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This workshop is sponsored in part by the USA National Phenology Network and the NSF USA-NPN Research Coordination Network (Grant #0639794). A Workshop.

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Presentation on theme: "This workshop is sponsored in part by the USA National Phenology Network and the NSF USA-NPN Research Coordination Network (Grant #0639794). A Workshop."— Presentation transcript:

1 This workshop is sponsored in part by the USA National Phenology Network and the NSF USA-NPN Research Coordination Network (Grant # ). A Workshop on Land Surface Phenology Presented by Kirsten de Beurs, Ph.D. Department of Geography Virginia Tech University & Geoffrey M. Henebry, Ph.D., C.S.E. Geographic Information Science Center of Excellence South Dakota State University

2 Lecture 1: Introduction to Land Surface Phenology GIScCE Geoffrey M. Henebry, Ph.D., C.S.E. Professor of Biology & Geography and Senior Research Scientist Geographic Information Science Center of Excellence (GIScCE) South Dakota State University Madison LSP Workshop: 08 APR 2008

3 1.Contexts for Land Surface Phenology (28) A. What is Phenology? (16) B. What are Objects of Phenological Interest? (3) C. What are Methods of Phenological Observation? (5) D. What are Methods of Phenological Analysis? (4) 2.Remote Sensing Basics (9) E.The Planetary Macroscope (3) F.Radiation Basics (3) G. Seeing “Green” from Space (3) 3.A Driver of Phenology (18) H.Whose Time? (2) I.Réaumur & Thermal Times (6) J.Example from Konza Prairie LTER: Insolation, AGDD, ANPP (9) 4.Concluding Remarks (3) Outline of Talk

4 GIScCE What is phenology ?

5 Instead every plant must possess a certain adjustment to the season, since the season turns out to be more responsible [for sprouting] than anything else. For all are seen to await their own appropriate season, meanwhile not sprouting at all and not be set in motion, trees and woody and herbaceous plants alike; for the fact is plainest in wild plants, where generation is the plant’s own doing and not promoted by man. De Causis Plantarum, Book 1, Theophrastus on Plant Phenology ( B.C.)GIScCE

6 GIScCE Phenology may be defined as the science of investigating the influence of meteorological conditions on the recurrence of the annual phenomena of animal and plant life, such as, for example, the dates of appearance of blossoms or insects. H.C. Gunton, 1938 Source: Gunton, H.C Nature Study Above and Below the Surface: A Bridge between Amateur and Professional. London: H.F.& G. Witherby., LTD. 134pp.

7 GIScCE Phenology may be defined as the science of investigating the influence of meteorological conditions on the recurrence of the annual phenomena of animal and plant life, such as, for example, the dates of appearance of blossoms or insects. H.C. Gunton, 1938 Source: Gunton, H.C Nature Study Above and Below the Surface: A Bridge between Amateur and Professional. London: H.F.& G. Witherby., LTD. 134pp.

8 GIScCE Phenology, which derived from the Greek word  meaning to show or to appear, is the study of periodic biological events in the animal and plant world as influenced by the environment, especially temperature changes driven by weather and climate. M.D. Schwartz, 2003 Source: Schwartz, M.D Introduction. In: (M.D. Schwartz, ed.) Phenology: An Integrative Environmental Science. Boston: Kluwer Academic Publishers. 564pp.

9 GIScCE Phenology, which derived from the Greek word  meaning to show or to appear, is the study of periodic biological events in the animal and plant world as influenced by the environment, especially temperature changes driven by weather and climate. M.D. Schwartz, 2003 Source: Schwartz, M.D Introduction. In: (M.D. Schwartz, ed.) Phenology: An Integrative Environmental Science. Boston: Kluwer Academic Publishers. 564pp.

10 GIScCE 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 Phenology in Tropical Ecology. Accra: Ghana Universities Press. 109 pp.

11 GIScCE 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 Phenology in Tropical Ecology. Accra: Ghana Universities Press. 109 pp.

12 GIScCE KEY POINTS Phenology…  Studies temporal patterns of biological events  Focuses on specific organisms  Seeks to understand the influences on or causes of timing of these events due to: abiotic forces biotic forces intraspecific interactions interspecific interactions

13 GIScCE CAVEATS Phenology is not…  restricted to annual phenomena  restricted to the extratropics  restricted to temperature effects  restricted to vernal emergence, the “onset of spring”

14 GIScCE Seasonality is a related term, referring to similar non-biological events, such as timing of the fall formation and spring break-up of ice on fresh water lakes. M.D. Schwartz, 2003 Source: Schwartz, M.D Introduction. In: (M.D. Schwartz, ed.) Phenology: An Integrative Environmental Science. Boston: Kluwer Academic Publishers. 564pp.

15 GIScCE Some Useful Distinctions & Categories  Phenology is distinct from seasonality: biotic vs. abiotic temporal patterns. But seasonality can affect phenology and vice versa.  Land surface phenology is distinct from phenology: observing electomagnetic radiation at coarse spatial resolution results in a mixture of signals that combines biotic and abiotic components.

16 Some Useful Distinctions & Categories  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 ].  LSPs affect the timing and magnitude of energy and water exchanges between the land surface and the boundary layer.GIScCE

17 Key surface types for LSPs:  Ever-green  Spring-green  Rain-green  Never-green GIScCE

18 GIScCE Differential Land Surface Phenology due to Land Use MODIS 1km in 2004 R = 08MAY G = 27JUL B = 08MAR SD NE KS

19 GIScCE Land Surface Phenology: AVHRR WDRVI 2000 R=Jun02-Jun15, G=Jul14-Jul27, B=Mar10-Mar23

20 GIScCE What are objects of phenological interest?

21 Question: What is Spring?— Growth in everything— Flesh and fleece, fur and feather, Grass and greenworld all together From The May Magnificat By Gerard Manley Hopkins GIScCE

22 GIScCE  Species Arrivals & Departures (Appearances & Disappearances)  Species Growth & Development  Species Abundance  Temporal Sequence of Species Interactions, e.g., pollination, seed dispersal.  Temporal Sequence of Population Interactions, e.g., reproductive behavior, mating rites.  Unusual Events, e.g., very early or very late events, disturbance and recovery, invasive species, meteorological extremes.  Others?

23 GIScCE What are methods of phenological observation?

24 GIScCE  Surveys along routes or transects  Periodic observations in permanent plots  Manipulative experiments with phenological response variables  Citizen science (e.g., GLOBE; NatureMapping)  Remote and proximal sensing  Harvesting of past observations from older articles, monographs, gray literature documents, and theses/dissertations and digitizing them for contemporary analyses.  Others?

25 GIScCE The Significance of the Observer in Phenology  As implied in the roots of the word, appearance is a critical aspect of phenological investigations, but appearance to whom ?  Survey or sampling design is one key to capturing ephemeral and/or spatially variable phenomena.  Another critical key is training of observers. Phenological items may involve visual or auditory cues. Recognition and correct identification of these cues may require substantial training or prior experience.  Error among observers is rarely quantified.

26 GIScCE Characteristics of a “good” phenological item pt 1 low labor cost/simple to observe sharp/distinct to minimize error among observers  issue of binomial vs. multinomial vs. ordinal scale common/abundant high degree of accessibility (visibility or audibility) Source: Leopold, A., and S.E. Jones A phenological record for Sauk and Dane Counties, Wisconsin, Ecological Monographs 17(1):

27 GIScCE Characteristics of a “good” phenological item pt 2 reliability of recurrence continuity evidence of newness locally-determined dynamics sufficient prior knowledge to identify the unusual what else? Source: Leopold, A., and S.E. Jones A phenological record for Sauk and Dane Counties, Wisconsin, Ecological Monographs 17(1):

28 GIScCE What are methods of phenological analysis?

29 GIScCE  Database Querying  Graphical Analysis  Association Rules  Exploratory Data Analysis/Data Mining  Statistical Models  Physiologically-based Models of Development  Simulation Models  Interpretative Gestalt  Others?

30 GIScCE Source: Leopold, A., and S.E. Jones A phenological record for Sauk and Dane Counties, Wisconsin, Ecological Monographs 17(1): Phenology, in short, is a “horizontal science” which transects all ordinary biological professions. Whoever sees the land as a whole is likely to have an interest in it. A. Leopold & S.E. Jones, 1947

31 Grasslands phenology emerges from the interactivity of multiple influences as filtered through the specifics of spatial relationships, genetic heritage, and the process of observation. source: Henebry, G.M Grasslands of the North American Great Plains. In: Phenology: An Integrative Environmental Science (M.D. Schwartz, editor). Kluwer, New York. pp

32 Using the planetary macroscope Learning to see again at different scales.Learning to see again at different scales. Scale describes the resolution (grain) and extent of measurements and the relationship between the thing observed and its measurement.Scale describes the resolution (grain) and extent of measurements and the relationship between the thing observed and its measurement. –Spatial scales –Temporal scales –Spectral scales –Radiometric scales Resisting the naïve interpretations that our evolved visual cognition system provides.Resisting the naïve interpretations that our evolved visual cognition system provides. Just as telescopes are “light buckets” gathering starlight and integrating it over extended periods, the constellation of earth-observing sensors gathers and integrates the sunlight and earthlight arising from the planetary surface.

33 Remote sensing samples just tiny fractions of reflected solar & emitted terrestrial radiation

34 Passive Sensing Shortwave:reflectedsunlight Longwave:emittedearthlight Illumination Target Sensor GIScCE

35 Any matter with a temperature greater than absolute zero emits electromagnetic radiation. How to determine what are the characteristics of that emission? Use the convenient fiction of the “blackbody”  a perfect absorber is also a perfect emitter. GIScCE

36 Half-a-Nickel Course in Radiation Laws (1)Planck’s Law : Upper bound on the intensity of the radiation emitted by a blackbody: B (T) d = ( 2 h c 2 ) / [ 5 ( e hc / k T -1) ] d where  is wavelength T is temperature in K h is Planck’s constant  x J s C is the speed of light in a vacuum  x 10 8 m s -1 k is Boltzmann’s constant  x J K -1 Resulting units: W m -2  m -1 sr -1  Power per unit area per unit solid angle per unit wavelength Intensity of emission contributed by the wavelength interval [, +d ] varies by the inverse fifth power. Hotter things emit shorter.

37 Half-a-Nickel Course in Radiation Laws (2)Wien’s Displacement Law: For a given absolute temperature, Planck’s Law has a single peak at a wavelength that is inversely proportional to that temperature: max x T = A or max = A / T where  is wavelength T is temperature in K A is a constant  2897  m K K oCoC mm Sun’s temp H 2 O boiling pt normal body temp APR max (04/22/80) APR max normal H 2 O freezing pt APR min (04/07/82)

38 Source: Wikipedia Atmospheric opacity across the electromagnetic spectrum

39 Blue Green Red Near infrared Spectra collected in the Nebraska Sandhills, June 2004

40 Normalized Difference Vegetation Index (NDVI) exploits the spectral contrast between NIR and red reflectance displayed by (most) terrestrial vegetation. NDVI = ( r NIR – r red ) / ( r NIR + r red ) NDVI gives some indication of the density of absorbers of photosynthetically active radiation (PAR  nm) at the surface. However, mapping NDVI into leaf area index (LAI) or aboveground net primary production (ANPP) is fraught with caveats and uncertainties. Nevertheless, it provides an important window into the dynamics of the vegetated land surface. GIScCE

41 GIScCE Drivers of Phenology

42 GIScCE Whose time? If phenology attends to the timing of recurrent biological events, then whose “clock” and “calendar” should track that time? Calendars are anthropocentric. Do the plants pay attention to our calendars? Can we link vegetation dynamics to a bioclimatological calendar?

43 GIScCE Heat-sum or degree-day methods are simple and quite old, but have a theoretical foundation in the kinetics of biochemical reactions. Source: Charles-Edwards, D.A., D. Doley, G. Rimmington Modelling Plant Growth and Development. Sydney: Academic Press Australia. 235pp.

44 GIScCE René Antoine Ferchault de Réaumur (February 28, October 17, 1757) In 1731 he became interested in meteorology, and invented the thermometer scale which bears his name: the Réaumur. Source: Wikipedia The freezing point of water is 0 degrees Réaumur, the boiling point 80 degrees Réaumur. Hence, a Reaumur degree is 1.25 Celsius degrees or Kelvins. Réaumur may have chosen the octogesimal division because the number 80 could be halved 4 times and still be an integer (40, 20, 10, 5); the number 100, for instance, could only suffer this process twice (50, 25).

45 Réaumur “adopted simply the sum of the mean daily temperature of the air as recorded by a thermometer in the shade, and counting from any given physiological epoch to any other epoch.” Abbe, Cleveland A First Report on the Relations Between Climates and Crops. Bulletin 36. Weather Bureau, No USDA. Source: van Keulen, H Forecasting and estimating effects of weather on yield. In: (K. Wisiol and J.D. Hesketh, eds.) Plant Growth Modeling for Resource Management: Volume 1 Current Models and Methods. Boca Raton, FL: CRC Press. Pp GIScCE

46 “The true problem for the climatologist to settle during the present century is not whether the climate has lately changed, but what our present climate is, what its well-defined features are, and how they can be most clearly expressed in numbers.” […] “It will be seen that rational climatology gives no basis for the much- talked-of influence upon the climate of a country produced by the growth or destruction of forests, the building of railroads or telegraphs, and the cultivation of crops over a wide extent of prairie.” Cleveland Abbe, Is our climate changing?, Forum, 6, pp , 1889 Source: The American Meteorological Society has an annual award: The Cleveland Abbe Award For Distinguished Service To Atmospheric Sciences By An Individual More on Professor Abbe here: GIScCE

47 GIScCE In phenological studies, it is sometimes convenient to summarize recent weather into measures that can relate to plant growth and development. Accumulated Growing Degree-Days (also known as thermal time) is a simple biometeorological variable that weights the passage of days by the quantity of “growing degrees” – that portion of the diel temperature range that is useful for plant growth, broadly construed. The calculation of AGDD is straightforward. The average temperature for a given day is calculated as the simple mean of the maximum and minimum temperatures observed that day. From this average, a “base temperature” is subtracted and values summed: AGDD t = AGDD t-1 + max[(AverageTemp t - Base),0]

48 GIScCE The magnitude of the base depends on the type of organism under consideration. I have found that for perennial grasslands a base of 0 o C is very effective. Crop models often use a base of 4 o C for cool season crops (e.g., winter wheat) and 10 o C for warm season crops (e.g., maize). In the northern hemisphere the convention is to start accumulating at the beginning of the year, with each 01JAN resetting the accumulation. (Is that appropriate?) While this approach is handy for temperate and boreal systems, it is not very useful in tropical or arid systems in which phenological timing is associated with available moisture, internal carbohydrate pools, co-evolved relationships, or other non-thermal triggers.

49 GIScCE Temperature serves a surrogate for insolation, but it is also very important itself for regulating rates of enzyme systems. Thus, temperature is a “mixed signal” and its use is further complicated by the fact that as variable it is intensive rather than extensive. Extensive measurements scale with change of dimension. Intensive measurements don’t. Examples: (1) the temperature of this room vs the mass of air in the room; (2) your body temperature vs your body weight.

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54 GIScCE Using a base temperature of 0 o C ( K)

55 GIScCE Using a base temperature of 4 o C ( K)

56 GIScCE Using a base temperature of 10 o C ( K)

57 GIScCE Konza Prairie LTER biweekly ANPP: Aboveground biomass dynamics are well approximated by a piece of a parabola.

58 Quadratic models can fit well retrospectively, but also fail spectacularly, as in Konza Prairie LTER biweekly ANPP on 01A: GIScCE

59 GIScCE Concluding Remarks  Land Surface Phenology describes the aspects of recurrent biotic and abiotic phenomena that are observable by sensors which have a coarse spatial resolution relative to the objects of interest.  LSPs are not traditional organism-centric specific sets of phenophases. As mixtures of signals, LSPs must be interpreted with care.  One simple, but powerful, approach to modeling temperate LSPs is linking images to weather using thermal time.

60 Peak NDVI is derived from the parameter coefficients and Green-up period (φ) is the amount of GDD (°C) necessary to reach the peak, and it too can be derived from parameter coefficients. Quadratic Model of Green-Up Nonlinear Spherical Model of Green-Up The peak (  +  ) gives the maximum NDVI.  is the quantity of AGDD required to reach the peak and corresponds to the duration of the observed green-up phase. φ =    NDVI peak =   GIScCE

61 Both LSP models fit well in some regions and neither does in others. Applying the better fit to reanalysis grid cells (~2 o ) across the northern hemisphere, we can map out four ecologically interpretable metrics that can be derived from the LSP model parameters: (1) the NDVI at the onset of the observing season ; (2) the seasonal peak NDVI; (3) the quantity of AGDD needed to reach the peak; and (4) the seasonal dynamic range of NDVI. Density sliced images of PC1s from 9 years ( & ) GIScCE QUESTIONS?


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