A better conservation tool creates better conservation results
"It's gratifying to see a decade's worth of my work uploaded and available for public consumption. The Data Basin application fills a much needed role in the conservation world."
Pierre Iachetti
Research Scientist with University of Victoria, Energy Systems & Sustainable Cities Group, Civil Engineering Department
"I would recommend Data Basin to anyone involved with large natural resource data management systems."
Karl Ford
Project Manager with BLM
"Data Basin is an ideal way for researchers to share their conservation maps and information with the wider conservation community."
Gillian Woolmer
Assistant Director with WCS Canada

Support the Data Basin mission

Data Basin supports people making a positive difference for the well-being of people and nature. Our members build effective solutions to environmental challenges by having better access to credible data, expert social networks, and decision-support tools. Data Basin enables you to explore, visualize, and use quality scientific data and information to better understand issues relevant to you and your community.

Making a difference requires your support. If every one of the 34000+ members of Data Basin donated just $10, we would be able to do what so many of you have asked us to do:

  • build new tools such as enhanced visualization and graphing & analytical tools
  • upload new datasets and update current datasets
  • maintain core system functions
  • provide more training and workshop opportunities

We encourage you to make a one-time donation or become an on-going sponsor. The Conservation Biology Institute (CBI) is a 501(c)(3) organization. All gifts are tax deductible. You can be confident your donations to CBI will be spent in support of our mission. Please feel free to contact us with any questions.

 Donate through PayPal

Our mission in action…

Mediterranean Ecosystems
Where are the areas most at risk from climate change?
Since climate change has become an important issue to be addressed by all agencies and conservation entities, Molly Cross from Wildlife Conservation Society and a group of her colleagues have developped a straightforward framework to address climate change issues in conservation planning (Cross et al. submitted). As a first critical step, a “feature of interest or concern” (species, ecosystem or its function, area) is chosen to start considering the climate change challenges. Klausmeyer and Shaw (2009) chose Mediterranean Ecosystems as a feature of interest and concern because of their striking plant diversity and their correlation with a unique climate.They note that Mediterranean Ecosystems represent “2% of our planet’s land area containing 20% of the known vascular plant diversity with the second lowest level of land protection of all terrestrial biomes”.
Once the “feature” has been identified, a management objective has to be clearly delineated to be able to evaluate when the objective has been met. In this example, Klausmeyer and Shaw (2009)’s objective was to identify which Mediterranean regions of the world needed the most immediate conservation action i.e. a prioritized list of where should new protected areas and connectivity pathways be established.
The Sierra Club has a catchy phrase for recommended action for conservation: protect the best, remove the stress, restore the rest. In the case of the Mediterranean systems, the first order of business was to find out where “the best” was located. Following Cross et al. (submitted)’s approach, the third step after identifying a feature and defining a practical management objective was to put together a conceptual model for the system of interest. Klausmeyer and Shaw (2009) defined the Mediterranean climate extent using climate indices defined earlier by Aschmann (1973). They then analyzed 136 projections of future climate from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset (Meehl et al. 2007). They came up with a map of the projected area of Mediterranean climate extent in the future with various levels of confidence with regard to their regional expansion or contraction. One of the areas with the most projected change, was identified as the west coast of Australia where the climate is projected to remain characteristic of Mediterranean lands in only 10% of the existing protected areas while 17% of the current Mediterranean climate will definitely shift to a brand new state.
The third step in Cross et al.’s framework is to identify intervention points and management actions. In this as in all other cases, slowing the rate of climate change by reducing the amount of greenhouse gasses in the atmosphere would give all species more time to adapt to change. Klausmeyer and Shaw also identified specific local actions that can be done to help species to adapt to climate change in areas most at risk, namely western Australia. Conservationists in this area should be encouraged to establish new protected areas, consider farmland areas for restoration, and modify current land management practices to minimize the future impacts of warming.
The final three steps in the Cross et al.'s framework involve evaluating the feasibility of suggested actions, prioritizing and implementing, and monitoring the effectiveness of the actions. These steps are best done at the local scale, so they were not covered in the Klausmeyer and Shaw analysis. The evaluation step should engage landowners, provincial and national government representatives, conservation organizations, and farmers, to agree on a feasible plan of action. The implementation phase will require significant funding and possibly policy change in order to be effective. Once the plan gets implemented it is also essential to revisit the plan as new data are collected and the site is closely monitored to evaluate the plan efficacy.
Co-author: Kirk Klausmeyer

Klausmeyer K.R. and M.R. Shaw (2009) Climate Change, Habitat Loss, Protected Areas and the Climate Adaptation Potential of Species in Mediterranean Ecosystems Worldwide. PLoS ONE 4(7): e6392. doi:10.1371/journal.pone.0006392

Photo credit: Dominique Bachelet (Conservation Biology Institute)
IDB - Environmental Safeguards Group
This group was created to support IDB ability to assess the potential impacts of proposed development projects to Critical Natural Habitats and Natural Habitats as defined under Section B.9 of the IDB Environment and Safeguards Policy.  The NGO Working Group that originally collaborated with IDB to develop this site includes Birdlife International, Conservation International, NatureServe, The Nature Conservancy, UNEP-WCMC, and World Wildlife Fund.

Pacific Northwest
Climate change impacts on vegetation

A new assessment of the potential impact of climate change on vegetation in the Pacific Northwest of the USA shows a mosaic of vulnerable and resilient areas.  Researchers found that coastal forests are vulnerable to large increases in fires, subsequent losses in carbon stocks, and encroachment from more southerly and/or easterly forest types.  The dry, fire-adapted forests east of the Cascades are projected to be more resilient to climate change. With projected increases in precipitation, vast expanses of shrublands in the Columbia Plateau and Northern Basin could convert to grasslands or woodlands.

Due to a limited number of field experiments (FACE or free-air CO2 enrichment), we don’t know how every plant species might respond to changes. As a result, models cannot be calibrated precisely for current vegetation cover.  To try to alleviate some of the problems associated with the diversity of species-specific responses, climate scientists use dynamic global vegetation models where plant functional types (such as maritime evergreen forests) rather than species are used to simulate vegetation assemblages and the associated ecosystem processes.

The dynamic global vegetation model MC1 was used to simulate vegetation dynamics, associated carbon and nitrogen cycles, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington. The model used historical climate data from the PRISM group (Chris Daly, OSU) at a 30arc second (~800m) spatial grain and anomalies from 9 future climate projections.  The vegetation model only simulates potential natural vegetation and does not simulate the impacts of urbanization, agriculture, or industrial development.

The model was run on a monthly time step from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below a minimum threshold. Regional differences in nitrogen deposition were not taken into account.  Future climate change scenarios were generated through statistical downscaling i.e. taking information produced at large scale and interpreting it at finer scale, of general circulation or global climate models (GCM) results. Anomalies (difference between historical simulations and future projections) were created to modify the climatology (long term average historical climate packaged as one year’s average conditions) produced by the PRISM group from a large set of observations at 30arc second spatial grain (~800m).
The three GCMs used were the CSIRO Mk3 (from Australia), MIROC 3.2 medres (from Japan, and Hadley CM 3 (from UK) (Table 8.1 in IPCC report Vol 1.), each run using three different CO2-equivalent emission scenarios):

  • B1 (declining population by 2050, social stability and reliance on clean and resource efficient technologies)
  • A1B (declining population by 2050, social interactions globally, and reliance on both traditional and renewable sources of energy)
  • A2 (increasing population, self reliant nations, and fragmented technological changes).

Temperatures are projected to increase throughout the region following the projected increase in CO2-eq emissions, but precipitation projections are more varied. For example:

  • CSIRO projections are relatively cool and wet
  • MIROC projections are hot and wet
  • Hadley projections are hot and dry.

Precipitation trends show a general increase in winter and a decrease in summer  while highest temperature increases are projected for summer. Previous published work showed that CSIRO performed poorly, MIROC moderately well, and Hadley very well in the Pacific Northwest for the historical period.

Major outcomes of this modeling exercise include:

  • The Pacific Northwest’s coastal forests are vulnerable to large increases in fires, corresponding losses in carbon stocks, and encroachment from either more southerly and/or easterly forest types.
  • The dry fire-adapted forests located east of the Cascades are projected to be fairly resilient to climate change.
  • With increasing precipitation, the model simulates vast expanses of shrublands in the Columbia Plateau and Northern Basin converting to either grasslands or woodlands.
  • Results for the CSIRO climate projections include an 82% increase in biomass burned and 1.2% (0.1 Pg C) decrease in carbon stocks for the region. For MIROC climate projections, projections show a 22% increase in biomass burned and 0.8% (0.07 Pg C) increase in carbon stocks.
  • Climate projections from the Hadley model cause the most extreme changes, with almost a 3 fold increase in biomass burned and 15% (1.26 Pg C) decrease in carbon stocks.

Model results are of course simplification of the real world and entirely dependent on model assumptions and uncertainties which come from 1) climatic inputs and particularly precipitation projections, 2) unknown plant species responses to elevated CO2, 3) future levels of emissions and subsequent nitrogen deposition, 4) ill-understood responses of belowground components of ecosystems.

The CO2 fertilization effect in the model increased productivity and water use efficiency as atmospheric CO2 concentration increased. Recent publications (Mote et. al 2008) have shown that despite early results in the field (FACE or free-air CO2 enrichment) showing an enhancement of productivity and water use efficiency, some plants have acclimated and showed a lesser response to CO2 than at the beginning of the experiment. Moreover, the larger impacts occurred belowground (increased root turnover, increased belowground productivity).  There is also evidence that nutrient availability constrains the long term response to increased atmospheric CO2. Consequently it is likely that this version of MC1 may have overestimated the positive effects of CO2 on plant growth in the future.

This work was the core of Brendan Rogers Master’s thesis under Dr. Ron Neilson, his advisor and MAPSS team leader, USDA Forest Service PNW station, in the Dept of Forest Ecosystem and Society, at Oregon State University where he defended in the Fall of 2009.


Bachelet, D., R. P. Neilson, J. M. Lenihan, and R. J. Drapek. 2001. Climate change effects on vegetation distribution and carbon budget in the United States. Ecosystems 4, no. 3 (April 21): 164-185. doi:10.1007/s10021-001-0002-7.

Daly, C., M. Halbleib, J. I. Smith, W. P. Gibson, M. K. Doggett, G. H. Taylor, J. Curtis, P. P. Pasteris, and N. USDA. 2008. Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States.
Gordon HB et al. (2002). The CSIRO Mk3 Climate System Model Aspendale: CSIRO Atmospheric Research. CSIRO Atm. Res. tech. paper no. 60.

Hasumi, H., and S. Emori, eds. 2004. K-1 Coupled GCM (MIROC) description. K-1 Model Developers Tech. rep. 1, 34 pp.

IPCC (2007).  Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment. Report of the Intergovernmental Panel on Climate Change, Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K 280 .B. Averyt, M. Tignor and H.L. Miller (eds.). Cambridge University Press, Cambridge, UK and New York, NY, USA.

Johns, T. C., J. M. Gregory, W. J. Ingram, C. E. Johnson, A. Jones, J. A. Lowe, J. F. B. Mitchell, D. L. Roberts, D. M. H. Sexton, and D. S. Stevenson. 2003. Anthropogenic climate change for 1860 to 2100 simulated with the HadCM3 model under updated emissions scenarios. Climate Dynamics 20, no. 6: 583-612.

Kuchler, A. 1975. Potential Natural Vegetation of the United States. 2nd edition. New York, NY: American Geographic Society.Nakicenovic, N., J. Alcamo, G. Davis, B. de Vries, J. Fenhann, S. Gaffin, K. Gregory, A. Grubler, T. Y. Jung, and T. Kram. 2000. Special report on emissions scenarios: a special report of Working Group III of the Intergovernmental Panel on Climate Change. PNNL-SA-39650, Cambridge University Press, New York, NY (US).

Mote, P., E. Salathe, V. Duliere, and E. Jump. 2008. Scenarios of Future Climate for the Pacific Northwest. Seattle, WA: Climate Impacts Group, University of Washington.

Norby, R. J., J. M. Warren, C. M. Iversen, B. E. Medlyn, R. E. McMurtrie, and F. M. Hoffman. 2008. Nitrogen limitation is reducing the enhancement of NPP by elevated CO2 in a deciduous forest. EOS Trans. AGU 89, no. 53. Fall Meet. Suppl., Abstract B32B-05.

Rogers, B. 2009. Potential impacts of climate change on vegetation distributions, carbon stocks, and fire regimes in the U.S. Pacific Northwest. MS Thesis, Oregon State University.

Salathe Jr, E. P., P. W. Mote, and M. W. Wiley. 2007. Review of scenario selection and downscaling methods for the assessment of climate change impacts on hydrology in the United States Pacific Northwest. International Journal of Climatology 27, no. 12.

Photo credits:  Dr. Dominique Bachelet...