Integrating occurrence data and expert maps for improved species range predictions

By Cory Merow, Adam M. Wilson, Walter Jetz. 2017

112 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/478f78ef8ed5e39b7d6f4f76f4e84f8ea5e5db40

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Florian Hartig
2. David J. Harris
3. Heike Lischke
4. Carsten F. Dormann
5. Matthias Schleuning
6. C. Kraan
7. Manuel J. Steinbauer
8. I. Kühn

In Ecology

1. Florian Hartig
2. David J. Harris
3. Heike Lischke
4. Carsten F. Dormann
5. Matthias Schleuning
6. C. Kraan
7. Manuel J. Steinbauer

In Nature and Landscape Conservation

1. Carsten F. Dormann
2. Florian Hartig
3. David J. Harris
4. Heike Lischke
5. Matthias Schleuning
6. C. Kraan
7. Manuel J. Steinbauer
8. I. Kühn

Citations in the corpus

• Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions (2018, background): “…in a BI-SDM with only one time-step could be achieved by masking unreachable habitat, down-weighting probabilities with the distance to expert-knowledge maps or by including dispersal barriers as additional predictors for each species (Gilman et al., 2010; Merow, Wilson, & Jetz, 2017).”
• Data Integration for Large-Scale Models of Species Distributions. (2020, unknown): “The real power of data integration, however, becomes apparent when linking datasets where the observationmodels are too dissimilar to permit simple data pooling without losing substantial information (Figure 1), for example, using expert-drawn range maps [69,70].”