3. Objectives, Rationale, and Significance
3.1 Capacity building
We propose to study species and their interactions with teams of students at 95 field sites,
building a powerful new multi-site framework for natural history research.
It will allow us to address large-scale research questions (section 3.2) and mentor
a new generation of field scientists.
Traditional methods of collecting and managing specimen-level data are neither economically nor functionally feasible
for studying the driving forces of large-scale ecological phenomena.
While required for systematics, processing physical specimens is too laborious
and inefficient to yield sufficient replicates of comparable data across sites and over time.
Faced with this problem, many studies have turned to citizen scientists
to collect data rapidly and over extensive geographical areas (Crall et al. 2010).
However, when data are strictly observational, they generally lack credibility and scientific rigor,
because species identifications cannot be verified and are often wrong (Mumby et al. 1995,
Ericsson and Wallin 1999, Barrett et al. 2002, Genet and Sargent 2003, Brandon et al. 2003).
To address these issues, Discover Life has designed a system to collect, identify,
integrate and check large quantities of high-quality data using digital photography, web tools and rigorous protocols.
Our experience with the Lost Ladybug Project
shows that when image data are verified by experts they can be of very high-quality.
We are now ready to expand our system across a network of field sites and taxa,
enabling researchers to answer ecological questions across scales ranging from local to continental.
3.2 Research Questions
Our initial work focuses on six questions. We will expand these to additional taxa as researchers join the network.
3.2.1 How temperature drives the phenology of plants, insects and other taxa
Many taxa have shown a biological response to climate change
(Parmesan and Yohe 2003, Walther et al. 2002, Root et al. 2003).
Certain plants, birds and butterflies have shifted their geographic distributions
(Grabherr et al. 1994, Thomas and Lennon 1999, Parmesan et al. 1999).
In addition, some plants, birds, butterflies and amphibians have shifted their seasonal phenology
(Fitter and Fitter 2002, Menzel et al. 2001, Bradley et al. 1999, Roy and Sparks 2000, Beebee 1995,
Gibbs and Breisch 2001).
Pickering, Hargrove, Creed, and Long are modeling satellite and weather data
to understand variation in the timing and length of the growing season,
using MODIS satellite images of the "green" signal from mid-latitude Mexico through southern Canada
and NOAA's data from over 10,000 ground-based weather stations.
These models, based on the methods of Hochberg et al. (1986), will predict the timing of spring and fall for plant communities
across the continent based on weather data.
To compare how weather drives phenonolgy at the species level,
we propose to collect specimen-level data and analyze species activity across study sites in a similar manner.
We will develop our protocols in consultation with the National Phenology Network and tailor them with
Climate change and phenology studies that focus on individual species
tend to favor more extreme changes than those studies of groups of species (Parmesan 2007).
Hence, we propose to collect data on many species from a phylogenetic array of plants,
moths and other taxa to increase the strength and accuracy of our results.
Because sampling frequency and population size can affect results from phenology studies (Miller-Rushing et al. 2008),
we will collect data frequently and focus on species that are common across sites.
- 3.2.2 Inventorying and predicting biodiversity and invasion across the continent
NEON has delineated 20 domains in the United States, defined by a multivariate analysis
of temperature, precipitation, and soil moisture
(Hargrove and Hoffman 2009; Field et al. 2006).
These domains are defined solely by abiotic factors and neither by the biological communities nor species within them.
How powerful are local versus large-scale factors in determining species distributions and patterns in biodiversity?
How important are biotic versus abiotic factors in structuring communities at different scales, from individual sites,
through NEON domains, to the biogeography of North American and surrounding areas?
Researchers have yet to take advantage of the climatic and edaphic factors that define NEON domains
in understanding biodiversity and predicting how it will change over the next century.
To rectify this, we propose to inventory plants, lichens, slime molds, butterflies, moths, syrphid flies and amphibians
at sites in each NEON domain and at 5 tropical sites in Central America.
We will analyze our local inventories in conjuction with species checklists at the domain level
that we will assemble from herbaria, museums, and other sources.
We will extend the methods that we used in large-scale comparisons of biodiversity across regions
(Bartlett et al. 1999, Skillen et al. 2000),
compare alpha diversity (species richness within the domains) and beta diversity
(rate of species turnover across domains) with data on species interactions,
and better understand how regional flora and fauna are pieced together.
Our proposed inventories will detect novel invasions of non-native species at each site,
and perceive general trends of invasive species across sites.
With its partners at USGS National Biological Information Infrastructure (NBII) and
referring to the USDA PLANTS database and APHIS information sources,
Discover Life has assembled invasive species lists.
These will be factored out when we try to understand how the climatic and edaphic variables have shaped the
native species composition and biogeography of the domains.
The invasive species lists will be factored in when we try to understand if
certain domains are more susceptible to biological invasion than others.
- 3.2.3 Between-year variation in pollinator abundance across sites and disruption of pollination seasonal synchrony
Changes in climate may have both direct and indirect effects on plant reproduction.
For those plants that rely on an animal pollinator, changes in the phenology of that
pollinator that do not correspond with changes in phenology of the host plant may
have dire consequences for both. Recent work in alpine environments suggests that
plant phonologies are changing asynchronously leading to novel communities where
formerly tightly co-adapted relationships may be disrupted (Forrest et al. 2010)
and there is increasing asynchrony between some plants and their pollinators
leading to declines in reproductive success of those plants (Thomson 2010).
Using data collected in this project, we plan to ask three questions:
Can we detect disruptions in synchrony between pollinator emergence and plant flowering times?
Are these disruptions significant enough to decrease plant fertility or pollinator abundance?
Does climate influence the amount of synchrony in pollinator and plant communities?
- 3.2.4 How climate affects local and regional fruiting of selected mushroom species
It has long been known that the phenology of macrofungi (mushrooms)
is influenced by both precipitation and temperature (Stephenson 2010),
and that there is already some change in phenology due to warming winter temperatures
(Kauserud 2008, Kauserud et al. 2010).
Because mushroom fruiting is more closely tied to weather responses than to photoperiod or day length,
their phenology is both harder to predict and more sensitive to climate (Kauserud et al. 2010).
We aim to determine how weather affects the phenology of individual species in this somewhat
climate-sensitive and unpredictable group.
The Fungimap project in Australia has demonstrated the feasibility of using citizen scientists
to document the occurrence of mushrooms on a continental scale
and will serve as a model for our mushroom component of the
proposed project. We will make identification keys, images and information relating to approximately 100
"target" species on Discover Life in a manner similar to that developed by Co-PI Stephenson
on www.mushroom.uark.edu and www.ncrfungi.uark.edu .
We plan to answer how rainfall and temperature affect local and regional fruiting of mushrooms.
- 3.2.5 Large-scale factors affecting slime mold biogeography, local diversity, and ecology
Slime molds (myxomycetes) generally occur on some of the same substrates (e.g., decaying wood and forest floor litter) as mushrooms.
Although the fruiting bodies produced by slime molds are smaller than those of mushrooms, those of most species tend to be produced
in groups or clusters that can be documented (i.e., with digital images) in the same way as mushrooms. Co-PI Stephenson wrote the
text of the only true field guide (Stephenson and Stempen 1994) available for slime molds and has developed educational materials
(see www.slimemold.uark.edu) that will serve as the starting point for this component of our project.
We aim to answer the following questions about the influence of climate change on species abundance
and association of species of myxomycete with particular vegetation types.
Species abundance and climate change.
There is little question that some species of myxomycetes are common while others are rare (Stephenson and Stempen 1994).
Are changes in levels of abundance occurring (i.e., common species declining and certain rare species becoming more evident)?
If so, can this be related to weather patterns? Do some species actually become locally extinct?
Association of species of myxomycete with vegetation type.
There is some evidence that the overall biodiversity of the assemblage of species of myxomycetes
associated with a particular vegetation type is related to the biodiversity of the plants (particularly the woody plants) present,
but this has never been evaluated on a regional or continental scale. To what extent does this linkage exist?
These studies will also provide baseline data for use by other researchers to answer novel questions about this group.
- 3.2.6 Lichen diversity and growth rates as bio-indicators of pollution and drought
Lichens are good bioindicators of air pollution, and in some cases yield more accurate results
than those from air particulate matter analysis (Rossbach et al. 1999, Garty 2001).
Since 1994, the US Forest Service has been using lichens (fia.fs.fed.us/lichen/background)
to monitor for air quality as part of the Forest Health Monitoring program.
However, these studies focus on species richness and do not provide fine-grained data about
lichen growth patterns.
We also do not fully understand the potential effects of drought and other weather conditions on lichen
growth rates and species richness (Ellis et al. 2007).
We aim to answer how weather and air quality affect lichen growth rates.