• Alaska Soil Map Units

      Zabihi, Khodabakhsh; Huettmann, Falk; Young, Brian (2017)
      The shapefile includes vector polygons of Alaska soil map units. The geographic projection was set at NAD 1983 Alaska Albers.
    • Application of environmental DNA-based occurrence data in modeling wood frog (Rana sylvatica) distribution in Interior Alaska

      Spangler, Mark A.; López, J. Andrés; Huettmann, Falk (2017)
      Knowledge of wood frog distribution in Alaska is incomplete due to insufficient baseline occurrence data. A short season of activity and difficult access to remote areas restrict implementation of consistent monitoring efforts. Detecting the presence of species in aquatic landscapes using environmental DNA (eDNA) assays is increasingly applied as a monitoring method in wildlife surveys. However, uncertainties regarding the technique’s sensitivity to environmental variables and human error have thus far prevented its widespread adoption in studies of species distribution. Predictive models built on machine learning algorithms can help provide precise descriptions of species distribution using eDNA occurrence data, but they will require ground-truthing efforts to confirm accuracy in under-sampled landscapes. Here we assess the ability of wood frog eDNA occurrence data to inform species distribution models under five criteria for data use. We sampled 60 wetlands for eDNA in the Fairbanks North Star Borough during summer 2015. Samples were processed using a species-specific quantitative PCR assay. Wood frog presence at each site was inferred from the PCR results. This data was used to construct four different wood frog distribution models. From each model we produced a predictive distribution map encompassing the Fairbanks North Star Borough. We assess the performance of each model using available wood frog presence data. Our highest performing model achieves moderate predictive accuracy (Area Under the Curve = 0.74). Weak signals in eDNA occurrence data are important in revealing species presence at low abundance, but strict lab hygiene, quality control practices, and detailed metadata are needed to retain confidence in the results. We show a powerful new way to study wood frog distribution by combining eDNA occurrence data with machine learning techniques. Wider implementation of eDNA surveys and increased availability of high resolution GIS data will help to refine these models.
    • Binary Map (Figure 6)

      Zabihi, Khodabakhsh; Huettmann, Falk; Young, Brian (2020)
      Classified prediction map of multi-species bark beetle occurrence using 95% confidence interval of assessment/test points to differentiate predicted index of relative occurrence (RIO) of the ecological model. Value 1 (presence) represents the favorable habitats and value 0 (absence) represents regions that may not be occupied by scolytines community based on the current climatic conditions and biophysical attributes of the landscape. The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
    • Birding Data for Costa Rica

      Huettmann, Falk (2009)
      These data describe 703 species with geo-referencing information (latitude longitude) for 42 locations in Costa Rica. They are taken from the species lists presented in B. Lawson (2009; A bird-finding guide to Costa Rica. Comstock Publishing Associates and Cornell University Press. ISBN 978-0-8014-7584-9). This database is based on extensive fieldwork by B. Lawson and as described in his book. Here, these extensive species list data got geo-referenced via Google Maps. The resulting database described here consist of 4,829 rows and 8 columns (Page No,Site No,Site Name, latitude, longitude, SpeciesNo,SpeciestoExpect,Source) and is 969KB in size. The following locations were sampled: Arenal Volcano National Park, Bosque de Paz Biological Reserve and Lodge, Bosque del Rio Tigre, Braulio Carrillo National Park, Cabo Blanco Absolute Nature Reserve, Cano Negro National Refuge, Carara National Park, Cerro de la Muerte, Diria National Park, El Copal Biological Reserve, El Rodeo (University for Peace), Esquinas Rainforest Lodge, Irazu Volcano National Park, Kekoldi Hawk Watch, Km 70 (route 2), La Ensenada Wildlife Refuge, La Paz Waterfal Gardens, La Selva Biological Station, Laguna del Lagarto Lodge, Lankester Gardens, Las Alturas, Las Cruces Biological Station, Las Heliconias Lodge, Manuel Antonio National Park, Marenco Beach and Rainforest Lodge, Monteverde Cloud Forest Reserve, Oro Verde Biological Reserve, Palo Verede National Park, Poas Volcano National Park, Rancho Naturalista, Rara Avis Rainforest Lodge, Rincon de la Vieja National Park, Rio Negro, San Gerardo de Dota, Santa Rosa National Park, Selva Bananito Lodge, Talari Mountain Lodge, Tapanti National Park, The Coastline, The University of Costa Rica, Tortuguero National Park, Virgen del Socorro.
    • CAFI Regeneration 2014

      2014
      CAFI Regeneration Updated December 2014
    • CAFI Site Description 2014

      2014
      CAFI Site Description Updated December 2014
    • CAFI Tree Inventory 1 2014

      2014
      CAFI Tree Inventory 1 Updated December 2014
    • CAFI Tree Inventory 2 2014

      2014
      CAFI Tree Inventory 2 Updated December 2014
    • CAFI Tree Inventory 3 2014

      2014
      CAFI Tree Inventory 3 Updated December 2014
    • CAFI Tree Inventory 5 2014

      2014
      CAFI Tree Inventory 5 Updated December 2014
    • CAFI Tree Inventory4 2014

      2014
      CAFI Tree Inventory 4 Updated December 2014