# Reading

# Favorite Papers and Books

Below is a short list of my favorite scientific papers and books on science.

## Papers on Species Distribution Modeling / Habitat Suitability Modeling

#### A statistical explanation of Maxent for ecologists, by Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudı´k, Yung En Chee and Colin J. Yates

This is an excellent description of how Maxent works and how it can be applied to species distribution/habitat suitability modeling. Like many papers, they do not talk about field data uncertainty and how Maxent will, by default, typically fit the model to the data much tighter than expected from theory (over-fitting).

While this sounds like a really fun paper (and it is), it is also a well executed species distribution modeling paper.

## GIS Books

#### Geographic Information Systems and Science by Paul A. Longley, Mike Goodchild, David J. Maguire and David W. Rhind

This is an excellent introduction to GIS. The book contains an overview of GIS concepts and applications and is applicable to any of the general GIS software packages. The book contains information on projections, datums, file formats, data sets, some cartography, and beginning of GIS analysis.

#### Introduction to Geographic Information Systems with Data Set CD-ROM by Kang-Tsung Chang

This is a more concise introduction than Longley's that also introduces the reader to network analysis and geospatial statistics. The book contains no color illustrations and goes into more of the mathematics behind GIS.

#### GIS Tutorial 1, 2, and 3, from Esri

These are a series of books to introduce readers to GIS with the ArcGIS line of products. The books are excellent step-by-step manuals especially for those that struggle with GIS or are learning outside of a classroom. You'll want to skip the chapters that are about features you are not interested in and you may want to check them out of a library or borrow a copy as you will probably only work through them once.

## Statistics Books

#### An Introduction to R

This is a very concise introduction to R.

#### Generalized Additive Models: An Introduction with R by Simon N. Wood

A great book for learning and reference on GAMs in R.

## Books on Modeling / Spatial Modeling

#### GIS, Spatial Analysis, and Modeling by David J. Maguire, Michael Batty, and Michael F. Goodchild, editors.

The introduction to this book is one of the best overviews of spatial modeling I have seen. The remaining chapters deal with topic-specific areas and may or may not be interesting to the reader.

#### Mapping Species Distributions: Spatial Inference and Prediction (Ecology, Biodiversity and Conservation) by Janet Franklin

This is an excellent introduction into Species Distribution / Habitat Probability modeling with an overview of many of the modeling approaches used. The book does not go into detail on issues of over fitting or representation of error from field data.

#### Principles of Modeling Uncertainties in Spatial Data and Spatial Analysis by Wenzhong Shi

One of the few books dedicated to modeling uncertainty in spatial data. A must read for those serious about spatial modeling and analysis.

#### Model Based Inference in the Life Sciences: A Primer on Evidence by David Anderson

This is an excellent book on the foundations of modeling.

## Science Books

#### Ideas and Opinions, Albert Einstein

A collection of writings over a range of topics. Very accessible for non-physicists and just as germane to today's issues as in Einstein's time.

#### Guns, Germs, and Steel, by Jared Diamond

Great book on how human society developed over the last 10,000 years. Focuses on how human technology and diseases helped create the distribution of cultures and countries we see today. While the author appears relatively unbiased, it is difficult at times to tell where the science ends and his opinion comes in.

#### The Structure of Scientific Revolutions, by Thomas Kuhn

A foundational work on modern science and a must read for any researcher.