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Macroecology & Conservation Unit cea.uevora.pt/umc

Macroecology & Conservation Unit www.cea.uevora.pt/umc. Research group that operates within the University of Évora, Portugal Former Laboratory of Biological Cartography Main area of research: Macroecology Main technical skills: GIS and statistics applied to ecology and conservation.

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Macroecology & Conservation Unit cea.uevora.pt/umc

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  1. Macroecology & Conservation Unit www.cea.uevora.pt/umc

  2. Research group that operates within the University of Évora, Portugal • Former Laboratory of Biological Cartography • Main area of research: Macroecology • Main technical skills: GIS and statisticsapplied to ecology and conservation

  3. Some of our research questions: • What factors govern the occurrence of species at different spatial scales? • What factors govern the occurrence of species at different temporal scales? • Where will species occur given projected environmental changes? • Where are the most important areas for biodiversity conservation?

  4. The GIS approach • Remote sensing • Field data (biological surveys and field validation) • Databases • Modelling

  5. The projects (1) SatTagis – a project on the left bank of the Tagus Estuary, a Nature Reserve just outside the city of Lisbon (3 million inhabitants). • We have built a time series of aerial photographs from 1958 up to 2000, and a series of satellite imagery from 1990 to 2001. • We have been comparing the efficiency of either methodology in studying land use changes over the study area.

  6. (1) SatTagis LandSat 5 TM 1985 Fotointerpretation of aerial photographs 1958

  7. (2) The Alqueva Dam Project • The Alqueva Dam was recently built in the South of Portugal. It just started flooding 25,000ha of land, causing a great impact on the landscape: the induced habitat reduction and fragmentation will greatly affect local flora and fauna species. • We have used GIS to integrate data from surveys of plants, macroinvertebrate, herptiles, birds and mammals, with environmental data, in order both to look out for endangered populations and to prioritise areas for conservation.

  8. (2) The Alqueva Dam Project: forecasting the flood

  9. (2) The Alqueva Dam Project: area selection for conservation

  10. (3) The Alqueva islands Some 100 islands will emerge within the reservoir: we have used GIS to model the islands-to-be at different water levels

  11. (4) The UNIBA Project • This is our main database, probably the most complete database on flora and fauna species of Southern Portugal (117,000 records so far). • It started has a project on its own, and it is now been fed by all other ongoing projects we have. • We plan to provide free access to some of the data online; we already establish protocols with other researchers/institutions that find UNIBA useful.

  12. (4) UNIBA

  13. (5) PortGap: statistics applied to conservation Field surveys are subjected to financial and time constrains: how far can we go in predicting species distribution and nature reserves location? In this project we compare the performance of sixmain techniques (General Linear Models, General Additive Models, Classification and Regression Trees, Artificial Neural Networks, Spatial Interpolators and Environmental Envelopes) to assess sp distribution and viability. Also we use complementary-based methods (e.g. Gap Analysis) to choose and prioritise conservation areas.

  14. Geomorphology (Slope) Climate (PCA – 1st axis) Landscape metrics (Number of patches) Human Density Environmental variables Observed occurrences Probabilities of occurrence

  15. (6) The Greenbelt Project • Ecological corridors are often crucial to maintain a nature conservation network healthy. • At the UMC we have been investigating the ecological corridors of Southern Portugal. • By joining the Greenbelt Project we consider connectivity at a broader scale, at an international level. Also we consider the need to translate complex research findings into units that make sense in conservation policies.

  16. (6) The Greenbelt Project, Southern Portugal Species sightings Species density Neighbourhood analysis Back to people

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