Notes taken by Michael White (, 435.760.7452) for the Applications discussion group at the National Phenology Network.

JB = Julio Betancourt

MD = Mike Dettinger

LG = Lianhong Gu

AF = Alfredo Huete

SM = Susan Mazer

RN = Ramakrishna Nemani

RP = Richard Primack

RP2 = Roger Pielke

MW = Michael White

XZ = Xubin Zeng

EP = Eric Post (group leader)

CW = Cynthia Wallace

EP. Reminder of EPN-type applications: socio-economic, health, nature management, education, gardening, hantavirus, west Nile (and other infectious diseases). What could be done with 20 years of data and 1 year of data. Also need for mining historical datasets. What can only be addressed with a national or continental scale network?

SM. Use of phenology for predicting outbreaks (previous years)

AH. Extension to ag regions.

RP. What can we do with phenology that can’t be done with temp?

RN. Phenological forecasting important.

XZ. Important to capture the immediate steps of soil water and temperature. Much better to measure directly. Should link applications to funding – seek out the applications sections. NOAA is emphasizing applications more. If we have 1 year of data: provides the possibility to get some really high quality data. May be more challenging with long term data. 1 year of good quality data provides opportunity to develop some improved phenology models for ecosystem models.

JB. Recaps some of the proposal goals and applications. Assess shifts in the timing of the fire season. Effects on hydrologic cycle. Carbon balance. Greenhouse gas emissions. Using phenology to track benefits of carbon emission controls. Ag crops and agroforestry. Cross-linking plant phenology to other organisms.

EP. Disease topics treatable with short- and long-term data.

RP. Movement of Mexican corn moth could be a good topic. Eaten by bats along the way.

MW. What is the growing season.

LG. We need NPN to validate models. Very hard to regulate phenology in models. Speed from one event to another needed.

RP. Leaf out can help.

SM. Is a biological understanding needed for ecosystem models? Or can it be empirical?

MW. Opens a can of worms on use of species-level phenology for models.

XZ. Quantification of SOS/EOS may be fairly simple but biomass much harder.

JB. Timing of phenological events may be important for productivity processes. We should work more with Ameriflux to tie phenology to carbon cycle processes.

EP. NPN participants don’t need to answer all the proposal questions. Perhaps the user can design experiments within NPN.

AH. Perhaps we could look at functional groups as opposed to species. We can’t look at one species.

MD. How do you put a cost/benefit on ecosystem models? NOAA does a good job with selling the weather prediction game: big limiting factor is soil moisture but maybe they really want phenology.

RN. Snow cover – phenology. Use snowtel-like decisions to trigger phenology.

MD. Yes but we still need the network to train the remote sensing.

XZ. Stresses the point that we need phenology for models.

EP. NPN should not have a goal of developing models – modelers should use the NPN.

MW. Use satellite data for mean conditions and species data for interannual variability.

EP. What can be done with existing data?

MD. We need the payoff-type questions. Here they are: (1) Monitoring and projecting impacts of atmospheric composition and climate variations and change on natural systems, including vegetation, wildfires, and water resources; (2) Enhanced data for agriculture, forestry, and nature management; (3) More widespread in situ foundations and data for carbon budgeting; (4) Improvements in weather, climate, and ecosystem forecasting and remote monitoring, on time scales from days to decades; (5) More direct foundations for vector and invasives control.

Some discussion followed on the use of phenology for weather/climate forecasts. General agreement that phenology and LE/H & recycled precip all important. Discussion continued to linger on the importance of phenology for a staggering variety of topics.

EP. We should think about highly temporally and spatially resolved studies.

AH. What about within- and among-ENSO studies. Example: Peruvian mesquite and ENSO.

EP. Example: one could look at geographic hotspots.

SM. Can we phrase questions to look at extreme events. Testing thresholds for specific species/communities? How env. changes affect ecosystem services, eg pollinator synchronicity.

EP. Good example: invasive species. Targeting control efforts.

MW. Need to preserve monitoring and question based approaches.

BREAK

EP. Working on a preamble for why we should study phenology.

SM. What is the scope of the statement? Phenological attributes of an ecosystem reflect its ability to sustain life.

EP. Understanding phenology allows us to have an ecological thermometer.

RP. Best indicator of climate change and variability.

RP2. Phenology also a forcing of climate, just as much as CO2 and solar luminosity. Biological system is part of climate at all scales.

At this point JB began to create a document with the preamble concepts. Some disagreements popped up about the importance of temperature itself versus the impacts of temperature changes. XZ argues that phenology is a better indicator of temperature than temperature itself. EP reinforces that people may care about phenology but not about temperature. Phenology has a better direct human impact. Some digressions ensued. EP took over working on the preamble.

JB argues for some specific examples of why phenology is great. RP2 includes environmental variability, not just climate change. MD suggests inclusion of the network concept. XZ: deemphasize climate. AH: add biodiversity.

MD recaps his five points (see above). Much wordsmithing follows. JB: need to understand the role of phenology in the biosphere. SM: NPN needs to have similar goals of acceptability in society as CDC, NWS, stream gauging. Suggestion widely supported.

EP: refocus on the importance of phenology in the biosphere. SM: phenology can be used as a predictor. XZ suggests an overarching sentence rationalizing NPN. EP wrote it down. SM: tie it back to things about which people care. MD/RP2/SM: some contention about the use of phenology for prediction versus diagnosis. JB argues that we’re losing sight of concrete, direct applications. EP was taking down these arguments in PowerPoint.

JB: we don’t understand how environmental factors affect phenology. We don’t know how the timing of phenological events affects the abundance and diversity of organisms and their function and interactions in the environment. NPN can add value to the large public investment in remote sensing products and platforms.

CW: bringing people back to nature. Natural reconnection. RP2: suggests the term environmental monitoring.