Download - Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University
![Page 1: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/1.jpg)
Some Thoughts on Shifts in Biome SeasonalityGeoff Henebry, South Dakota State University
We need to unpack this “new” phrase
1) “Shifts” implies an observable baseline against which to quantify a change and further implies that the shift is significant
2) “Biome” implies an emergent vegetation-climate association
3) “Seasonality” implies quasi-periodic abiotic phenomena
What about phenology? GIScCEGIScCE
![Page 2: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/2.jpg)
Phenology has been defined as the study of the timing of recurring biological events, the causes of their timing, their relationship to biotic and abiotic forces, and the inter-relations among phases of the same or different species.
J.Y. Ewusie, 1992
Source: Ewusie, J.Y. 1992. Phenology in Tropical Ecology. Accra: Ghana Universities Press. 109 pp.
GIScCEGIScCE
![Page 3: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/3.jpg)
Some Useful Distinctions
Phenology has traditional been linked to species
Land Surface Phenologies (LSPs) are the seasonal spatio-temporal patterns of the vegetated land surface [as observed by synoptic sensors at spatial resolutions and extents relevant to meteorological processes in the
atmospheric boundary layer] (de Beurs and Henebry, 2004 RSE;
2005 GCB; 2005 IJRS; 2008 JClim).
NASA Community White Paper on “Phenology” (Friedl et al.
2006) describes the concept of LSPs and stresses that LSPs are intrinsically mixtures of biotic & abiotic signals
Strong latitudinal & altitudinal controls on LSPs
Various shades of LSPs• Spring-green• Rain-green• Ever-green• Never-green
GIScCEGIScCE
![Page 4: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/4.jpg)
What are some aquatic aspects of phenology/seasonality?
Various shades of aquatic: Inland vs. Coastal vs. Bluewater
Inland distinctions: wetlands, lakes, reservoirs, perennial vs. intermittent streams, rivers & their floodplains
Aquatic phenomena: Lake ice on/off, onset of meltwater flows, flood-pulse events, algal/cyanobacterial blooms, ...
What is common to terrestrial & aquatic phenologies and/or seasonalities?
Human modulation (LCLUC, ag mgmt, pollution, invasive & introduced species, etc.)
Atmospheric modulation (ENSO, NAM, PDO, etc.)
Solar modulation? GIScCEGIScCE
Kryjov, VN, and C-K Park. 2007. Solar modulation of the El Niño/Southern Oscillation impact on the Northern Hemisphere annular mode. GRL 34:L101701
![Page 5: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/5.jpg)
What are key challenges?
Multiplicity of Methods + Multiplicity of Targets = Confusion
The nomenclature void must be addressed !
Land Surface Phenology Variable Intercomparison Project initiated by Mike White, USU, and Kirsten de Beurs, VT, at 2007 AGU phenology sessions.
What are appropriate spatial units for characterizing phenology/seasonality? Pixels? Ecoregions? Ad-hoc units? MAUP=modifiable areal unit problem
What are appropriate temporal units for characterizing phenology/seasonality? Calendar time? Compositing periods? Thermal time?
What are appropriate methods to characterize “shifts” and assess their significance? Step changes vs. Trends (accumulations of insignificant changes)
GIScCEGIScCE
![Page 6: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/6.jpg)
AGDD
ND
VI
AGDD
ND
VI
AGDDN
DV
I
Changes in LSP following the collapse of the Soviet Union are not uniform across Kazakhstan (de Beurs and Henebry 2004, 2005).
![Page 7: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/7.jpg)
CENTRAL ASIATrends in
MODIS NBAR NDVI (C4 CMG)2001-2006 DOY 65-241
Revealed using theSeasonal Mann-Kendallnonparametrictrend test corrected for autocorrelation (de Beurs and Henebry 2004 GRSL)
Red: |SMK lt 0|Green: SMK gt 0Blue: mean NDVI
White: CountriesBlue: RiversYellow: Coastlines
GIScCEGIScCE
![Page 8: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/8.jpg)
GIScCEGIScCE
White: CountriesBlue: RiversBrown: Coastlines
CENTRAL ASIATrends in
MODIS NBAR NDVI (C4 CMG)2001-2006 DOY 65-241
Revealed using theSeasonal Mann-Kendallnonparametrictrend test corrected for autocorrelation (de Beurs and Henebry 2004 GRSL)
Red: |SMK lt 0|Green: p le 0.01Blue: mean NDVI
![Page 9: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/9.jpg)
CIRCUM-POLAR Trends in
MODIS NBAR NDVI (C4 CMG)
2000-2006 DOY 97-257
Red: 1-(p le 0.01)Green: mean NDVI ge 0.1Blue: SMK trend test gt 0
GIScCEGIScCE
![Page 10: Some Thoughts on Shifts in Biome Seasonality Geoff Henebry, South Dakota State University](https://reader033.vdocuments.mx/reader033/viewer/2022051621/56814bef550346895db8d575/html5/thumbnails/10.jpg)
Significant opportunities for the research themeShifts in Biome Seasonality
Blending of datastreams from multiple sensors/platforms
• Active microwave • Passive microwave• Thermal and mid-IR (3-5 m)• Geostationary optical• Polar orbiting optical
to develop a comprehensive suite for characterizing land surface phenologies & seasonalities in different biomes/ecoregions.
Useful for monitoring, change analysis, impacts assessment, modeling (carbon, water, nutrients, weather, climate, land use, habitat,…), and ecological forecasting.
GIScCEGIScCE