Dr. Dao (crouching on right) and team with Dr. Tovi Lehmann (with sandals), Dr. Yaro (with white cap), and Moussa Diallo (front).
The fact that mosquitoes are insects of massive importance is of little dispute. With malaria still killing almost half a million people annually and after recent outbreaks of Zika, dengue and West-Nile viruses the threat of mosquito-borne diseases is becoming common knowledge. The meme of ‘Mosquitoes are the No.1 killer of all time,’ is also growing more popular (I even heard it from my 8-year-old kid one day after he returned from school!). Yet, with all we think we know about the little bug(ger)s, it’s probably only the tip of the iceberg.
Much work was done over the past century to try to answer basic questions about mosquitoes like:
How big are their populations?
How long do they live?
Where do they go when we don’t see or feel them?
Different methods have been developed to provide insights and notions on the mosquitoes’ movements, survival, and populations estimates; but the limitations and conditions of these methods mean that our knowledge is still incomplete.
One of the gold-standard tools for answering questions like those above is Mark-Release-Recapture (MRR). It was developed almost a century ago and has been modified and remodified through the years, as different marking technologies became available. Continue reading →
Pathogens and the infectious diseases that they cause can have devastating impacts on host individuals and populations. To better understand how pathogens are able to cause disease, we can investigate the genetic mechanisms underlying the infection process. Hosts may respond to infection by upregulating defence pathways. Pathogens, in turn, evade these host immune responses as they infect and cause disease. As this process unfolds and each organism responds to the other, gene expression changes in both the host and the pathogen. These gene expression changes can be captured by dual RNA‐seq, which simultaneously captures the gene expression profiles of a host and of a pathogen during infection. Continue reading →
Analysis of datasets collected on marked individuals has spurred the development of statistical methodology to account for imperfect detection. This has relevance beyond the dynamics of marked populations. A couple of great examples of this are determining site occupancy or disease infection state.
The regular series of EURING-sponsored meetings (which began in 1986) have been key to this development. They’ve brought together biological practitioners, applied modellers and theoretical statisticians to encourage an exchange of ideas, data and methods.
This new cross-journal Special Feature between Methods in Ecology and Evolution and Ecology and Evolution, edited by Rob Robinson and Beth Gardner, brings together a collection of papers from the most recent EURING meeting. That meeting was held in Barcelona, Spain, 2017, and was hosted by the Museu de Ciènces Naturals de Barcelona. Although birds have provided a convenient focus, the methods are applicable to a wide range of taxa, from plants to large mammals. Continue reading →
The discovery of Chronic Wasting Disease (CWD) in Norway in 2016 has led to extensive measures and testing of deer in Norway. Since 2018 there have been similar measures within the EU. But how many deer need to be tested before we can be (almost) certain that a population is not infected by CWD?
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 →
Current eDNA sampling technologies consist mainly of do‐it‐yourself solutions. The lack of purpose‐built sampling equipment is limiting the efficiency and standardization of eDNA studies. So, Thomas et al. (a team of molecular ecologists and engineers) designed ANDe™.
In this video, the authors highlight the key features and benefits of ANDe™. This integrated system includes a backpack-portable pump that integrates sensor feedback, a pole extension with remote pump controller, custom‐made filter housings in single‐use packets for each sampling site and on-board sample storage.
This double-size issue contains six Applications articles (one of which is Open Access) and two Open Access research articles. These eight papers are freely available to everyone, no subscription required.
–Temperature Manipulation: Welshofer et al. present a modified International Tundra Experiment (ITEX) chamber design for year-round outdoor use in warming taller-stature plant communities up to 1.5 m tall.This design is a valuable tool for examining the effects of in situ warming on understudied taller-stature plant communities
–Zoon: The disjointed nature of the current species distribution modelling (SDM) research environment hinders evaluation of new methods, synthesis of current knowledge and the dissemination of new methods to SDM users. The zoon R package aims to overcome these problems by providing a modular framework for constructing reproducible SDM workflows.
–BEIN R Package: The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data. The bien r package allows users to access the multiple types of data in the BIEN database. This represents a significant achievement in biological data integration, cleaning and standardisation.
A salamander having its skin swabbed to test for Bsal infection.
Imagine you’re at the doctor’s office. You’re waiting to hear back on a critical test result. With recent emerging infectious diseases in human populations, you are worried you may be infected after a sampling trip to a remote field site. The doctor walks in. You sit nervously, sensing a slight tremble in your left leg. The doctor confidently declares, “Well, your tests results came back negative.” In that moment, you let out a sigh of relief, the kind you feel throughout your body. Then, thoughts start flooding your mind. You wonder– what are the rates of false negatives associated with the test? How sensitive is the diagnostic test to low levels of infection? The doctor didn’t sample all of your blood, so how can they be sure I’m not infected? Is the doctor’s conclusion right?
Now, let’s say I’m the doctor and my patient is an amphibian. I don’t have an office where the amphibian can come in and listen to me explain the diagnosis or the progression of disease − BUT I do regularly test amphibians in the wild for a fatal fungal pathogen, known as Batrachochytrium dendrobatidis (commonly known as Bd). Diseases like Bd are among the leading causes of the approximately one-third of amphibian species that are threatened, near threatened, or vulnerable to extinction. To test for Bd, and the recently emerged sister taxonBatrachochytrium salamandrivorans (hereafter referred to as: Bsal), disease ecologists rely on non-invasive skin swabs. Continue reading →
X-ray micro-computed tomography – or µCT – is a technique that uses x-rays to create high resolution cross-sections of samples. Virtual 3D models can be made from these cross-sections without destroying the original samples. Micro-CT has important applications in medical imaging and, in the biomedical field, in vivo µCT allows researchers to make virtual 3D models of the skeleton and organs of live small animals. Three-dimensional models like these could provide insight into diseases and guide the development of medicines and therapies.
In vivo µCT holds three major advantages over other methods:
It allows for repeated measurements of small live animals at different times without having to sacrifice them.
It eliminates variation among individuals.
It can reduce the number of animals required to obtain statistically meaningful data.
A variety of commercially available µCT scanners that are optimised for scanning live animals are now available. The use of in vivo µCT in ecological and evolutionary studies, however, has greatly lagged behind its use in biomedical studies. Continue reading →
A model that predicts outbreaks of zoonotic diseases – those originating in livestock or wildlife such as Ebola and Zika – based on changes in climate, population growth and land use has been developed by a UCL-led team of researchers.