One of the ‘grand challenges’ for scientists, governments, stakeholders and practitioners around the world is to understand and predict how climate change will continue to impact upon natural ecosystems and the social and economic services they provide. This is a Herculean task; changes in climate vary greatly across space and time, attribution of observed changes to anthropogenic climate change is challenging, and climate change acts in combination with other human pressures, resulting in a wide range of impacts on natural systems. However, scientific research can help determine where and when changes to species distributions and ecosystem structure and functioning will occur, and identify which species are likely to be ‘winners’ and ‘losers’, providing guidance to assist with adaptive management of ecosystems and the services they provide.

Our understanding of how climate change has affected life on Earth has been driven by important studies of general patterns, and broad-scale correlative modelling of changes in species distributions, and typically communicated as poleward or depth-related range shifts in response to large-scale average change in regional or global climate.
But in our quest for generalizations, and perhaps to communicate complex scientific findings to non-scientists, have we clouded our interpretation and expectations of what we observe? Generalizations and overall trends, whilst useful heuristically, frequently fail to match the observed ecological responses that are driven by local, short-term variability.

Fig. 1. Zonation of species on a rocky shore due to differing biological tolerances to local environmental conditions. Image: Chris Harley.

For example, 30+ year trends in average sea surface temperature are increasingly being used to project and forecast species’ range limits, despite the knowledge that decadal-scale increases in mean temperature—or climate—are not driving performance and survival at organismal scales and are ultimately not the cause of observed changes. Shorter-term variation in local environmental conditions—weather, including extreme events—are the underlying drivers of species distributions and ecosystem functioning via effects on the physiology of individual organisms.

Understanding the mechanisms by which organisms interact with the environment around them (Figure 1.) can help to identify regions where species will be most vulnerable to climate change, identify the potential triggers of tipping points in the structure and healthy functioning of marine ecosystems, and devise ‘guard tails’ to prevent some of the worst impacts from happening. As climate change also interacts with other stressors, identifying areas where species are vulnerable to climate change means that we may be able to alleviate manageable stressors such as pollution or harvesting/fishing.

Communicating impacts

Humans, like other organisms, are affected by weather rather than climate per se, and people’s perception of climate change is shaped significantly through their experience of weather and short-term personal experience. Psychological studies into levels of trust between audiences and communicators show that weather forecasters are highly trusted due to their daily predictions being empirically tested by their lay
audience, with an acceptable level of error (Figure 2). This is in contrast to current scientific communication of climate change impacts, whereby presenting average trends (akin to the weather forecaster giving the same average forecast each day for a month) that are not observed each day across the timeframe can serve to undermine trust, as no concession was made for variability.

Implications for end users

Climate management strategies aim to enhance the resilience of natural and human-managed systems, and maintain sustainable ecosystem services. Implementation of such strategies can be hampered and misled by an over-reliance on simplified trends, as management decisions require forecasts that account for responses at far smaller spatial and temporal scales, for example within individual marine protected areas or catchment areas. As a result of this mismatch, management actions are too often based on broad-scale trends and averages that may have very little to do with the vulnerability of organisms and ecosystems at a local scale, and any deviations from these generalizations can be misinterpreted as counter-evidence to global warming.

Creating biologically relevant metrics of environmental change that include how climate drives weather, and the knowledge of how organisms and ecosystems will respond at appropriate spatial and temporal scales, can offer insight into which aspects of climate change may be most important to monitor and predict. This approach can also enhance our ability to communicate impacts to non-scientists, especially government legislators, policymakers and stakeholders attempting to enact climate change adaptation strategies.

It is clear from our findings that shifts in species ranges predicted by over-simplistic, generalist models are likely to be contradicted in any but the broadest terms. Responses differ depending on the level of stress and the location of the organism, as well as species-specific thermal tolerances with respect to the range and mosaic of geographical patterns in temperature experienced across the biogeographic range of any species (Figure 4).

We need to develop mechanistic frameworks that account for local environmental conditions and biological responses, and understand how these impacts translate into ecological responses that affect humans. Whilst it is unrealistic to experimentally study many combinations of stressors and organisms, a better understanding of mechanisms can highlight vulnerabilities in organisms and ecosystems, and incorporate inherent variability within predictions of future distributions and responses of species.
By taking a more joined-up approach we can combine information on climate change, biological responses and the direct impacts for society, and report these findings at scales relevant to managed areas and marine reserves, thereby enhance communication among climate researchers, stakeholders and the general public.

Dr Nova Mieszkowska of The Marine Biological Association and Brian Helmuth of Northeastern University.

This article first appeared in Issue 4 of The Marine Biologist magazine, spring 2015. The magazine is available as a benefit of MBA membership. Find out more about becoming a member of the MBA.

International Network for the Study of Intertidal Ecosytems INSHORE:

Fig. 2. We tend to trust daily weather predictions because we can test them against our own observations. Weatherman: Jim Gandy, Chief Meteorologist, News 19, USA.Fig. 3. ‘Robolimpet’. Image: Fernando Lima

Fig. 4. Starfish and mussels on the shore. Image: Brian Helmuth.

Gray Williams  & Bayden Russell, The Swire Institute of Marine Science, The University of Hong Kong, Hong Kong

Brian Helmuth, Northeastern University, USA

Nova Mieszkowska, Marine Biological Association of the UK

Gianluca Sarà, University of Palermo, Italy

Fernando Lima, CIBIO, University of Porto, Portugal

Chris Harley, University of British Columbia, Canada

Yunwei Dong, Xiamen University, China

Sean Connell, University of Adelaide, Australia

Christopher McQuaid, Rhodes University, South Africa

Gil Rilov, Israel Oceanographic and Limnological Research, Haifa, Israel

Read more: Beyond long-term averages: making biological sense of a rapidly changing world. Climate Change Responses 1: 1-12

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Nova Mieszkowska and Brian Helmuth.

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