It's generally assumed that in most grasslands these events reduce grass production, yet their effects have been viewed somewhat monolithically. When it comes to forecasting the consequences of future climate variability, droughts and heat waves in early-, mid-, or late-summer are not viewed very differently. Absence of evidence is not necessarily evidence of absence though.
The Konza LTER has built up datasets over the past 25 years that can really test this, though.
27 years of annual productivity
27 years of daily weather
27 years of daily stream discharge
27 years of biweekly soil moisture
17 years of biweekly productivity
11 years of remotely-sensed NDVI
I'll write about some of the datasets another time, but if one examines the annual productivity data and the climate data together with the critical climate period approach, it is clear that the timing of climate variability is just as important--if not more--than the magnitude.
First, grass productivity only responds to drought (or the converse precipitation) during part of the growing season (Apr 10-Aug 2). Drought in August doesn't reduce primary productivity.
And heat waves? They only reduce productivity during a 25-d window. Jul 10 - Aug 2. Heat waves in August, no less June, just have no impact on productivity.
We can use these data to come up with new relationships between productivity and climate variability.
A couple of lessons can be learned here, but the most striking is that droughts and heat waves in August just don't affect grass production. It's not that grasses aren't growing then. About 10% of the production happens then and in some years it can be as high as a third of the mean annual productivity. Yet, growth during that time is not tied to climate then.
It's hard to explain why this is so, but the practical consequences are clear. If droughts or heat waves are more likely to happen in August, it doesn't matter for the amount of grass we have. We've shown elsewhere it still impacts the bison, most likely because they cue in on grass quality than quantity. But ANPP is insensitive. If we want to predict future productivity well, they we better know timing as well as magnitude.
**On a side note, the results are really the highest expression of what the LTER approach can accomplish. I think long-term datasets have fallen out of fashion in the ecological community. When was the last time Science or Nature published a paper that centered on a long time-series from an LTER site. Compared to experiments, models, and cross-site synthesis, long time series seems like a short leg of the table these days. No one has ever set up an experiment to test what natural variability has shown us about the timing of variability.