Introduction

Purpose

This field guide is designed primarily to enable participants in our citizen science venture to identify wildlife visiting residential compost piles in eastern Connecticut.  The goal of this experiment is to determine whether or not the addition of animal-based kitchen scraps really does affect wildlife visitation to compost piles.  Through citizen science, we are engaging the help of interested people to reach this goal by assisting with the identification of animals in web-based images.

How to Use This Field Guide

This field guide describes the 33 species of birds and mammals documented by wildlife monitoring cameras since the experiment’s start in 2008.  Images are captured when a warm, moving animal is detected by a camera’s infrared sensor aimed at the compost pile.  The guide portrays, both verbally and visually, the visitors to the piles.  An alphabetical menu lists the animals’ names in alphabetical order, while a taxonomic menu arranges related species together, as you would find in a typical field guide.  Both menus are divided by birds and mammals.

Read through this manual to become familiar with the diversity of potential visitors within the images that you will analyze.  Then consult it regularly when actually assessing images for the project’s database and when taking the qualify quiz beforehand.  For citizen scientist participants, click here for details regarding the image database and quiz.

Species Accounts

The field guide provides brief account of an animal’s appearance and its behavior at the compost piles, emphasizing the key characteristics for identification (highlighted typically in a pair of images).  Within a description, the size (body length including tail) of a species is based on measurements provided for birds by Poole (2005) and for mammals by Kays and Wilson (2009).  The species account then relates how regularly and when (both seasonally and day vs. night) a particular species has been encountered in our study.  Finally, for each species described, its account suggests similar species of compost visitors that have been documented in this study or that otherwise occur in the study area.  These are species with which the focal species might be confused, so be aware of how to draw distinctions among them.  A bibliography lists taxonomic guides useful for identifying the avian and mammalian fauna found at the study site.

Species Images

For a typical species, two series of images are presented, along with the initial pair of images.  The first series represents images in which the animal is very clearly depicted.   These “Well-Defined” images provide good views from a variety of angles (e.g., head on, from the side, tail end) and collectively furnish further illustration of the key features used in its identification.  Additionally, a second series, “Challenging Images,” provides views from which the animal’s identification is more difficult.  In many of the images from this study, the animal is not clearly depicted, but obscured.  It may be partially hidden behind the compost pile, moving out of the camera’s field of view, or concealed by a shadow.  For social visitors, such as crows, individuals in the foreground will sometimes block view of those in the background.  Furthermore, raindrops or ice on the camera lens and foggy conditions in general can lead to images that are hard to interpret.  Our current cameras use infrared illumination under low light conditions.  Thus, nocturnal visits will lead to grayscale rather than color images.  Identifications from these grayscale images can be tricky, since information on the animal’s coloration is not as readily available.   For the “Challenging Images,” corresponding links will provide both visual and written keys to help you interpret them.  However, push yourself by thoroughly viewing these “Challenging Images” before consulting the keys.  After all, you will not have a key when you examine the actual images, and many of those will be challenging to interpret; however, remember that you should consult this guide as you analyze your images.