Global Environmental Change and Biodiversity A Workshop in Paris 

1-4 May, 2005, Dourdan, France  

Background:

Population declines and extinctions of plant and animal species due to human activities have been primarily caused by habitat destruction and degradation, overexploitation, and invasive species.  Most conservation strategies have been designed to limit the negative effects of these human impacts on biodiversity.  In the future, global environmental change - increasing temperature, changes in precipitation patterns, increasing atmospheric CO2 concentration, N deposition, etc. - is likely to become a major factor influencing species abundance, distribution, and behavior (Peters & Lovejoy 1992, Chapin et al. 2001, Hannah & Lovejoy 2003).  It is essential that we develop a sound scientific understanding of how global environmental change will modify biodiversity so that decision makers can be appropriately alerted to the possible effects of global change on biodiversity, conservation strategies can be adapted to account for environmental change, and assessments can be made of the potential effects of changes in biodiversity on ecosystem services.

A wide variety of observations, models, and experiments suggest that global environmental change has modified and will continue to modify biodiversity in important ways. For example, shifts in species ranges, population declines, and changes in timing of activities of plants and animals have already occurred in the past century and are often correlated with increased temperature or changes in precipitation patterns (e.g., Pounds et al. 1999, Parmesan & Yohe 2003, Root et al. 2003).  Bioclimatic models - which are based on climate projections and climatic constraints on species estimated from current spatial distributions - suggest that projected changes in temperature and precipitation will lead to a continuation of these range shifts in the future with negative effects on biodiversity at regional and global scales (e.g., Bakkenes et al. 2002, Midgley et al. 2002, Thomas et al. 2004) and on the health of humans and agriculturally important plants and animals (e.g., Sutherst 2001, 2004). Dynamic Global Vegetation Models (DGVMS) - which simulate the response of vegetation to atmospheric and climatic change at global scales - suggest that distributions of major species groups and biomes are also likely to shift towards the poles and higher altitudes (e.g., Cramer et al.  2001, Bachelet et al. 2003, Bonan et al. 2003, Bond et al. 2003, Gerber et al. 2004).  Experiments with elevated CO2, elevated temperature, and N additions suggest that all these factors will affect plant community structure and, in some cases, lead to substantial reductions in biodiversity (e.g., Leadley et al. 1999, Shaver et al. 2000, Roem et al. 2002, Körner 2003, Zavaleta et al. 2003).

All of these approaches - observations, experiments, and models - have strengths, but also have weaknesses that limit our ability to determine the reliability of predictions of the effects of global environmental change on biodiversity in the future.  For example: 

• Observations provide evidence that global warming has already modified diversity at regional scales in situ and, as such, are exceptionally useful for persuading scientists and the public that even relatively small changes in climate can influence species distributions.  However, historical changes in climate are potentially confounded with a number of other factors including land use change, making it difficult to demonstrate a causal link between observed shifts in species distributions and climate. 

• Current species distributions provide an extraordinary database for estimating long-term climatic limits on species range and, thus, a relatively simple and powerful means of extrapolating into the future. However, bioclimatic models have not yet included rising atmospheric CO2 concentrations or N deposition as driving factors in future species distributions, even those these have already driven shifts in plant community structure and may become much more important in the future (Sala et al. 2000, Chapin et al. 2001). In addition, the positive and negative interactions between species that may maintain coherent community structure are not accounted for in these models. 

• Dynamic Global Vegetation Models provide more mechanistic representations of climatic constraints on plant distributions than bioclimatic models and some account explicitly for inter-specific interactions.  However, these models assume that plants can be grouped into large classes that have similar responses to environmental change (plant functional types), even though experiments suggest that plant functional types can be difficult to identify in situ (e.g., Poorter & Navas 2003, Morgan et al. 2004). 

• Experiments provide a means of rigorously separating cause and effect for individual factors involved in environmental change, but the small spatial and temporal scale of these experiments may make it difficult to extrapolate from experiments to real systems.   In addition, relatively few experiments to date have examined the interactions between several environmental factors and their impact on biodiversity.

Objectives:

This meeting brought together researchers 1) doing experimental work at the patch scale with elevated CO2, warming, and N deposition, 2) modeling species response to climate change at regional scales using bioclimatic envelopes, 3) modeling in shifts in plant species groups at global scales (DGVM models), and 4) analyzing observational data and developing biodiversity observation networks. The goal was to develop a research agenda that contributes to exchanges of ideas between fields of research, tests of hypotheses underlying models, and reflections on the use of observational and experimental studies. Our belief is that we can improve our confidence in the ability to predict the effects of global environmental change on biodiversity by combining and comparing a variety approaches.

Several previous international meetings have addressed issues related to climate change effects on biodiversity.  For example, researchers studying the observed impacts of climate change on wildlife have already met several times, including a recent meeting at the Tyndall Centre, UK in April 2003 (Green et al. 2003).  The objectives of our meeting differed in that we focused on the developing ties across groups of scientists having widely varying approaches to studying the effects of global change on biodiversity.  Because of the complexity of this task we limited the scope of this meeting to terrestrial ecosystems.

  A few of examples of the kinds of issues that were addressed:

• Field experiments suggest that elevated CO2 frequently increases soil water content, and that this change in soil water status often leads to shifts plant community structure (Morgan et al. 2004). DGVMs can take this effect of CO2 into account, and could be tested against these observed responses.  Bioclimatic models do not take this CO2 effect into account, even though this could alter the relationships between species distributions and climate.  How can the interactions between these different approaches be improved?

• A number of animal species have been observed to have shifted their distributions towards the poles or to higher altitudes in the last century.  However, a variety of mechanisms other than climate change could explain this (e.g., land used change).  Bioclimatic models have been criticized because they do not generally take into account species interactions, land use change, etc.  Coherence between observations and bioclimatic models would clearly increase the confidence in both approaches.  Is it possible to make a number of such comparisons?

• DGVMs predict changes in distribution of plant functional types based on semi-mechanistic approaches.  Bioclimatic models have been used to predict changes in species distributions based on current bioclimatic envelopes.  Are the predictions of species level and plant functional type responses coherent? 

• Few of the modeling or observational studies have included N deposition as a driver of vegetation change even though many experimental and local scale observational studies suggest that it can be the predominant driver of biodiversity change in regions of high N deposition.  How can this be included in the design of observational networks and in models of vegetation change?  

  Meeting Publication

  Midgley, G.F., Hannah, L., Rutherford, M.C. and Powrie, L.W.  2002.  Assessing the vulnerability of species richness to anthropogenic climate change in a biodiversity hotspot. Global Ecological Biogeography  11:445–451.  

  Meeting Agenda

  Participant List

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