From 94844804a0a7d26ca4cfa8c75c531850cd728cb8 Mon Sep 17 00:00:00 2001
From: Bruna Amaral <74007922+br-amaral@users.noreply.github.com>
Date: Fri, 8 Mar 2024 14:22:22 -0500
Subject: [PATCH] Update index.html

type, remove 1. in the beginning of the abstract
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@@ -91,7 +91,7 @@ <h1>Overcoming data gaps using integrated models to estimate migratory species
 	      <strong>Citation</strong> - <a href="https://github.com/farrmt">Farr M.T.</a>, <a href="https://github.com/ezylstra">Zylstra, E.R.</a>, Ries, L., and <a href="https://github.com/ezipkin">Zipkin E.F.</a> (2024) Overcoming data gaps using integrated models to estimate migratory species’ dynamics during cryptic periods of the annual cycle. <em>Methods in Ecology and Evolution</em>. <a href=https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.14282>DOI: 10.1111/2041-210X.14282</a>
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-	<strong>Abstract</strong> - 1.	Environmental and anthropogenic factors affect the population dynamics of migratory species throughout their annual cycles. However, identifying the spatiotemporal drivers of migratory species' abundances is difficult because of extensive gaps in monitoring data. To estimate population abundance and distribution at broad spatiotemporal extents, we developed an integrated model that incorporates unstructured data during time periods and spatial locations when structured data are unavailable. Data for widespread and migratory species are often fragmented across multiple monitoring programs. Our integrated model can estimate population abundance at broad spatiotemporal extents despite structured data gaps during the annual cycle by leveraging opportunistic data.
+	<strong>Abstract</strong> - Environmental and anthropogenic factors affect the population dynamics of migratory species throughout their annual cycles. However, identifying the spatiotemporal drivers of migratory species' abundances is difficult because of extensive gaps in monitoring data. To estimate population abundance and distribution at broad spatiotemporal extents, we developed an integrated model that incorporates unstructured data during time periods and spatial locations when structured data are unavailable. Data for widespread and migratory species are often fragmented across multiple monitoring programs. Our integrated model can estimate population abundance at broad spatiotemporal extents despite structured data gaps during the annual cycle by leveraging opportunistic data.
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 	<strong>Code and Data</strong> - <a href="https://github.com/zipkinlab/Farr_etal_2024_MEE">Link to repo</a>