Was it the organizers, attendees (see Rule 3), goals, size, subject matter, timetabling, activities, venue, location, seating plan, seats, timetable, time keeping, props, access to plug sockets, ...projection equipment, biscuits, heating, travel, weather? ...problems with not sticking to your plan: unexpected discussions or opportunities can tempt you to deviate from your timetable. Acknowledgments Thank you to co-organizers, funders (British Ecological Society, Microsoft Research, Microsoft Research Connections, Natural Environment Research Council NERC), participants, and organizations who supported workshops I've worked on.
•Science and policy rely on reliable and unbiased communications.•Visualisations and graphics are a powerful means to communicate.•Ecology lacks appropriate expertise, skills, and knowledge in ...visualisation.•Great opportunities are available if we rethink the role of visualisation in our work.•The way we think about visualisation needs to be reframed within our disciplines.
Visualisations and graphics are fundamental to studying complex subject matter. However, beyond acknowledging this value, scientists and science-policy programmes rarely consider how visualisations can enable discovery, create engaging and robust reporting, or support online resources. Producing accessible and unbiased visualisations from complicated, uncertain data requires expertise and knowledge from science, policy, computing, and design. However, visualisation is rarely found in our scientific training, organisations, or collaborations. As new policy programmes develop e.g., the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), we need information visualisation to permeate increasingly both the work of scientists and science policy. The alternative is increased potential for missed discoveries, miscommunications, and, at worst, creating a bias towards the research that is easiest to display.
In this first of three papers we examine the use of niche concepts in ecology and especially in species distribution modelling (SDM). This paper deliberately focuses on the lack of clarity found in ...the term 'niche'. Because its meanings are so diverse, the term niche tends to create confusion and requires constant qualification. The literature houses many idiosyncratic ideas of what the niche is, but few examples where niche is more explanatory than the terminologies of population and community ecology or the statistical methods used to implement SDM analyses. In many cases the original (and inspirational) concepts are not directly applicable to our modern applications (e.g. set theory). There are some conceptual limitations found in individual definitions of niche (e.g. the fundamental niche concept), so it is perhaps understandable why more neutral terminology is becoming popular in SDM. An examination of the literature reveals a wide range of uncritical use of niche terminology. Our findings in this paper do not necessarily support the position of niche as a universally useful concept.
By over-focusing on precise definitions, ecology has produced a confused idea of the niche concept. This, our second paper, develops a practical philosophy for the niche that approaches the concept ...at the correct level of abstraction. We deconstruct the niche into effect and response components and then reconstruct those parts into a general, visual schematic of the niche and ecology. Using this schematic we examine the relationship of particular niche ideas to ecology, and examine the relationship between niche and ecological subdisciplines, particularly species distribution modelling (SDM). This general description clarifies the duality of the niche concept, as both a facet of species and a facet of environments. Unclear use of these dual concepts can confuse the scientific approach, and our ideas about uncertainty and error. By misclassifying models as concepts, ecology has confused the niche. Our practical philosophy uses the current wealth of ecological and niche ideas as a panoramic view of a general niche concept. We argue that stitching the niche produces a concept that underpins straightforward ecological thinking.
In particular, the use and development of software tools is becoming vital for investigating scientific hypotheses, and a wide range of scientists are finding software development playing a more ...central role in their day-to-day research. While many guides to software development exist, they are often aimed at computer scientists 6 or concentrate on large open-source projects 7; the present guide is aimed specifically at the vast majority of scientific researchers: those without formal training in computer science.
In a discussion it is often easier to staunchly reject or offer resolute support for an idea. This third paper on the niche concept aims to develop a balanced argument by exploring general principles ...for determining an appropriate level for pitching the niche concept that will guide better use and less abuse of niche concepts. To do this we first have to accept that niche concepts are not necessarily essential for ecology. Rather than to improve niche concepts, our aim should then be to pitch the niche in terms of ecology. This aim helps us develop an 'ultimate goal of the niche' by which we can evaluate the concepts we use. For species distribution modelling, there has been a focus on the niche as an equilibrium outcome that perhaps has less relevance for disequilibrium situations (e.g. climate change projections). As is the case for much of ecology, more causal explanations of species' distributions use alternative terminologies and less frequently use the word 'niche'. We suggest that niche concepts that are better aligned with the rest of ecology could arise from taking more responsibility for our own implementations, and by explaining our models with terms other than niche. A general, holistic niche concept promotes this view and promotes practical thinking about what we are modelling and how we interpret those models, which in turn should help inspire and support innovative modelling approaches in species distribution modelling.
Seeing what is not shown Hengesbach, Nicole; McInerny, Greg J.; Albuquerque, João Porto de
Information Design Journal : IDJ,
12/2022, Volume:
27, Issue:
1
Journal Article
Peer reviewed
Abstract
Critical studies of data visualization often highlight how the reductive nature of visualization methods excludes
data limitations and qualities that are crucial to understanding those data. ...This case study explores how a data visualization
could express contingent, situated, and contextual facets of data. We examine how such data limitations might be surfaced and
represented within visualizations through an interplay between the critique of an existing data visualization and the development
of alternative designs. Based on a case study of urban tree data, we interrogate data limitations in relation to four different
types of missingness: Incompleteness, Emptiness, Absence, and Nothingness. Our study enables reflections on how data limitations
can be investigated using visualizations and considers the development of a critical visualization practice.
Summary
1. Developing the next‐generation of species distribution modelling (SDM) requires solutions to a number of widely recognised problems. Here, we address the problem of uncertainty in ...predictor variables arising from fine‐scale environmental variation.
2. We explain how this uncertainty may cause scale‐dependent ‘regression dilution’, elsewhere a well‐understood statistical issue, and explain its consequences for SDM. We then demonstrate a simple, general correction for regression dilution based on Bayesian methods using latent variables. With this correction in place, unbiased estimates of species occupancy vs. the true environment can be retrieved from data on occupancy vs. measured environment, where measured environment is correlated with the true environment, but subject to substantial measurement error.
3. We then show how applying our correction to multiple co‐occurring species simultaneously increases the accuracy of parameter estimates for each species, as well as estimates for the true environment at each survey plot – a phenomenon we call ‘neighbourly advice’. With a sufficient number of species, the estimates of the true environment at each plot can become extremely accurate.
4. Our correction for regression dilution could be integrated with models addressing other issues in SDM, e.g. biotic interactions and/or spatial dynamics. We suggest that Bayesian analysis, as employed here to address uncertainty in predictor variables, might offer a flexible toolbox for developing such next‐generation species distribution models.
Aim Human impacts on the biosphere are a matter of urgent and growing concern, with ecologists increasingly being asked to project biodiversity futures. The Intergovernmental Platform on Biodiversity ...and Ecosystem Services (IPBES) is likely to comprehensively assess such projections, yet despite being widely used and potentially critical tools for analysing socio-environmental futures, integrated assessment models (IAMs) have received little attention from ecological modellers. We aim to raise awareness and understanding of IAMs among ecologists by describing the structure and composition of IAMs, assessing their utility for biodiversity projections and identifying limitations that hamper greater interaction between scientists using IAMs and those using ecological models. We also hope to inspire more accessible and applicable models by suggesting development needs for IAMs. Methods We conduct a systematic review of four state-of-the-art IAMs, which describes and contrasts key model features and analyses six aspects of IAMs that are of fundamental interest to ecologists. Conclusions IAMs could be valuable for modelling biodiversity futures; however, current IAMs were not developed for this application and challenges remain for ecologists looking to use their outputs. Separating and understanding the differences resulting from IAM formulation and those resulting from specific scenario assumptions is currently problematic, and current IAMs may be unable to accurately represent environmental conditions for both Earth-system projections and for building robust models of biodiversity because key ecological processes are absent. We suggest that model intercomparisons would identify differences in model dynamics, and detailed studies of how dynamical interactions between components influence behaviour would address why such differences arise. Bioeconomic fisheries models and agriculture pollination models provide starting points for integrating key ecological feedbacks within IAMs. Ultimately, making IAMs more accessible within the multidisciplinary study of global change, drawing on user-centred research, would enable more resolved, reliable and accurate assessment of how Earth's socio-ecological system is approaching planetary boundaries.
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