Datasets used by quantitative ecologists are getting more and more complex. So we need more complex models, such as hierarchical and complex spatial models. Typically, Bayesian approaches such as Markov chain Monte Carlo have been used. But these methods can be slow, making it infeasible to fit some models.
Statistical and quantitative methods within ecology have increased substantially in recent years. This rise can be attributed both to the growing need to address global environmental change issues, as well as the increase in data sources to address these challenges. Continue reading →
Working on FLightR, the package for analysis of data obtained from solar geolocation tracking devices, we were haunted by the unpleasant feeling of investing in technology which will soon be out of date. Until now solar geolocators have been popular in ornithological studies. This is because they’re small, light-weight (< 1/3 g) tracking devices that can be deployed even on miniature birds, such as swallows and warblers. They’ve also been the longest-lasting data loggers, with the most storage space and, of course, the most affordable ones.
Are Solar Geolocators Finished?
There are apparent drawbacks of using this technique though. To begin with, solar geolocation simply does not work for some species. You can’t use it to study birds living in dense tropical forests or in cavities, because of the light-pattern bias. For the same reason, it doesn’t provide fantastic results in light-polluted areas. Data from geolocators cannot be retrieved remotely, and this is why you need to have high recapture rates for the species you’re studying. Continue reading →
Today, we’re pleased to announce that we’re launching a new article type for Methods in Ecology and Evolution: Practical Tools. Like our Applications articles, Practical Tools will be short papers(up to 3000 words). They’ll focus on new field techniques, equipment or lab protocols. From this point forward, our Applications papers will solely focus on software and code.
Practical tools need to clearly demonstrate how tools designed for specific systems or problems can be adapted for more general use. Online supporting information can include specific instructions, especially for building equipment. You can find some examples of Applications that would now fit into this article type here and here.
The standard approach to quantifying natural selection, developed by Lande and Arnold, does not allow for comparable metrics between linear (i.e. selection on the mean phenotype) and nonlinear (i.e. selection on all other aspects of the phenotypic distribution, including variance and the number of modes) selection gradients. Jonathan Henshaw’s winning submission provides the first integrated measure of the strength of selection that applies across qualitatively different selection regimes (e.g. directional, stabilizing or disruptive selection). Continue reading →
In January 2018, Methods in Ecology and Evolution launched a Policy on Publishing Code. The main objective of this policy is to make sure that high quality code is readily available to our readers. set out four key principles to help achieve this, as well as explaining what code outputs we publish, giving some examples of things that make it easier to review code, and giving some advice on how to store code once it’s been published.
The BES Microbial Ecology Special Interest Group is running a workshop today (Thursday 2 November) on Novel Tools for Microbial Ecology. To compliment this workshop, Xavier Harrison has edited a Virtual Issue of the best Methods in Ecology and Evolution articles on advances in methods of studying microbial evolution and ecology from the past few years.
Advances in Next-Generation Sequencing (NGS) technology now allow us to study associations between hosts and their microbial communities in unprecedented detail. However, studies investigating host-microbe interactions in the field of ecology and evolution are dominated by 16S and ITS amplicon sequencing. While amplicon sequencing is a useful tool for describing microbial community composition, it is limited in its ability to quantify the function(s) performed by members of those communities. Characterising function is vital to understanding how microbes and their hosts interact, and consequently whether those interactions are adaptive for, or detrimental to, the host. The articles in this Virtual Issue cover a broad suite of approaches that allow us to study host-microbe and microbe-microbe interactions in novel ways.
Evolutionary quantitative genetics provides formal theoretical frameworks for quantitatively linking natural selection, genetic variation, and the rate and direction of adaptive evolution. This strong theoretical foundation has been key to guiding empirical work for a long time. For example, rather than generally understanding selection to be merely an association of traits and fitness in some general way, theory tells us that specific quantities, such as the change in mean phenotype within generations (the selection differential; Lush 1937), or the partial regressions of relative fitness on traits (direct selection gradients; Lande 1979, Lande and Arnold 1983) will relate to genetic variation and evolution in specific, informative ways.
These specific examples highlight the importance of the theoretical foundation of evolutionary quantitative genetics for informing the study of natural selection. However, this foundation also supports the study other critical (quantification of genetic variation and evolution) and complimentary (e.g., interpretation when environments, change, the role of plasticity and genetic variation in plasticity) aspectsof understanding the nuts and bolts of evolutionary change.Continue reading →
‘Just Google it’ marks an important step in converting ecology to an armchair science. Many species (e.g. owls, hawks, bears) are difficult, time-consuming, expensive and even dangerous to observe. It would be a lot easier if we didn’t have to spend time, energy and risk lives having to observe organisms in the field! Continue reading →
It’s not easy to characterise the local environment of species living in mountains because these habitats are highly heterogeneous. At a large scale, we typically assume that temperature varies with altitude, but at a local scale, we understand that exposure to wind or being in the shade has a great influence on climatic conditions. If you go from the south-facing to the north-facing side of a mountain, it can be easily 5°C colder. If we can feel that, so can the organisms that live up there. Plants in particular are submitted to tremendous climatic variations over a year. What we want to know is: how did they adapt to these climatic variations and how localised is their adaptation?
Overcoming the Challenges of Measuring Local Adaptation
We don’t know much about how organisms adapt locally because it’s so difficult to measure the environmental conditions that these plants are facing. Existing weather stations can’t capture micro-habitat conditions because they are few and far between. What we can do instead, is use topographic models of mountains to model their environment. After all, if orientation, slope or shade have an impact on climatic conditions, why couldn’t we use them to model local variations in temperature for example? Continue reading →