>Net Primary Production

Net Primary Production


This is an example of productivity of individual or groups of plants. High NPP will tend to indicate healthy plant communities, low NPP may indicate stressed plant communities. How to set high and low may be the question.
Category: 
Ecological Processes

QT: Indicators

What is it?

According to NASA, terrestrial biological productivity (or primary productivity) is the single most fundamental measure of “global change” of practical interest for humankind. Primary productivity is the measure of carbon intake by plants during photosynthesis, and this measure is an important indicator for studying the health for plant communities.

Net Primary Productivity (NPP) is the amount of carbon uptake after subtracting Plant Respiration (RES) from Gross Primary Productivity (GPP). GPP is the total rate at which the ecosystem capture and store carbon as plant biomass, for a given length of time.

NPP = GPP – RES

Photosynthesis is the process in which the energy from the sun converts carbon dioxide (CO2) from the atmosphere and water (or water vapor) to organic sugar molecules (carbohydrates), which are stored in the plants, and oxygen, which we, and other life on earth, consume. The extra water molecules which are derived in photosynthesis are reused by the plant or transpired into the atmosphere. Below is the chemical formula for photosynthesis:

6CO2 + 12H20 (+sunlight) C6H12O6+6O2+6H2O

NPP measures the mass of the new plant growth (chemically-fixed carbon) produced during a given interval. Change in NPP may change with vegetation health, so NPP rates were used to analyze the overall trend of carbon uptake in this region over the past ten years. To analyze trend, we downloaded ten years of monthly satellite data from NASA, which are are reported as grams of carbon uptake per meter square per day (gC/m2/day). With monthly data, we ran a Seasonal-Kendall trend analysis, and with annual data, we ran a Mann-Kendall and Regional-Kendall trend analysis.

Why is it important?

Humans continue to release CO2 and other greenhouse gases into the atmosphere from the burning of fossil fuels and agricultural practices. Plants cannot convert CO2 into biomass as fast as it is entering the atmosphere, causing a global buildup. These greenhouse gases trap heat from the sun and cause the surface temperature to rise, which has started a chain of events that will have enormous impacts on the globe in the years to come. These changes include glacial melting, sea level rising, and climatic shifting, which in turn can affect the welfare and health of all living things on this planet.

Target or Desired Condition

We take the desired condition to be a landscape where all trees are fully mature; that is, they have grown to the point where additional carbon storage on the landscape in aboveground biomass is limited to the rate of trees dying and new ones growing. Such a landscape is at its maximum potential for mitigating climate change through storage of atmospheric carbon dioxide.

We also selected a target for new carbon sequestration, as indicated by NPP, as an increasing trend, or at least not a declining trend. This means that a significant upward trend is a good condition from a climate mitigation point of view, and a declining trend is a poor condition.

What can influence or stress condition?
Regional climate will greatly affect the natural growth of shrubs and trees. Between 2006 and 2009, California experienced three consecutive dry water years. NPP will tend to decline in response to seasonal and drought-related drying. Plants take up CO2 through holes in their leaves called stomata. These will close under very dry conditions in order to reduce water loss by the plant. This means that as conditions dry, rates of carbon sequestration will decline. Because climate change may lead to drier and hotter conditions in many places in California, NPP may decline.

Data Sources

In February 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS), aboard NASA’s Terra and Aqua satellites, began producing regular global estimates for GPP and NPP at a spatial resolution of one square-km. When analyzing data from satellites, the scale, or resolution, which the data is collected can greatly influence the analysis. We downloaded these data from NASA Earth Observations, which provides global NPP data at a 0.1 degree scale (equivalent to approximately 8.5 km east/west and 11 km north/south at the study site). While this analysis could be improved with a finer-scaled dataset, with an average of 16.5 pixels for each subwatershed, this provided enough data to make estimates of general trends. The full dataset available was downloaded, with a temporal scale from February 2000 to January 2010 (120 GIS layers). These data were downloaded as georeferenced .tif files at the highest resolution (0.1 degrees) and as floating point pixel values. Each pixel represents the rate of NPP as grams of carbon uptake per meter squared per day (gC/m2/day), averaged over the 0.1 degree box and for that month.

The downloaded MOD 17 data is a product consisting of 8-day Net Photosynthesis (PSN) and NPP. Annual NPP is the time integral of the PSN product over a year.

These NPP data were used to provide an estimate of NPP for this study region. It has been previously found that areas recently affected by fire can cause the MODIS algorithm which is used to estimate NPP (MODIS 4.1 fPar) to overestimate NPP for many terrestrial ecosystems (Cheng, et al. 2006), and therefore, if the specific values were important, another data source should be used to validate MODIS data. Since this study has a coarse spatial resolution with a fairly stable ecosystem, we use these data to analyze the overall trend and assume a consistent variation of NPP estimates.

Data Transformations

Data is provides as a raster grid (1 km per pixel). Each pixel represents the amount of intake of grams of carbon per meter squared per day (gC/m2/day). We intersect these raster data and the vector data designated the regions in our study area, and generate a mean value per subbasin (per month, season, and year).

What did we find out/How are we doing?

There were relatively high scores for carbon standing stock, ranging from 86 for the East Branch North Fork Feather to 96 for Deer Creek. There was significant downward trends in annual NPP for the three the western, lower elevation and agricultural rich, subwatersheds (Lower Bear, Lower Feather, Lower Yuba). Despite the high absolute values of the indicator scores, scores should be as close to 100% as possible, because of the need to reach global greenhouse gas mitigation goals.

How sure are we about our findings? (Things to keep in mind)

With regard to NPP, these data were not readily available at the highest resolution provided by NASA. While the GIS processing of the raster data should provide an accurate estimate for calculated parameters, the smallest subwatersheds, for example Deer Creek, contain only a few of the low-resolution data cells that NASA currently provides through their website.

Sub-watershed
Area Code Score Trend Confidence
North Fork Feather NFF 94
East Branch North Fork Feather EBNFF 86
Middle Fork Feather MFF 88
Lower Feather LF 93 Downward
North Yuba NY 93
Middle Yuba MY 89
South Yuba SY 93
Deer Creek DC 96
Lower Yuba LY 91 Downward
Upper Bear UB 91
Lower Bear LB 93 Downward