From open data to preregistration of hypotheses, Erlend Nilsen and colleagues ask how can we make the most of open science in applied ecology? Take a look at this introduction to their recent Commentary and share your thoughts in the comments below.
A world in rapid change
The world around us is changing rapidly, and much of the research reported through Journal of Applied Ecology is, in one way or another, linked to ongoing global environmental and climate change. These challenges are real, so we need to muster all available data as best we can to find ways to mitigate and even reverse unnecessary environmental degradation, whilst at the same time securing the livelihood of the people who inhabit the land.
However, it is not only the world surrounding us that is changing. So too does the world of science. One of the more remarkable changes over the last half decade is the emergence of an ‘open science’ culture.
Openness about the scientific process
Open science is a fundamental way of thinking about the scientific enterprise. Open data, open access and open code (which is often required when publishing in scientific journals) are very visible elements of the open science culture. But open science is much more than this. Open science also include ideas about which part of the scientific process and products should be open to the public, and how science should relate to the larger society. It potentially affects all parts of the research life cycle, even the question setting and planning stage. The rise of the open science movement is sometimes seen as a response to the so called ‘reproducibility crisis’, as discussed here.
So how can, or should, we reorient ourselves to harvest the benefits from the open science movement, so that we can produce evidence that is as robust as possible, and research that can be used to understand the natural world and manage resources in a sustainable way?
Patterns and causality in an open science era
In our Commentary, Exploratory and confirmatory research in the open science era, we discuss some of the implications of the transition towards a more open science culture in applied ecology and conservation. The specific backdrop of our commentary is the classical debate about confirmatory (i.e. hypothesis testing) and exploratory (i.e. descriptive) research. Inspired by the seminal paper by Graham Caughley published 26 years ago, we conducted a rapid screening of a sample of the published literature. We find that a majority of studies in applied ecology and conservation that do not address specific hypotheses, and that most true experiments are conducted on small geographical scales.
What are the consequences of this, and how can we better harness the benefits of the open science era to make the science as robust as possible? One of our key messages is that while we do need both descriptive and confirmatory work, mixing them up is not a good idea. In general, we argue that there should be much clearer distinction between studies that seek to describe and those that seek to establish causal relationships than what is currently the case in applied ecology.
Together we can do this
The open science era offers many tools and routines (e.g. efficient use of open data, preregistration of hypotheses or the analysis plans, registration of post-hoc hypothesis for later testing) that can improve the situation. Moreover, recent developments in statistical models (e.g. models for integrating various data sets, novel models for causal inference, and evidence synthesis for compiling evidence) should allow us to better utilise observational biodiversity data to make causal inference.
It can take time to change a culture, and both scientists, journal editors and research funders should contribute to the change. This way, we can we can fully utilise the potential that the open science era holds.
Read the open access Commentary, Exploratory and confirmatory research in the open science era, in Journal of Applied Ecology.