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 →
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 →
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.
The Southampton based research team including Dr Clive Trueman, Dr Katie St. John Glew and Dr Laura Graham, built maps of the chemical variations in jellyfish caught in an area of approximately 1 million km2 of the UK shelf seas. These chemical signals vary according to where the fish has been feeding due to differences in the marine environment’s chemistry, biology and physical processes. Continue reading →
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 →
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 →
مدلسازی توزیع گونهها به تخمین و برآورد ارتباط بین مجموعهای از نقاط حضور گونه با متغیرهای زیستمحیطی مرتبط می پردازد. یکی از مراحل اساسی این فرایند، ارزیابی قدرت مدل برای پیشبینی مکانهایی است که احتمال حضورگونه در آنجا وجود دارد. این کار اغلب با ارزیابی پیشبینی انجام شده در مجموعهای ازنقاط که در فرآیند مدلسازی مورد استفاده قرار نگرفته اند (نقاط آزمایشی) صورت میگیرد.
تقسیم تصادفی دادههای حضور گونه به نقاط آزمایشی و آموزشی
مطالعات پیشین بر این نکته تاکید دارند که به منظور ارزیابی معتبر، نقاط آزمایشی باید مستقل از نقاط آموزشی باشند، این درحالیست که داده مستقل واقعی به ندرت در دسترس می باشد. به همین دلیل، در فرایند مدلسازی معمولا دادههای موجود را به دو قسمت دادههای آموزشی (برای کالیبره کردن مدل) و داده های آزمایشی (برای ارزیابی دقت مدل) تقسیم میکنند، این استراتژی میتواند چند قسمتی هم باشد (برای مثال اعتبارسنجی متقاطع یا cross-validation). از آنجاییکه این تقسیم بندی معمولا بصورت تصادفی انجام میشود، بنابراین گاهی اوقات نقاط آزمایشی در فواصل نزدیک به نقاط آموزشی قرار میگیرند. شکل زیر این مساله را به خوبی نشان می دهد که در آن نقاط آزمایشی به رنگ قرمز و نقاط آموزشی آبی هستند. اما آیا این مساله میتواند مشکلی ایجاد کند؟ Continue reading →
As human impacts on the world accelerate, so does the need for tools to monitor the effects we have on species and ecosystems. Alongside technologies like camera traps and satellite remote sensing, passive acoustic monitoring (PAM) has emerged as an increasingly valuable and flexible tool in ecology. The idea behind PAM is straightforward: autonomous acoustic sensors are placed in the field to collect audio recordings. The wildlife sounds within those recordings are then used to calculate important ecological metrics – such as species occupancy and relative abundance, behaviour and phenology, or community richness and diversity.
The Pros and Cons of Passive Acoustic Monitoring
Using sound to monitor ecosystems, rather than traditional survey methods or visual media, has many advantages. For example, it’s much easier to survey vocalising animals that are nocturnal, underwater or otherwise difficult to see. Also, because acoustic sensors capture the entire soundscape, it’s possible to calculate acoustic biodiversity metrics that aim to describe the entire vocalising animal community, as well as abiotic elements in the environment.
The use of PAM in ecology has been steadily growing for a couple of decades, mainly in bat and cetacean studies. But with sensor costs dropping and audio processing tools improving, there’s currently a massive growth in interest in applying acoustic methods to large-scale or long-term monitoring projects. As very low-cost sensors such as AudioMoth start to emerge, it’s becoming easier to deploy large numbers of sensors in the field and start collecting data. Continue reading →
Spatial Conservation Planning and the Quest for Perfect Data
Conservation planners and managers often need to make decisions with imperfect information. When deciding what action to take or how to divide resources between candidate locations, we rarely have all the information we’d like on what species are present at a site or which areas are most critical for supporting their population viability. A large volume of ecological research focuses on answering these very questions.
To make conservation decisions, we need other types of data as well. These include information on things like the cost of carrying out a given conservation action, current condition of sites, the distribution and intensity of threats in a region, and much more. Many conservation problems are spatial, meaning that we often need to decide between multiple candidate locations and that there are spatial dependencies between sites that need to be accounted for. All these different pieces of information are needed to make cost-efficient and effective conservation decisions.
Ecologists and conservation biologists are usually concerned about the completeness and accuracy of the ecological data used to make these decisions (understandably). But less effort has been spent in researching and verifying the accuracy of the types of data mentioned above. At the same time, we have relatively poor understanding of how data gaps influence solutions optimised across multiple species and locations, and the relative importance of gaps in different types of data. This is what we set out to find in ‘Not all data are equal: Influence of data type and amount in spatial conservation prioritisation’. Continue reading →