Tag: Species Distribution Models

Robert May Prize

Increasing Complexity in Species Distribution Modelling

Megan Laxton and colleagues originally set out to translate an existing example of a species distribution model into a new software framework. However, what originated as a simple modelling example developed into a discussion on structural complexity in species distribution models. Complexity in Species Distribution Models The original idea for our paper was to provide a worked example demonstrating the usage of the R package … Continue reading Increasing Complexity in Species Distribution Modelling

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Statistical methods

voluModel: a new R package to model species distributions in 3 dimensions

Post provided by Hannah Owens (she/her)

One of the base units of analysis for biogeography and conservation science is the species range map. Once we know where a species is, we can ask questions like “Why is it there?”, “How did it get there?”, or “What can we do to make this place better for it?” Especially these days, I am very interested in mapping marine fish distributions, which, it turns out, is not as simple as mapping terrestrial species.

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Unknown's avatarBen Whittaker1 Comment
Conservation and management, Field Methods

Understanding climate change through animal song

Post provided by Diego Llusia (he/him), Camille Desjonquères (she/her) and Sara Víllen-Peréz (she/her)

Many species produce sound as a means of communication, emitting calls or songs to broadcast information to others in the surrounding area. In this blog post, Diego Llusia, Camille Desjonquères, and Sara Víllen-Peréz discuss their research on recording animal calls and how these soundtracks can be used to help monitor the impacts of climate change. 

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Unknown's avatarBen Whittaker1 Comment
Robert May Prize

Spatial thinning and class balancing: Key choices lead to variation in the performance of species distribution models with citizen science data

Post provided by Valerie Steen

Each year Methods in Ecology and Evolution awards the Robert May Prize to the best paper published in the journal by an author at the start of their career. Ten Early Career Researchers made the shortlist for this year’s prize, including Valerie Steen who is a Postdoctoral Researcher at Oregon State University in the USA. In this interview, Valerie shares insights on her paper ‘Spatial thinning and class balancing: Key choices lead to variation in the performance of species distribution models with citizen science data’.

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Robert May Prize

Robert May Prize 2021: Winner Announced

We are delighted to announce David Wilkinson as the winner of the Robert May Prize 2021, awarded to the best paper by an early career researcher in the 2021 volume of Methods in Ecology and Evolution. In this interview, David shares insights on his winning article ‘Defining and evaluating predictions of joint species distribution models’. Congratulations to all the shortlisted authors, whose articles you can read … Continue reading Robert May Prize 2021: Winner Announced

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Conservation and management, Statistical methods

Let’s get real: translating species distribution models into conservation practice

Post provided by Veronica F. Frans

Species distribution models (SDMs) are popular methods for identifying important habitats for species, but what does it take to translate SDMs into conservation practice? In this post, Veronica Frans discusses the applications of iSDMdb as featured in the paper, “Integrated SDM database: enhancing the relevance and utility of species distribution models in conservation management”, recently published in Methods in Ecology and Evolution.

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Methods 10th Anniversary

10th Anniversary Volume 5: Extracting Signals of Change from Noisy Ecological Data

Post provided by Nick J. B. Isaac

To celebrate the 10th Anniversary of the launch of Methods in Ecology and Evolution, we are highlighting an article from each volume to feature in the Methods.blog.

For Volume 5, we have selected ‘Statistics for citizen science: extracting signals of change from noisy ecological data’ by Isaac et al. (2014).  In this post, the authors discuss the background and key concepts of the article, and the application of the article for assessing biodiversity occurrence datasets.

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Methods 10th Anniversary, Statistical methods, Theoretical methods

10th Anniversary Volume 1: The Art of Modelling Range-Shifting Species

Post provided by Jane Elith, Mike Kearney and Steven Phillips  

10th anniversary logo

To celebrate the 10th Anniversary of the launch of Methods in Ecology and Evolution, we are highlighting an article from each volume to feature in the Methods.blog. For Volume 1, we have selected ‘The art of modelling range-shifting species’ by Elith et al. (2010).  In this post, first author, Professor Jane Elith, discusses the background and key concepts of the article, and how things have changed since the paper was published.

Illustration of the idea that model settings affect prediction.

We started work on this manuscript around 2008, prompted by increasing use of species distribution models for climate change and invasive species problems. At that stage there was growing recognition of the problems in these applications (e.g. see a recent MEE review on transferability) but relatively few tools for dealing with them. In our view, if correlative models are to be used for such purposes, the data and models require special attention.

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Uncategorized

Issue 10.12: Statistical Ecology, UAVs, Invasive Species and More

The December issue of Methods is now online!

The final 2019 issue of Methods in Ecology and Evolution is online now.

To close out another brilliant year, we’ve got papers on invasive species, convolutional neural networks, rapid spatial risk modelling, species distribution models and much more.

You can find out more about our Featured Articles (selected by the Senior Editor) below. We also discuss this month’s Open Access and freely available papers we’ve published in our latest issue (Practical Tools and Applications articles are always free to access, whether you have a subscription or not) .

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