Intra-specific variation in wing morphology and its impact on take-off performance in blue tits (Cyanistes caeruleus) during escape flights

Diurnal and seasonal increases in body mass and seasonal reductions in wing area may compromise a bird's ability to escape, as less of the power available from the flight muscles can be used to accelerate and elevate the animal's centre of mass. Here, we investigated the effects of intra-specific variation in wing morphology on escape take-off performance in blue tits (Cyanistes caeruleus). Flights were recorded using synchronised high-speed video cameras and take-off performance was quantified as the sum of the rates of change of the kinetic and potential energies of the centre of mass. Individuals with a lower wing loading, WL (WL=body weight/wing area) had higher escape take-off performance, consistent with the increase in lift production expected from relatively larger wings. Unexpectedly, it was found that the total power available from the flight muscles (estimated using an aerodynamic analysis) was inversely related to WL. This could simply be because birds with a higher WL have relatively smaller flight muscles. Alternatively or additionally, variation in the aerodynamic load on the wing resulting from differences in wing morphology will affect the mechanical performance of the flight muscles via effects on the muscle's length trajectory. Consistent with this hypothesis is the observation that wing beat frequency and relative downstroke duration increase with decreasing WL; both are factors that are expected to increase muscle power output. Understanding how wing morphology influences take-off performance gives insight into the potential risks associated with feather loss and seasonal and diurnal fluctuations in body mass

Landscape scale habitat suitability modelling of bats in the Western Ghats of India: Bats like something in their tea

To conserve biodiversity it is imperative that we understand how different species respond to land use change, and determine the scales at which habitat changes affect species' persistence. We used habitat suitability models (HSMs) at spatial scales from 100-4000. m to address these concerns for bats in the Western Ghats of India, a biodiversity hotspot of global importance where the habitat requirements of bats are poorly understood. We used acoustic and capture data to build fine scale HSMs for ten species (Hesperoptenus tickelli, Miniopterus fuliginosus, Miniopterus pusillus, Myotis horsfieldii, Pipistrellus ceylonicus, Megaderma spasma, Hipposideros pomona, Rhinolophus beddomei, Rhinolophus indorouxii and Rhinolophus lepidus) in a tea-dominated landscape. Small (100-500. m) scale habitat variables (e.g. percentage tea plantation cover) and distances to habitat features (e.g. distance to water) were the strongest predictors of bat occurrence, likely due to their high mobility, which enables them to exploit even small or isolated foraging areas. Most species showed a positive response to coffee plantations grown under native shade and to forest fragments, but a negative response to more heavily modified tea plantations. Two species were never recorded in tea plantations. This is the first study of bats in tea plantations globally, and the first ecological Old World bat study to combine acoustic and capture data. Our results suggest that although bats respond negatively to tea plantations, tea-dominated landscapes that also contain forest fragments and shade coffee can nevertheless support many bat species

Sex biases in bird and mammal natural history collections.

Natural history specimens are widely used across ecology, evolutionary biology and conservation. Although biological sex may influence all of these areas, it is often overlooked in large-scale studies using museum specimens. If collections are biased towards one sex, studies may not be representative of the species. Here, we investigate sex ratios in over two million bird and mammal specimen records from five large international museums. We found a slight bias towards males in birds (40% females) and mammals (48% females), but this varied among orders. The proportion of female specimens has not significantly changed in 130 years, but has decreased in species with showy male traits like colourful plumage and horns. Body size had little effect. Male bias was strongest in name-bearing types; only 27% of bird and 39% of mammal types were female. These results imply that previous studies may be impacted by undetected male bias, and vigilance is required when using specimen data, collecting new specimens and designating types.Copyright and usage: © 2019 The Author(s) Published by the Royal Society. All rights reserved The attached file is the final approved manuscript (Author Generated Postprint), you are advised to consult the publisher’s version if you wish to cite from it

Variable ranking and selection with random forest for unbalanced data

When one or several classes are much less prevalent than another class (unbalanced data), class error rates and variable importances of the machine learning algorithm random forest can be biased, particularly when sample sizes are smaller, imbalance levels higher, and effect sizes of important variables smaller. Using simulated data varying in size, imbalance level, number of true variables, their effect sizes, and the strength of multicollinearity between covariates, we evaluated how eight versions of random forest ranked and selected true variables out of a large number of covariates despite class imbalance. The version that calculated variable importance based on the area under the curve (AUC) was least adversely affected by class imbalance. For the same number of true variables, effect sizes, and multicollinearity between covariates, the AUC variable importance ranked true variables still highly at the lower sample sizes and higher imbalance levels at which the other seven versions no longer achieved high ranks for true variables. Conversely, using the Hellinger distance to split trees or downsampling the majority class already ranked true variables lower and more variably at the larger sample sizes and lower imbalance levels at which the other algorithms still ranked true variables highly. In variable selection, a higher proportion of true variables were identified when covariates were ranked by AUC importances and the proportion increased further when the AUC was used as the criterion in forward variable selection. In three case studies, known species–habitat relationships and their spatial scales were identified despite unbalanced data

Do Bat Gantries and Underpasses Help Bats Cross Roads Safely?

Major roads can reduce bat abundance and diversity over considerable distances. To mitigate against these effects and comply with environmental law, many European countries install bridges, gantries or underpasses to make roads permeable and safer to cross. However, through lack of appropriate monitoring, there is little evidence to support their effectiveness. Three underpasses and four bat gantries were investigated in northern England. Echolocation call recordings and observations were used to determine the number of bats using underpasses in preference to crossing the road above, and the height at which bats crossed. At gantries, proximity to the gantry and height of crossing bats were measured. Data were compared to those from adjacent, severed commuting routes that had no crossing structure. At one underpass 96% of bats flew through it in preference to crossing the road. This underpass was located on a pre-construction commuting route that allowed bats to pass without changing flight height or direction. At two underpasses attempts to divert bats from their original commuting routes were unsuccessful and bats crossed the road at the height of passing vehicles. Underpasses have the potential to allow bats to cross roads safely if built on pre-construction commuting routes. Bat gantries were ineffective and used by a very small proportion of bats, even up to nine years after construction. Most bats near gantries crossed roads along severed, pre-construction commuting routes at heights that put them in the path of vehicles. Crossing height was strongly correlated with verge height, suggesting that elevated verges may have some value in mitigation, but increased flight height may be at the cost of reduced permeability. Green bridges should be explored as an alternative form of mitigation. Robust monitoring is essential to assess objectively the case for mitigation and to ensure effective mitigation