intro.html

<img src="GothicCabins.jpg" width = "400px" align = "right">

<p><small>Adapted with permission from: <a href="http://tiee.esa.org/vol/v13/issues/data_sets/wu/abstract.html">Carrie Wu and Amy Ellwein. 2017. The Biology of Climate Change: The effects of a changing climate on migrating and over-wintering species at a high-elevation field station. TIEE 13:2 </a><br>
<i>Image credit: billy barr screen capture: Day's Edge Productions; L. Buckley</i>
</small></p>

<br>
<h4>Effects of rapid climate change on migrating and over-wintering species at a high elevation field station</h4>

<p>Virtually all species use predictable yearly changes in their local climate to determine when to initiate life-cycle events like breeding, flowering, and migration. Environmental factors such as temperature, day length, and precipitation can directly control the timing of these biological events, or act as cues that set an organism’s “biological clock” (Forrest and Miller-Rushing 2010). Over the past two decades, a growing body of evidence suggests that climate change is affecting this seasonal timing, or <b>phenology</b>, of plants and animals in a wide range of ecosystems, including temperate forests (Both et al. 2009), freshwater lakes (Seebens et al. 2009), and the open ocean (Koeller et al. 2009).  While these shifts in an organism’s life-history timing may keep it well-synchronized with local environmental changes, its interactions with other species may be disrupted. This <b>trophic mismatch</b>, or decoupling of interacting species, can result if the species do not show the same phenological shifts in response to a changing environment. For example, as the initiation plant growth has advanced in response to warming spring temperatures, peak food availability no longer corresponds to the timing of caribou reproduction, resulting in fewer births and more deaths among caribou calves in Greenland (Post and Forchhammer 2008). This trophic mismatch results from species using different environmental signals to regulate their phenology: the caribou are cued by increasing day length to migrate to areas where newly-emergent food should be plentiful, but plants initiate growth in response to temperature, not day-length.</p>

<img src="bbarr2.png" width = "450px" align = "right">

<p>In the following visualization, you can explore a long-term data set of climatic variables and phenology that have been collected at the <a href="https://www.rmbl.org/">Rocky Mountain Biological Laboratory</a> (RMBL) in Gothic, Colorado for several decades.  Since the mid-1970s, long-term resident and RMBL accountant, billy barr (he does not capitalize his name), has been recording weather conditions and the date of first sightings of many animal and plant species following snowmelt.  These data provide a unique opportunity to look for trends in phenology as they relate to climatic conditions.</p>

<p>You can evaluate the data from RMBL that formed the foundation of a study by Inouye et al. (2000), and then examine whether trends identified during that time period are supported by an additional 10 years of data collected during the subsequent decade.</p>

<p><small>Literature cited: Both C et al. 2009. J Anim Ecol, 78, 73-83; Forrest J and AJ Miller-Rushing. 2010. Phil Trans Roy Soc B 365: 3101–3112; Koeller P et al. 2009. Science 324: 791- 793; Inouye DW et al. 2010. PNAS 97: 1630-1633; Post E and MC Forchhammer. 2008. Phil Trans Roy Soc B 363: 2369–2375; Seebens H et al. 2009. Glob Change Biol 15: 1394- 1404. 
</small></p>
<br>
<h4>Background of the people and place</h4>

<img src="bbarr1.png" width = "450px" align = "right">

<p>Begin by reading the article, <a href="https://www.theatlantic.com/science/archive/2017/01/billy-barr-climate-change/512198/">The Hermit Who Inadvertently Shaped Climate-Change Science</a>, which introduces you to billy barr and why he started collecting this data in the first place. The images depict billy outside his cabin with some of his weather observing equipment and billy reviewing a data notebook in his cabin.</p>

<p>Next, read the article by David Inouye and colleagues, <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC26486/">Climate change is affecting altitudinal migrants and hibernating species</a>, upon which this activity is based. Here are the data for anyone who wants to explore them more: <a href="https://pubmed.ncbi.nlm.nih.gov/10677510/">phenology data set</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/10677510/">updated phenology data from 2000 to 2010</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/10677510/">climate data set </a>
</p>

<p>Finally, watch the video <a href="https://vimeo.com/182392548">The Snow Guardian</a> and this <a href="https://www.youtube.com/watch?v=LCcbWK3UAUE&feature=youtu.be">time-lapse of snowpack</a> at Snodgrass Mountain, CO. You can also check out billy barr's <a http://www.gothicwx.org/> weather </a> page with cameras and data.</p>

<br>
<h4>Data used in the visualization</h4>

<img src="marmots.png" width = "400px" align = "right">

<p>The visualization includes environmental data including snow melt date, total annual snowfall, annual snowpack, mean minimum April temperature, mean maximum April temperature, and melt water.</p>

<p>The visualization also includes first sightings data, which marks the date of first observation for 22 organisms consisting of 2 hibernating animals, 17 migrating animals, and 3 plants. The snow melt date and phenology data are recorded in terms of JD, or Julian day.  This simply indicates the day of year, where Day 1 = January 1, Day 32 = February 1, and so on.</p>

<p>Plant and animal species whose phenology has been monitored at the RMBL:
<br>
<b>Hibernating species</b>
<br>
Yellow-bellied marmot (<i>Marmota flaviventris</i>, depicted), Least chipmunk (<i>Tamias minimus</i>)
<br><br>
<b>Migrating species</b>
<br>
American robin (<i>Turdus migratorius</i>), Steller's jay (<i>Cyanocitta stelleri</i>), Red-winged blackbird (<i>Agelaius phoeniceus</i>), Dark-eyed junco (<i>Junco hyemalis</i>), Northern flicker (<i>Colaptes auratus</i>), Tree swallow (<i>Tachycineta bicolor</i>), Red-naped sapsucker (<i>Sphyrapicus nuchalis</i>), Fox sparrow (<i>Passerella iliaca</i>), Ruby-crowned kinglet (<i>Regulus calendula</i>), Yellow-rumped warbler (<i>Setophaga coronata</i>), Cliff swallow (<i>Petrochelidon pyrrhonota</i>), Golden-mantled ground squirrel(<i>Callospermophilus lateralis</i>), Broad-tailed hummingbird (<i>Selasphorus platycercus</i>), White-crowned sparrow (<i>Zonotrichia leucophrys</i>), Brown-headed cowbird (<i>Molothrus ater</i>), Mountain bluebird (<i>Sialia currucoides</i>), Yellow warbler (<i>Setophaga petechia</i>)
<br><br>
<b>Plant species</b>
<br>
Tall-fringed bluebell (<i>Mertensia ciliata</i>), Glacier lily (<i>Erythronium grandiflorum</i>), Western spring beauty (<i>Claytonia lanceolata</i>)
</p>


<br>
<h4>How to use the visualization</h4>

<p>The three tabs (“vs Year,” “vs snow condition,” and “vs other weather conditions”) allow you to change what is plotted on the x-axis.</p>

<p>In the “vs Year” tab, the time period decides the time limits of the x-axis. Both snow conditions and the first sighting dates of an organism are plotted on the y-axis. Thus, if you wish to plot only a snow condition, or only the first sighting dates of an organism, ensure that the other drop-down is blank. The unit "JD" stands for Julian Date, which simply indicates the day of year, where Day 1 = January 1, Day 32 = February 1, and so on. </p>

<p>In the “vs snow condition” and “vs other weather conditions” tabs, the time period is used to present a temporal subset of the data. The snow/weather condition is plotted on the x-axis, and the first sighting dates of an organism are plotted on the y-axis.</p>

<p>Below the plot you can see the linear regression statistics of the trendline. The slope is the rise/run or the rate of change. The p-value and the R<sup>2</sup> values determine the significance of the relationship between the two variables. A significant (nonzero) relationship between two variables has a p-value < 0.05.</p>