Assisted Migration: Evaluating the Merits of a Newly Proposed Conservation Strategy

Will existing conservation strategies prevent global warming from driving many species to extinction? According to a recent publication by McLachlan, Hellman, and Schwartz (2007), the answer is no, because many species may not be able to tolerate, adapt, or shift their geographic distributions quickly enough to survive rapidly changing climates. Thus, current conservation solutions targeted to climate change, which are based primarily on building interconnected systems of corridors and reserves, may be inadequate for many species. Such approaches will be particularly inadequate for species that are entirely blocked from shifting their geographic ranges by anthropogenic barriers to dispersal, such as urban sprawl. Recognizing these limitations, some activist groups have begun to take matters into their own hands; the Torreya Guardians (http://www.torreyaguardians.org/), have begun transplanting Torreya taxifolia, a tree endemic to northern Florida, to points as far northward as New York. McLachlan et al. (2007) describe such intentional transport of species to prevent species extinction in light of climate change as “assisted migration”. Moreover, they point out that this newly emerging conservation strategy, while potentially useful in preventing extinction, is currently being applied in ad hoc fashion with no guiding policy or legal framework. They suggest that it is in urgent need of evaluation by coalitions of scientists, policy makers, and managers. We agree.

Assisted migration is clearly a drastic solution to a pressing problem, and many scientists may wonder whether we have sufficient knowledge and wisdom to successfully implement such a solution. Alternatively, doing nothing in the face of potentially rapid climate changes also carries significant ecological risks. Below we outline the major benefits, limitations, and potential costs of assisted migration, as well as key scientific questions and knowledge gaps that challenge the implementation of this strategy.

Benefits:
· Preventing extinctions of targeted species.
· Replacing the current ad hoc approaches to assisted migration with a more coherent set of policies and laws, grounded in the best-available science.

Limitations:
· This strategy may be too costly to protect many species (see Potential Costs, below).
· Operationally, current scientific knowledge may be insufficient to optimize this strategy (see Scientific Needs and Questions, below).
· Ethical considerations may preclude common use of this strategy.
· Environmental law and policy may prevent or hinder the application of this strategy. In particular, the heterogeneity of existing legal structures, both internationally and intranationally, may hinder attempts to implement assisted migration.
· This strategy may not protect species whose habitats or climate zones disappear entirely under global warming scenarios.

Potential Costs:
· Direct economic costs of physically transporting and establishing new populations. These costs alone may prohibit the implementation of assisted migration for all but a few favored species.
· Usurpation of limited public attention and financial support from other conservation efforts.
· Species introduced further northwards may become ‘invasive’ in their new location and may disrupt ‘native’ species assemblages that are already impacted by environmental change. In general, we have a poor ability to predict which species will aggressively invade surrounding ecosystems and which will not.
· Translocated colonists may diminish the size and genetic diversity of source populations that have the potential to survive in situ.
· Adapted gene complexes may be disrupted, maladapted genotypes translocated, and existing genetic diversity may not be adequately conserved.

Scientific Needs and Questions:
· How many species will or might go extinct in the absence of assisted migration, i.e. what is the cost of doing nothing?
· How many species exist, what is there natural history and geographic distribution? We cannot assist species unknown to science, nor those that are poorly understood.
· What factors determine which species are most likely to be come aggressive invaders? What strategies can minimize harm to native species surviving in locations where translocations are occurring?
· Better understanding of environmental tolerance, plasticity, adaptation, and dispersal.
· Better understanding of abundance and genetic structure across geographic ranges.
· Better understanding of the magnitude, time scale, and geographic variation of climate change.
· The development of strategies for optimizing the mechanics, timing and location(s) of translocations. For example:
o How should we move species, e.g., individually or by entire ecosystems?
o Where should we move species to, e.g. how far northwards?
o When should we move species, e.g., now or when a population is in decline?

Ethical Issues and Questions:
· Which species should we save, if we can’t save them all?
· Does taking no action break an ethical responsibility to act?
· Does moving species outside their native range in effect create ‘exotic’ species?
· Much of conservation biology is founded on a “love of place”, e.g. Aldo Leopold’s land ethic. How do we reconcile this with climate change and the potential for species and ecosystem shifts, assisted or otherwise?

Legal Issues and Questions:
· How do we best handle distinctions among different classes of ‘invasive species’, i.e. between species moved for conservation purposes versus those traditionally considered to be exotic? To what extent do we need to develop a legal framework for this?
· How should existing national legislation, e.g., the Endangered Species Act or the National Invasive Species Act in the USA, as well as local, state or international law guide policy?
· What new legislation is needed to create effective policy?
· What legal liabilities are incurred by moving populations of a species to a new location?

Economic Issues and Questions:
· How much will it cost to perform assisted migration? This question comprises both the direct costs of physically transporting and establishing individuals and propagules, and the indirect economic and ecological costs associated with transplanted populations.
· How do we balance these costs of assisted migration against the costs of inactivity?

The list above is not exhaustive, yet it illustrates the complexity of this issue and the difficulty in evaluating the merits of this new strategy. Assisted migration is not likely to serve as the preeminent solution to climate-driven extinction risk, but instead could serve as an important component of the suite of strategies used to conserve biodiversity. Currently existing strategies, such as attempts to reduce greenhouse gas emissions and the development of networks of corridors and reserves, should be continued.

A thorough evaluation of assisted migration challenges the basic language and conceptual framework of existing conservation policy, which has been based on a largely static conceptualization of species and ecosystems. In such a view, species are either ‘native’ or ‘exotic’; a primary job of land managers is to protect the species belonging to their managed ecosystems and keep out other species; and networks of reserves are built to conserve particular regions. But this static framework is likely to be both conceptually and practically inadequate for conservation solutions to 21^st-century climate change. We must build conservation networks with the capacity to continually assess the viability of populations within and among reserves and to facilitate, either passively or actively, the geographic responses of species to climate change. We must also recognize, that in a changing world, not all populations can be locally saved from climate-driven extinction, but rather devote resources to ensuring that losses are balanced by the establishment of new populations elsewhere.

Clearly, biogeographers have a critical role to play in the discussion and possible implementation of assisted migration. Without a program of assisted migration some species will go extinct and existing genetic diversity will be lost, but without additional information it is hard to estimate how great these losses will be. Much information is needed to help evaluate this newly proposed strategy. We hope that this brief editorial will help to stimulate conversations, written responses, compilation of a more complete list of issues to consider, a holistic evaluation of assisted migration, and eventually to the suite of conservation strategies needed to preserve biological diversity in the 21^st century and beyond.

¹Dov F. Sax and ²John W. Williams

1 Department of Ecology and Evolutionary Biology, Brown University, Providence, RI 02912
2 Department of Geography, University of Wisconsin, Madison, WI 53706

Literature Cited:

McLachlan, J. S., J. J. Hellmann, and M. W. Schwartz. 2007. A framework for assisted migration in an era of climate change. Conservation Biology 21: 297-302

A version of this article appears in the Summer 2007 issue of the IBS Newsletter.

Geophylogenies – Uniting space and time

Graphic images designed to interrelate evolutionary models and geography have been important in the development and illustration of evolutionary concepts and hypotheses (Hewitt 2001). Images have been particularly important in phylogeography (Avise et al. 1987, Avise 2000) and panbiogeography (Croizat 1958, Craw et al. 1999). The majority of images, with the exception of panbiogeography, have been cartographic in nature in that they are drawn with license with the specific purpose of depicting a particular aspect of the data rather than being directly rendered from the data itself.

Recently there has been move toward direct rendering of visualizations from data using geographical information systems (GIS) (Kidd & Ritchie 2006) and Google Earth™ (Janies et al. 2007).This change has been stimulated by ever increasing data volumes and complexity, the desire for quick and simple data exploration, and a growing interest in integrating evolutionary models with external geographical information to identify and quantify the geographical flow of lineages, selection, niche evolution and population connectivity for conservation planning (Kidd & Ritchie 2006, Storfer et al. 2007). Direct rendering of visualizations from data has the advantage of reflecting current database state, uniform presentation of high numbers of graphic elements and flexible editing; however it may sometimes be difficult to create clear images, e.g. in areas of high data density, as graphical license is restricted.

‘Geophylogenies’ are phylogenetic models transformed into spatial networks through the application of a biogeographical model (Kidd & Liu in press). Geographical coordinates are associated with the nodes and links of the phylogenetic tree; observed tip nodes are associated with coordinates defining where the entity (genotype or species) is observed while internal nodes and branch paths are inferred from a biogeographical model. The simplest biogeographical model is to place inferred nodes at the spatial centroid of observations of the subclade it defines. Alternative historical models could be derived from ecological niche models (Guisan & Zimmerman 2000) or historical biogeographical approaches, e.g DIVA (Ronquist 1997) or LaGrange (Ree et al. 2005).

Example 1: Evolution of the Artiodactyla in Space and Time.

My colleague Sam Price (NESCent) and I recently received third prize in a Visualizing Network Dynamics competition (http://vw.indiana.edu/07netsci/entries/) with a 2D visualization (Figure 1; and see http://vw.indiana.edu/07netsci/entries/#evolution for entire image).

Figure 1.- Geophylogeny of 174 extant species of Artiodactyla (even-toed hoofed mammals) with some ancestral nodes positioned on the basis of fossil evidence. Here the entire geophylogeny is displayed on a polar projection with arrows showing ‘flow’ from geophylogeny root to extant tip species. Red dots are the spatial centroid of extant taxa ranges. The light red dot is the root node (positioned from fossil evidence). Form here the group extensively radiated across the Eurasian and African continents with the exception of arctic and desert ecosystems. A fewer lineages crossed the Bearing strait to radiate in the Americas. Care should be taken interpreting this image as extinct species, e.g. North America camels are fully incorporated.

Example 2: H5N1 Bird Flu virus spread and evolution with Google Maps.

Janies et al.(2007) provide an excellent example using Google Earth™ to trace the global spread and evolution of H1N5 avian influenza. Google Earth™ (http://earth.google.com/) is a freely available platform-independent global desk mapping client with a user friendly interface. The geophylogeny can be displayed in its entirety or by year illuminating temporal change. Terminal nodes are symbolized to indicate organism host to which ‘description boxes’ are attached detaining key amino acid states, surface protein mutations, ancestral and sister nodes and the source of the data. Hyperlinks directly link to the corresponding GenBank record. Branches are colour coded to indicate genotype or host vector and also have linked description boxes detailing inferred mutational change along the branch. The model is downloadable from Systematic Biology online (aiTrees.kmz from http://systbio.org/?q=node/184).

Figure 2. H5N1 Bird Flu phylogeny with branches colour-coded to indicate dispersal vector overlaid onto population density.

Resources

For other examples and methodological details:

http://evoviz.org/GeoPhyloBuilder. Includes ‘Geophylobuilder – The Movie’ a short animated video of geophylogenies.

http://evoviz.org/GoogleEarth

http://iphylo.blogspot.com/2007/06/earth-not-flat-official.html

http://iphylo.blogspot.com/2007/06/google-earth-phylogenies.html

Creating geophylogenies:

GeoPhyloBuilder for ArcGIS. ARC Geodatabases, shapefiles and KML for Google Earth (needs Arc license), http://www.nescent.org/informatics/software.php

CIPRES Experimental Google Earth Phylogenetic Tree Server. Bill Piel’s (Yale) Internet service that builds geophylogenies in KML for display in Google Earth, http://www.treebase.org/getrees/

Pie Charts on Google Earth:

Phylogeoviz Yi-Hsin Erica Tsai’s (Duke University) Internet service that puts pie charts on Google Earth, http://www.phylogeoviz.org/

Workshop:

A ‘Visualizing Evolution in Space and Time’ workshop is planned for the 4^th International Biogeography Society Meeting, Mérida, Mexico, January 2009.

David Michael Kidd, National Evolutionary Synthesis Center (NESCent), Durham. North Carolina, USA.

References

Avise, J.C. (2000) Phylogeography Harvard University Press, Cambridge, Massachusetts.

Avise, J.C., Arnold, J., Ball, R.A., Bermingham, E., Lamb, T., Neigel, J.E., Reeb, C.A. & Saunders, N.C. (1987) Intraspecific phylogeography: the mitochondrial DNA bridge between population genetics and systematics. Annual Review of Ecology and Systematics, 18, 489-522.

Craw, R.C., Grehan, J.R. & Heads, M.J. (1999) Panbiogeography: Tracking the History of Life. Oxford University Press.

Croizat, L. (1958) Panbiogeography. Published by the Author, Caracas.

Guisan, A. & Zimmerman, N.E. (2000) Predictive habitat distribution modelling in ecology. Ecological Modelling, 135, 147-86.

Hewitt, G.M. (2001) Speciation, hybrid zones and phylogeography - or seeing genes in space and time. Molecular Ecology, 10, 537-49.

Janies, D., Hill, A.W., Guralnick, R., Habib, F., Waltari, E. & Wheeler, W.C. (2007). Genomic Analysis and Geographic Visualization of the Spread of Avian Influenza (H5N1). Systematic Biology, 56, 321 - 29.

Kidd, D.M. & Ritchie, M.G. (2006) Phylogeographic information systems; Putting the geography into phylogeography. Journal of Biogeography, 33, 1851-65.

Kidd, D.M. & Liu, X. (in press) GEOPHYLOBUILDER 1.0: an ArcGIS extension for creating 'geophylogenies'. Molecular Ecology Notes.

Ree, R., Moore, B.R., Webb, C.O. & Donoghue, M.J. (2005) A liklihood framework for inferring the evolution of geographic range on phlyogenetic trees. Evolution, 59(11), 2299-311.

Ronquist, F. (1997) Dispersal-vicariance analysis: a new approach to the quantification of historical biogeography. Systematic Biology, 46(1), 195-203.

Storfer, A., Murphy, M.A., Evans, J.S., Goldberg, C.S., Robinson, S., Spear, S.F., Dezzani, R., Delmelle, E., Vierling, L. & Waits, L.P. (2007) Putting the ‘landscape’ in landscape genetics. Heredity, 98(3), 128-42.

The biogeography mailing list

Dear Members of International Biogeography Society,

We are pleased to announce the creation of a biogeography listserv. We hope this will be a forum that will encourage communication and collaboration among biogeographers.

This list will be limited to active members of the International Biogeography Society and will be used to distribute information regarding biogeography. This may include occasional society announcements, job announcements, workshops, upcoming meetings, and other biogeography related topics that our members feel appropriate to post.

To subscribe to biogeography_L, please send the following message to:

listproc@nevada.edu

(Note: nothing in the "subject" line)

subscribe biogeography_L

We look forward to hearing from you,

IBS Board of Directors

Cheers,

Lois F. Alexander
Treasurer of the IBS

New SAM Version is now available!

Macroecologists and biogeographers now recognize that nearly all biodiversity data show strong spatial autocorrelation, driven by spatially structured environmental variation and/or by dispersal mechanisms. Although spatial autocorrelation analysis was introduced in the late 1970s (Sokal & Oden 1978a,b), only recently ecologists really started to pay attention to these issues (Legendre 1993, Diniz-Filho et al. 2003). That is why we started a project a few years ago, to design a new software for spatial analysis named SAM (Spatial Analysis in Macroecology). The idea was to create an integrated and user-friendly software package that could be easily used by researchers to analyze spatial data, as well as a platform to teach spatial analysis in undergraduate and graduate programs. The first version was released in September 2005 (Rangel et al. 2006a), and SAM recently achieved more than 2,500 users worldwide since this first release.

So far, more than 20 courses on spatial statistics were given by the authors, in more than 20 graduate courses and conferences, worldwide. Authors are available to give lectures on Spatial Statistics and SAM. SAM courses can be discussed under formal invitation of academic units, and are mainly directed to students in ecology, evolutionary biology, biogeography and macroecology. These courses are free of charge, although the SAM project does not include funding for such courses, so we require that travel and daily expenses be paid by those who are inviting us.

A new SAM version (2.0) has been now officially released (May 2007), after a first trial of tests during a SAM workshop held on January 9, 2007 in the 3rd Biannual Conference of the IBS in the Canary Islands (see Rangel et al. 2006b). The program is freely available at http://www.ecoevol.ufg.br/sam/ (permanent URL at http://purl.oclc.org/sam/). The new version is basically the result of the feedback from the hundreds of users around the world and will include important modifications regarding data input and output, and also a new module on K-means cluster analysis, which can be spatially constrained or not (Diniz-Filho & Bini 2005), and a number of updated features (Dutilleul 1993, Legendre et al. 2002, Griffith & Peres-Neto 2006). More importantly, SAM now integrates more directly to Geographic Information Systems, by allowing users to open and export data to ESRI® shapefiles.

Thus, SAM users have now all the tools needed to import both data on the distribution of species (e.g. available at http://www.natureserve.org/) and environmental variables (e.g. remote sensing data) that characterize the landscape of the domain of interest. Help file was also improved, becoming nearly a manual for spatial analysis. All these features make SAM a nearly complete platform to investigate patterns in biodiversity. Finally, SAM is growing fast, and new modules, such as Geographically Weighted Regression, Ripley's K, Path Analysis, Logistic Regression, are planned for the next version, to be released by the end of 2007 .

Thiago Fernando L. V. B. Rangel, Department of Ecology & Evolutionary Biology, University of Connecticut
José Alexandre Felizola Diniz-Filho and Luis Mauricio Bini, Departamento de Biologia Geral, ICB, Universidade Federal de Goiás

References
Diniz-Filho, J.A.F. & Bini, L.M. (2005) Modelling geographical patterns in species richness using eigenvector-based spatial filters. Global Ecology and Biogeography, 14, 177-185.
Diniz-Filho, J.A.F., Bini, L.M. & Hawkins, B.A. (2003) Spatial autocorrelation and red herrings in geographical ecology. Global Ecology and Biogeography, 12, 53-64.
Dutilleul, P. (1993) Modifying the t-test for assessing the correlation between 2 spatial processes. Biometrics, 49, 305-314.
Griffith, D. A. & Peres-Neto, P. R. (2006) Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses. Ecology, 87, 2603-2613.
Legendre, P. (1993) Spatial autocorrelation: trouble or new paradigm? Ecology, 74, 1659-1673.
Legendre, P., Dale, M.R.T., Fortin, M.J., Gurevitch, J., Hohn, M. & Myers, D. (2002) The consequences of spatial structure for the design and analysis of ecological field surveys. Ecography, 25, 601-615.
Rangel, T. F. L. V. B., Diniz-Filho, J. A. F. & Bini, L. M. (2006a) Towards an integrated computational tool for spatial analysis in macroecology and biogeography. Global Ecology and Biogeography, 15, 321-327.
Rangel, T.F.L.V.B., Diniz-Filho, J.A.F., & Bini, L.M. (2006) Spatial Analysis in Macroecology and Biogeography: News. IBS Newsletter, 4 (4). Available at http://www.biogeography.org/newsletter.htm.
Sokal, R. R. & Oden, N. L. (1978a) Spatial autocorrelation in biology. 1. Methodology. Biological Journal of Linnean Society, 10, 199-228.
Sokal, R. R. & Oden, N. L. (1978b) Spatial autocorrelation in biology. 2. Some biological implications and four applications of evolutionary and ecological interest. Biological Journal of Linnean Society, 10, 229-249.

Let’s blog

Dear fellow biogeographers,

Several IBS members proposed the creation of a web blog for the Society in the last meeting in the Canary Islands. A blog is defined as a ‘website where entries are written in chronological order and displayed in reverse chronological order’.

Blogs have become mainstream media tools for providing commentary and news on the Internet. In July 2007, blog search engine Technorati was tracking more than 73 million blogs and the number of people that reads blogs, every day, is much larger.

Surprisingly, few scientific societies have created blogs. However, if the aim is to promote a scientific discipline outside academia a good way to start is by creating a blog. Blogs are new and we are still learning how to use them effectively. So you are bound to see many changes as we go along.

I hope the IBS blog will help increasing communication among biogeographers and promote the discipline outside the walls of the academia.

If you are a member of the IBS, enthusiastic about the project and want to become a regular contributor to the blog, please let us know. Any ideas and suggestions are welcome.

We hope you see this project being yours as much as it is ours.

All the best,

Miguel B. Araújo
Vice President for Public Affairs and Communications of the IBS