Quantifying animal movement is central to research spanning a variety of topics. It’s an important area of study for behavioural ecologists, evolutionary biologists, ecotoxicologists and many more. There are a lot of ways to track animals, but they’re often difficult, especially for people who don’t have a strong background in programming. Vivek Hari Sridhar, Dominique G. Roche and Simon Gingins have developed a new, simple software to … Continue reading Quantifying Animal Movement from Videos
There’s a frustrating yin and yang to biological research: motivated by curiosity and imagination, we often find ourselves instead defined by limitations. Some of these are fundamental human conditions. The spectrum of light detectable by human eyes, for example, means we can never see a flower the way a bee sees it. Others limitations, like funding and time, are realities of modern-day social and economic systems.
Early career researchers (ECRs) starting new projects and delving into new research systems must be especially creative to overcome the odds. Large grants can be transformative, giving a research group the equipment and resources to complete a study, but they’re tough to get. Inexperienced ECRs are at a disadvantage when competing against battle-hardened investigators with years of grant writing experience. Small grants of up to about $5000 USD, on the other hand, are comparatively easy to find. So, how can ECRs make the most of small, intermittent sources of funding?
Hay un frustrante toma-y-dame en el campo de la investigación biológica: motivados por la curiosidad y la imaginación, a menudo nos encontramos definidos por limitaciones. Algunas de estas, como nuestros sentidos, son condiciones humanas fundamentales. El espectro de luz detectable por los ojos humanos, por ejemplo, significa que nunca podremos ver a una flor de la misma forma en que la ve una abeja. Otras limitaciones, como financiamiento y tiempo, representan las realidades de los sistemas sociales y económicos de hoy día.
Los investigadores al comienzo de sus carreras (Early Career Researchers, o ECRs en sus siglas en inglés) que se embarcan en nuevos proyectos y se involucran con sistemas nuevos de investigación deben ser especialmente creativos para poder superar las probabilidades. Una generosa beca puede ser transformativa, pero un ECR con poca experiencia está en desventaja cuando compite con investigadores ya endurecidos por la batalla, quienes tienen años de experiencia escribiendo propuestas de financiamiento. Por otra parte, las pequeñas becas en el rango de $2.000 a $5.000 son comparativamente fáciles de encontrar. ¿Cómo puede un ECR aprovechar al máximo estas pequeñas e intermitentes fuentes de financiamiento?
Scientists from international conservation charity ZSL (Zoological Society of London), Imperial College London and conservationists from the Rotokare Scenic Reserve Trust used acoustic monitoring devices to listen in on the ‘conversations’ of New Zealand’s endemic hihi bird, allowing them to assess the success of the reintroduction without impacting the group.
For the first time ZSL scientists were able to use the calls of a species as a proxy for their movement. A happy hihi call sounds like two marbles clanging together in what is known as the ‘stitch’ call. Scientists saw the calls change from an initial random distribution to a more settled home range – marking the hihi reintroduction and the new method a success. Continue reading “‘Eavesdropping’ Technology used to Protect one of New Zealand’s Rarest Birds”
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.
EURING Meetings
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.
Scientists at the University of Southampton have developed maps of chemicals found in jellyfish which could offer a new tool for conservation in British waters and fisheries. The maps will also be able to detect fraudulently labelled food in retail outlets by helping to trace the origins of seafood.
It is widely accepted that many conservation challenges are directly related to human behaviour. Whether it is the over-collection of a rare orchid by harvesters in Southeast Asia, or the decisions by collectors in Europe to buy and smuggle these orchids home, understanding the extent and nature of these behaviours is essential to addressing the threats they might cause. This has led conservation researchers and practitioners to start looking outside of their discipline, to find methods and approaches from across the social sciences to improve our understanding of these complex issues.
While this interdisciplinarity is a positive move for conservation, it is important that we treat these ‘new’ methods carefully and understand their limitations. If we don’t, there is a risk that our new toolbox full of exciting methods that sound great on a funding application, may in fact not be making what we do any better, or in extreme cases they may even be making it worse.
Muitos desafios em conservação estão diretamente relacionados com o comportamento humano. Quer seja a recolha excessiva de uma orquídea rara no Sudeste Asiático, ou a compra e contrabando dessas orquídeas por colecionadores na Europa, entender a magnitude e a natureza desses comportamentos é essencial para lidar com as ameaças que eles podem causar. Isso levou os investigadores e profissionais da área de conservação a começarem a olhar para fora da sua própria disciplina, de modo a encontrar métodos e abordagens das ciências sociais para melhorar a nossa compreensão sobre estas questões complexas.
Embora esta interdisciplinaridade seja um passo positivo para a conservação, é importante tratar esses “novos” métodos com cuidado e entender as suas limitações. Se não o fizermos, existe o risco da nossa nova caixa de ferramentas, repleta de métodos interessantes que soam bem em candidaturas a financiamento, na verdade não melhorar aquilo que nós geralmente já fazemos ou, em casos extremos, até piorá-lo.
Tendo isto em conta, um grupo de cientistas sociais em conservação, liderado por investigadores das Universidades de Oxford e Exeter, decidiu examinar em profundidade um desses “novos” métodos, fornecer recomendações sobre quando e como ele deveria ser usado, e quando não deveria. O artigo, disponível gratuitamente na revista científica Methods in Ecology and Evolution nesta semana, examina a Técnica de Contagem de Itens (TCI), que tem sido cada vez mais usada em conservação para fazer perguntas sobre tópicos “sensíveis”. Continue reading “Limitações e benefícios da técnica de contagem de itens: considerações sobre o uso de novos métodos em Conservação”
Metapopulation Microcosm Plates (MMP) are devices which resemble 96-well microtiter plates in size and shape, but with corridors connecting the wells in any configuration desired. They can be used to culture microbial metapopulations or metacommunities with up to 96 habitat patches.
In these two video tutorials, Helen Kurkjian explains how you can assemble, fill and clean MMPs in your lab.
Modelling species distributions involves relating a set of species occurrences to relevant environmental variables. An important step in this process is assessing how good your model is at figuring out where your target species is. We generally do this by evaluating the predictions made for a set of locations that aren’t included in the model fitting process (the ‘testing points’).
Random splitting of the species occurrence data into training and testing points
The normal, practical advice people give about this suggests that, for reliable validation, the testing points should be independent of the points used to train the model. But, truly independent data are often not available. Instead, modellers usually split their data into a training set (for model fitting) and a testing set (for model validation), and this can be done to produce multiple splits (e.g. for cross-validation). The splitting is typically done randomly. So testing points sometimes end up located close to training points. You can see this in the figure to the right: the testing points are in red and training points are in blue. But, could this cause any problem? Continue reading “Spatial Cross-Validation of Species Distribution Models in R: Introducing the blockCV Package”
Methods Blog 