ratio of females and males, lifetime reproductive success, reproductive lifespan (longevity) and mortality of nestlings.</p

Initial (A) and best (B) models of lifetime sex ratio of male common buzzards with completely known life histories (n = 94).

<p>ANOVA between initial and best model of female lifetime sex ratio χ² = 0.943, df = 2, P = 0.624, ΔAIC = 3.1.</p

Sex ratio of nestling buzzards hatched (a) in poor, intermediate and good territories based on their proportional occupancy and (b) in years with low, intermediate and high vole abundance to dark intermediate and light mothers.

<p>Binning into three territory quality classes is for visual purposes only. Statistical analyses were performed with the continuous variable territory quality.</p