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Janet Franklin

Researcher at University of California, Riverside

Publications -  246
Citations -  15490

Janet Franklin is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Vegetation & Species distribution. The author has an hindex of 53, co-authored 232 publications receiving 13361 citations. Previous affiliations of Janet Franklin include University of California, Santa Barbara & Sonoma State University.

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Book

Mapping Species Distributions: Spatial Inference and Prediction

TL;DR: This chapter discusses the history and Ecological Basis of Species' Distribution Modeling, and the design and implementation of species' distribution models.
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Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients:

TL;DR: Predictive vegetation mapping as discussed by the authors is defined as predicting the geographic distribution of the vegetation composition across a landscape from mapped environmental variables, which is made possible by the availability of digital maps of topography and other environmental variables such as soils, geology and climate variables.
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Plant diversity patterns in neotropical dry forests and their conservation implications

Dryflor, +67 more
- 23 Sep 2016 - 
TL;DR: Using 835 inventories covering 4660 species of woody plants, marked floristic turnover among inventories and regions indicates that numerous conservation areas across many countries will be needed to protect the full diversity of tropical dry forests.
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Predictive soil mapping: A review

TL;DR: Predictive soil mapping (PSM) can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic data base to create a predictive map.
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Moving beyond static species distribution models in support of conservation biogeography

TL;DR: In this article, the authors combine static species distribution models (SDM), predicting the geographical pattern of suitable habitat, with dynamic landscape and population models to forecast the impacts of environmental change on species status, an important goal of conservation biogeography.