This post is an outcome of the ‘Maximising the Exposure of Your Research’ Workshop at the BES 2015 Annual Meeting in Edinburgh (UK). If you’re interested in joining us for our 2016 Annual Meeting in Liverpool (UK), you can find some more information and pre-register HERE.
In recent years there has been a significant increase in the number of academic articles published. At the same time, readers are changing how they find content, tending towards a point of entry at article level as opposed to journal level. These two factors mean that it is increasingly necessary for authors to make their articles easy for relevant readers to find. Search Engine Optimisation (SEO) is one of the best ways to do this.
Our final issue of 2015 contains one Applications article and two Open Access articles, all of which are freely available.
– stagePOP: A tool for predicting the deterministic dynamics and interactions of stage-structured populations (i.e. where the life cycle consists of distinct stages, for example eggs, juveniles and reproductive adults). The continuous-time formulation enables stagePop to easily simulate time-varying stage durations, overlapping generations and density-dependent vital rates.
Julia Cherry et al. provide one of this month’s Open Access articles. In ‘Testing sea-level rise impacts in tidal wetlands: a novel in situ approach‘ the authors describe the use of experimental weirs that manipulate water levels to test sea-level rise impacts in situ and at larger spatial scales. This new method can provide more robust estimates of sea-level rise impacts on tidal wetland processes. This article was accompanied by a press release when it was published in Early View. You can read more about this article here.
Biodiversity Indicators are some of the most important tools linking ecological data with government policy. Indicators need to summarise large amounts of information in a format that is accessible to politicians and the general public. The primary use of indicators is to monitor progress towards environmental targets. For the UK, a suite of indicators are produced annually which are used to monitor progress towards the Aichi targets of the Convention on Biological Diversity as well as for European Union based commitments. However, this is complicated by the fact that biodiversity policy within the UK is devolved to each of the four nations, so additional indicators have been developed to monitor the commitments of each country.
A range of biodiversity indicators exist within this suite covering the five strategic goals of the Convention; which include addressing the causes of biodiversity loss, reducing pressures on biodiversity and improving status of biodiversity within the UK. Within strategic goal C (improve status of biodiversity by safeguarding ecosystems, species and genetic diversity) there are currently 11 “State” indicators that use species data to monitor progress towards the targets underlying this goal. Most existing species based indicators use abundance data from large scale monitoring schemes with systematic protocols. However, there are other sources of data, such as occurrence records, that can offer an alternative if they are analysed using the appropriate methods. This post will discuss the development of species indicators for occurrence records to complement the current UK species based indicators, specifically relating to the C4b priority species indicator and the D1c pollinators indicator. Continue reading “Building a Better Indicator”
Today, we are pleased to be welcoming a new member of the Methods in Ecology and Evolution Associate Editor Board. Anne Chao joins us from the National Tsing Hua University in Taiwan and you can find out a little more about her below.
Anne Chao
Anne Chao
“I am 60% statistician, 30% mathematician and 10% ecologist. Mathematical and statistical problems in ecology and evolution fascinate me. My current research interests include statistical inferences of biodiversity measures (for example taxonomic, phylogenetic, and functional diversities along with related similarity/differentiation indices), and statistical analysis of ecological and environmental survey data (such as standardising biological samples and rarefaction/extrapolation techniques).”
If you’re anything like me, you might experience a minor existential crisis weekly. As scientists we question the world around us and, for me, this questioning turns all-too-often inwards to my career. I don’t think that’s unusual: ask any scientist about their ‘Plan B’, and the extent to which it’s thought through is often astonishing (if a café-cum-cocktail bar ever opens in Glasgow’s West End, which specialises in drinks that employ spice blends from around the world and are named after old spice trade routes and trading vessels, then you know I’ve jumped the science ship).
Contributing open-source software is something which has made my work feel a bit more relevant and helped me feel a bit less of an imposter. I’ll explain why that is, give some tips to beginners for building a first R package, and hopefully persuade other (especially early-career) researchers to do the same. Continue reading “A Quickstart Guide for Building Your First R Package”
Last month we published a blog post with some tips on selecting preferred reviewers for your manuscript. It was hugely popular (if you haven’t read it yet you can do so here), so we have decided to follow it up with some advice on identifying NON-preferred reviewers (or Author Opposed Reviewers as they are now known on ScholarOne).
Unlike preferred reviewers, you are not required to identify non-preferred reviewers when you submit your paper to Methods. However, in certain cases this option is can be very useful for your manuscript. It is important not to overuse or misuse this feature of the submission system though and the below tips will help you to avoid doing this.
The Golden Rule: Always Explain Why!
It can often be difficult to decide whether to identify someone as an author opposed reviewer. While there are some guidelines that journals can (and do) offer, a lot of the time authors find themselves in the grey area between these. We understand that it is unlikely that every question you have will be answered by our guidance (although we hope that we can address at least a few of them), but there is a way around this: explain why you have made a person a non-preferred reviewer. Continue reading “When to Identify Non-Preferred Reviewers”
Last week the Center for Open Science held a meeting with the aim of improving inference in ecology and evolution. The organisers (Tim Parker, Jessica Gurevitch & Shinichi Nakagawa) brought together the Editors-in-chief of many journals to try to build a consensus on how improvements could be made. I was brought in due to my interest in statistics and type I errors – be warned, my summary of the meeting is unlikely to be 100% objective.
True Positives and False Positives
The majority of findings in psychology and cancer biology cannot be replicated in repeat experiments. As evolutionary ecologists we might be tempted to dismiss this because psychology is often seen as a “soft science” that lacks rigour and cancer biologists are competitive and unscrupulous. Luckily, we as evolutionary biologists and ecologists have that perfect blend of intellect and integrity. This argument is wrong for an obvious reason and a not so obvious reason.
We tend to concentrate on significant findings, and with good reason: a true positive is usually more informative than a true negative. However, of all the published positives what fraction are true positives rather than false positives? The knee-jerk response to this question is 95%. However, the probability of a false positive (the significance threshold, alpha) is usually set to 0.05, and the probability of a true positive (the power, beta) in ecological studies is generally less than 0.5 for moderate sized effects. The probability that a published positive is true is therefore 0.5/(0.5+0.05) =91%. Not so bad. But, this assumes that the hypotheses and the null hypothesis are equally likely. If that were true, rejecting the null would give us very little information about the world (a single bit actually) and is unlikely to be published in a widely read journal. A hypothesis that had a plausibility of 1 in 25 prior to testing would, if true, be more informative, but then the true positive rate would be down to (1/25)*0.5/((1/25)*0.5+(24/25)*0.05) =29%. So we can see that high false positive rates aren’t always the result of sloppiness or misplaced ambition, but an inevitable consequence of doing interesting science with a rather lenient significance threshold. Continue reading “There’s Madness in our Methods: Improving inference in ecology and evolution”
Isotopes are atoms that have the same number of protons and electrons but differ in their number of neutrons; they are lighter and heavier forms of the same element. Unlike radioactive isotopes, stable isotopes do not decay over time.
This month’s issue contains two Applications articles and one Open Access article, all of which are freely available.
– mvMORPH: A package of multivariate phylogenetic comparative methods for the R statistical environment which allows fitting a range of multivariate evolutionary models under a maximum-likelihood criterion. Its use can be extended to any biological data set with one or multiple covarying continuous traits.
– Low-cost soil CO2 efflux and point concentration sensing systems: The authors use commercially available, low-cost and low-power non-dispersive infrared (NDIR) CO2 sensors to develop a soil CO2 efflux system and a point CO2 concentration system. Their methods enable terrestrial ecologists to substantially improve the characterization of CO2 fluxes and concentrations in heterogeneous environments.
This month’s Open Access article comes from Jolyon Troscianko and Martin Stevens. In ‘Image calibration and analysis toolbox – a free software suite for objectively measuring reflectance, colour and pattern‘ they introduce a toolbox that can convert images to correspond to the visual system (cone-catch values) of a wide range of animals, enabling human and non-human visual systems to be modelled. The toolbox is freely available as an addition to the open source ImageJ software and will considerably enhance the appropriate use of digital cameras across multiple areas of biology. In particular, researchers aiming to quantify animal and plant visual signals will find this useful. This article received some media attention upon Early View publication over the summer. You can read the Press Release about it here.
Post provided by ALISTAIR HOBDAY (senior principal research scientist, CSIRO Australia), Tim Lynch (senior research scientist, CSIRO, Australia) and Rachael Alderman (wildlife biologist, Tasmanian Department of Primary Industry, Parks, Water and Environment, Australia).
Behavioural and ecological research and monitoring of wildlife populations are based on collection of field data. Demographic data, such as breeding frequency, birth rates and juvenile survival, have been critical in understanding population trends for a wide range of species.
Photography has been extensively used by field biologists and ecologists to gather these data and they have been quick to take up improvements in this technology. Many field programmes today use photography either for primary data collection or the communication of results. Advances in digital photography, image storage and transmission, image processing software and web-based dissemination of images have been extremely rapid in recent years, offering ecologists and biologists a range of powerful tools.
Digital imagery has been captured from a wide range of platforms, each of which has various advantages and limitations for biological study. The most remote images are captured from satellite-based sensors, which have been used to assess population abundance of large animals, such as elephant seals, or locate colonies of emperor penguins. Cameras mounted on aircraft can also provide large-scale perspectives but both of these platforms suffer from high cost, operational limitations due to weather, and limited temporal replication. Recent use of drones, while cheaper, still requires a person to be close to the survey location and can only be used in short bursts, typically lasting less than 20 minutes.
Land-based cameras – or those fixed onto animals – can track behaviour closely, but have low sample size as data tends to be collected at the scale of individual or small groups. To improve replication, fleets of remote cameras can be used or multiple images stitched together post hoc to form a montage. However, this increases cost, either for hardware or labour to manually construct panoramas. To date all these camera systems have had limits to their spatial and/or temporal resolution and, therefore, to the number of individuals covered. This restricts biological study at the population level. Continue reading “High-Res Camera Surveys of Wildlife Colonies: The advantages over traditional approaches”
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