index.Rmd

--- 
knit: "bookdown::render_book"
title: "Source code and supplementary material for _Using citizen science to parse climatic and landcover influences on bird occupancy within a tropical biodiversity hotspot_"
author: 
     - Vijay Ramesh
     - Pratik R. Gupte
     - Morgan W. Tingley
     - VV Robin
     - Ruth DeFries
date: "`r Sys.Date()`"
site: bookdown::bookdown_site
output: 
  bookdown::gitbook:
    fig_caption: yes
  bookdown::pdf_document2:
    documentclass: scrreprt
    toc-depth: 1
    secnumdepth: 2
    geometry: "left=4cm, right=3cm, top=2.5cm, bottom=2.5cm"
bibliography: [references_ebird.bib]
biblio-style: apalike
link-citations: yes
github-repo: vjjan91/eBirdOccupancy
---

# Introduction

This is the readable version containing analysis that models associations between environmental predictors (climate and landcover) and citizen science observations of birds across the Nilgiri and Anamalai Hills of the Western Ghats Biodiversity hotspot.   

Methods and format are derived from https://cornelllabofornithology.github.io/ebird-best-practices/.

## Data processing

The data processing for this project is described in the following sections. Navigate through them using the links in the sidebar.

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![**The Nilgiri and Anamalai Hills in southern India provide a convenient geography for studying the interplay of land cover and climate on the distributions of bird species.**
(a) The Nilgiri and Anamalai Hills of the Southern Western Ghats are topographically complex, with maximum elevations > 2,000 m, and are separated by the very low-lying Palghat Gap, which serves as a natural barrier to the dispersal of many hill birds. (b) Lower elevations are primarily covered by agriculture and settlements, reflecting the intense human pressure on this region, while mid- and higher elevations show a mix of natural and human-modified land cover types (see Fig. 2 for details). (c) The coastal edge of the area, and the windward hill slopes show limited temperature seasonality across the December – May period; this seasonality increases with distance from the coast but is lower at higher elevations inland. (d) Higher elevations also show limited precipitation seasonality than both low-lying coastal and inland regions. Our study area (bounds shown as dashed lines) includes multiple combinations of elevation, land cover type, and temperature and rainfall seasonality, resulting in a naturally occurring crossed-factorial design that allows us to study the effects of climate and land cover on bird occupancy. Representative forest-restricted and habitat-generalist birds from the study area are shown between panels (all images were obtained from Wikimedia commons and credit is assigned for each species in brackets); From L to R: (1) Malabar grey hornbill (by Koshy), (2) Crimson-backed sunbird (by Mandar Godbole), (3) Asian emerald dove (by Selvaganesh), (4) Black-and-orange flycatcher (by LKanth), (5) Grey-headed canary flycatcher (by David Raju), (6) Greater-racket tailed drongo (by MD Shahanshah Bappy), (7) Eurasian hoopoe (by Zeynel cebeci), (8) Chestnut-headed bee-eater (by MikeBirds), (9) Coppersmith barbet (by Raju Kasambe), (10) Red-vented bulbul (by TR Shankar Raman), (11) Pied bushchat (by TR Shankar Raman), (12) Ashy prinia (by Rison Thumboor). Elevation is from 30 m resolution SRTM data (Farr et al. 2007), land cover, at 1 km resolution, is reclassified from Roy et al. (2015), while climatic variation is represented by CHELSA seasonality layers (temperature: BIOCLIM 4a, rainfall: BIOCLIM 15), at 1km resolution (Karger et al. 2017). All layers were resampled to 1 km resolution for analyses.](figs/fig_01.png)