Interannual variation in global-scale net primary production: Testing model estimates

Testing estimates of year‐to‐year variation in global net primary production (NPP) poses some challenges. Large‐scale, multiyear records of production are not readily available for natural systems but are for agricultural systems. We use records of agricultural yields at selected sites to test NPP estimates produced by CASA, a global‐scale production model driven by both meteorological data and the satellite‐derived normalized difference vegetation index (NDVI). We also test estimates produced by the Miami model, which has underlain several analyses of biosphere response to interannual changes in climate. In addition, we test estimates against tree ring data for one boreal site for which data from both coniferous and deciduous species were available. The agricultural tests demonstrate that CASA can reasonably estimate interannual variation in production. The Miami model estimates variation more poorly. However, differences in NDVI‐processing algorithms substantially affect CASA's estimates of interannual variation. Of the four versions tested, the FASIR NDVI most closely reproduced yield data and showed the least correlation with changes in equatorial crossing time of the National Oceanic and Atmospheric Administration satellites. One issue raised is the source of the positive trends evident in CASA's NDVI‐based estimates of global NPP. The existence of these trends is consistent with potential stimulation of terrestrial production by factors such as CO2 enrichment, N fertilization, or temperature warming, but the magnitude of the global trends seen is significantly greater than suggested by constraints imposed by atmospheric fluxes

A global climate niche for giant trees

Rainforests are among the most charismatic as well as the most endangered ecosystems of the world. However, although the effects of climate change on tropical forests resilience is a focus of intense research, the conditions for their equally impressive temperate counterparts remain poorly understood, and it remains unclear whether tropical and temperate rainforests have fundamental similarities or not. Here we use new global data from high precision laser altimetry equipment on satellites to reveal for the first time that across climate zones \u27giant forests\u27 are a distinct and universal phenomenon, reflected in a separate mode of canopy height (~40 m) worldwide. Occurrence of these giant forests (cutoff height > 25 m) is negatively correlated with variability in rainfall and temperature. We also demonstrate that their distribution is sharply limited to situations with a mean annual precipitation above a threshold of 1,500 mm that is surprisingly universal across tropical and temperate climates. The total area with such precipitation levels is projected to increase by ~4 million km2 globally. Our results thus imply that strategic management could in principle facilitate the expansion of giant forests, securing critically endangered biodiversity as well as carbon storage in selected regions

Predicting the time of green up in temperate and boreal Biomes

Direct observations as well as Normalized Difference Vegetation Index (NDVI) data from satellites have shown earlier leaf appearance in the northern hemisphere, which is believed to result from climate warming. The advance of leaf out to earlier times in the year could be limited or even reversed, however, as temperate and boreal trees require a certain amount of chilling in winter for rapid leaf out in spring. If this chilling requirement is not fulfilled, an increasing amount of warming is required. Implications of these chilling requirements at the biome level are not clear. One approach to estimate their importance is to generalize the exponential relationships between chilling and warming established for single species. Previous work using NDVI data suggests that this is indeed feasible but much has been limited to specific biomes or a very few years of data for the modelling. We find chilling requirements for northern temperate and boreal biomes by fitting various phenology models to green-up dates determined from NDVI using various methods and 12 years of data. The models predict that in northern middle and high latitudes the advance of green-up will be limited to a total of 4 to 5 days on average (but up to 15 days regionally) over the time period 2000–2060 as estimated using two contrasting climate simulations. This results from the exponentially increasing warming requirements for leaf out when winter chilling falls below a threshold as shown by a comparison with models that consider only spring warming. The model evaluation suggests an element of regional adaptation of the warming required for leaf out in large biomes

Phenological rules for the leaf out date in temperate and boreal Biomes determined from NDVI

Phenological rules for the leaf out date in temperate and boreal Biomes determined from NDV

Radiative transfer modeling of direct and diffuse sunlight in a Siberian pine forest

We have expanded the Monte Carlo, ray-tracing model FLIGHT in order to simulate photosynthesis within three-dimensional, heterogeneous tree canopies. In contrast to the simple radiative transfer schemes adopted in many land-surface models (e.g., the Big Leaf approximation), our simulation calculates explicitly the leaf irradiance at different heights within the canopy and thus produces an accurate scale-up in photosynthesis from leaf to canopy level. We also account for both diffuse and direct sunlight. For a Siberian stand of Scots pine Pinus sylvestris, FLIGHT predicts observed carbon assimilation, across the full range of sky radiance, with an r.m.s. error of 12%. Our main findings for this sparse canopy, using both measurements and model, are as follows: (1) Observationally, we detect a light-use efficiency (LUE) increase of only ≤10% for the canopy when the proportion of diffuse sky radiance is 75% rather than 25%. The corresponding enhancement predicted by our simulations is 10–20%. With such small increases in LUE, our site will not assimilate more carbon on overcast days compared to seasonally equivalent sunny days; (2) the scale-up in photosynthesis from top-leaf to canopy is less than unity. The Big Leaf approximation, based on Beer's law and light-acclimated leaf nitrogen, overpredicts this scale-up by ≥60% for low sky radiance (≤500 μmolPAR m−2 s−1); (3) when leaf nitrogen is distributed so as to maximize canopy photosynthesis, the increase in the canopy carbon assimilation, compared with a uniform nitrogen distribution, is small (≅4%). Maximum assimilation occurs when the vertical gradient of leaf nitrogen is slightly shallower than that of the light profile