Search datasets
Taxonomic Group
- (-) Remove (none) filter (none)
- Amphibians / Reptiles (1) Apply Amphibians / Reptiles filter
- Birds (1) Apply Birds filter
- Fishes (1) Apply Fishes filter
- (-) Remove Herbaceous plants filter Herbaceous plants
- Invertebrates (4) Apply Invertebrates filter
- Mammals (1) Apply Mammals filter
- Microbes (1) Apply Microbes filter
- (-) Remove Woody Plants filter Woody Plants
Biome
- Boreal Forest (2) Apply Boreal Forest filter
- Desert (3) Apply Desert filter
- Freshwater (3) Apply Freshwater filter
- (-) Remove Marine filter Marine
- (-) Remove Mediterranean / Chaparral filter Mediterranean / Chaparral
- Temperate Forest (5) Apply Temperate Forest filter
- Temperate Grassland (9) Apply Temperate Grassland filter
- (-) Remove Tropical Forest filter Tropical Forest
- Tundra (2) Apply Tundra filter
Data Type
Ecological Level
- (-) Remove (none) filter (none)
- (-) Remove Community filter Community
- (-) Remove Ecosystem filter Ecosystem
- (-) Remove Population filter Population
- Species (3) Apply Species filter
Scale (extent)
Displaying 1 - 3 of 3
This dataset follows a lowland tropical rain forest for 17 years in Costa Rica. Dataset Location: Ecological Archives (1983-1993) , Ecological Archives Update (1993-2000) Site Location: La Selva Biological Station, Costa Rica (10 o 26' N, 83 o 59' W) Sites Georefferenced: Yes Timespan: 1983 - 2000 Sampling Frequency: annually...MORE
This web site hosts data from the Georgia Coastal Ecosystems Long Term Ecological Research station on the Altamhaha, Doboy, and Sapelo Sounds. Dataset Location: http://gce-lter.marsci.uga.edu/public/app/data_catalog.asp Site Location: Altamhaha, Doboy, and Sapelo Sounds; coast of Georgia, U.S.A. Datasets Available: THEMES - algal productivity; aquatic invertebrate ecology; bacterial productivity; general nutrient chemistry;...MORE
Via NEON's overview page: Data will be collected from 106 sites (60 terrestrial, 36 aquatic and 10 aquatic experimental) across the U.S. (including Alaska, Hawaii and Puerto Rico) using instrument measurements and field sampling. NEON will combine site-based data with remotely sensed data and existing continental-scale data sets (e.g. satellite...MORE