A Parsimonious Approach to Modeling Animal Movement Data

Animal tracking is a growing field in ecology and previous work has shown that simple speed filtering of tracking data is not sufficient and that improvement of tracking location estimates are possible. To date, this has required methods that are complicated and often time-consuming (state-space models), resulting in limited application of this technique and the potential for analysis errors due to poor understanding of the fundamental framework behind the approach. We describe and test an alternative and intuitive approach consisting of bootstrapping random walks biased by forward particles. The model uses recorded data accuracy estimates, and can assimilate other sources of data such as sea-surface temperature, bathymetry and/or physical boundaries. We tested our model using ARGOS and geolocation tracks of elephant seals that also carried GPS tags in addition to PTTs, enabling true validation. Among pinnipeds, elephant seals are extreme divers that spend little time at the surface, which considerably impact the quality of both ARGOS and light-based geolocation tracks. Despite such low overall quality tracks, our model provided location estimates within 4.0, 5.5 and 12.0 km of true location 50% of the time, and within 9, 10.5 and 20.0 km 90% of the time, for above, equal or below average elephant seal ARGOS track qualities, respectively. With geolocation data, 50% of errors were less than 104.8 km (<0.94°), and 90% were less than 199.8 km (<1.80°). Larger errors were due to lack of sea-surface temperature gradients. In addition we show that our model is flexible enough to solve the obstacle avoidance problem by assimilating high resolution coastline data. This reduced the number of invalid on-land location by almost an order of magnitude. The method is intuitive, flexible and efficient, promising extensive utilization in future research

Profiling Trait Anxiety: Transcriptome Analysis Reveals Cathepsin B (Ctsb) as a Novel Candidate Gene for Emotionality in Mice

Behavioral endophenotypes are determined by a multitude of counteracting but precisely balanced molecular and physiological mechanisms. In this study, we aim to identify potential novel molecular targets that contribute to the multigenic trait “anxiety”. We used microarrays to investigate the gene expression profiles of different brain regions within the limbic system of mice which were selectively bred for either high (HAB) or low (LAB) anxiety-related behavior, and also show signs of comorbid depression-like behavior

Reviewing the use of resilience concepts in forest sciences

Purpose of the review Resilience is a key concept to deal with an uncertain future in forestry. In recent years, it has received increasing attention from both research and practice. However, a common understanding of what resilience means in a forestry context, and how to operationalise it is lacking. Here, we conducted a systematic review of the recent forest science literature on resilience in the forestry context, synthesising how resilience is defined and assessed. Recent findings Based on a detailed review of 255 studies, we analysed how the concepts of engineering resilience, ecological resilience, and social-ecological resilience are used in forest sciences. A clear majority of the studies applied the concept of engineering resilience, quantifying resilience as the recovery time after a disturbance. The two most used indicators for engineering resilience were basal area increment and vegetation cover, whereas ecological resilience studies frequently focus on vegetation cover and tree density. In contrast, important social-ecological resilience indicators used in the literature are socio-economic diversity and stock of natural resources. In the context of global change, we expected an increase in studies adopting the more holistic social-ecological resilience concept, but this was not the observed trend. Summary Our analysis points to the nestedness of these three resilience concepts, suggesting that they are complementary rather than contradictory. It also means that the variety of resilience approaches does not need to be an obstacle for operationalisation of the concept. We provide guidance for choosing the most suitable resilience concept and indicators based on the management, disturbance and application context