By Zack Holden, USFS Scientist, Northern Region, Missoula, MT
It’s been fascinating to watch the 2011 climate year go by. The seasonal patterns we’ve observed in 2011 have had a real impact on many of us, both socially and ecologically. I’m still recovering from a delayed field season because of snow, and we’ve had almost no fire season until recently.
One interesting example is huckleberry production. Wayne Kasworm of the US Fish and Wildlife Service began monitoring annual huckleberry production in 1989. He’s been sampling berry production at transects across the Cabinet-Yaak grizzly bear recovery zone in northern Idaho and western Montana every year for the last 23 years. These kind of monitoring datasets are rare, and I’m grateful he had the discipline and vision to do what he did. Wayne’s data show a lot of interannual variation in berry production, but what causes that variation, and how well can it be explained by climatic variation? Some of our SNOTEL stations now have long enough records to be useful for analyzing historical patterns. I extracted a number of metrics from stations near Wayne’s berry transects. I calculated things like Growing Degree Days, precipitation, snow water equivalent and snow-off date. I also looked at monthly and seasonal temperature ranges. In the absence of actual humidity observations, this metric can be used as a proxy for atmospheric transmissivity and vapor pressure deficit. The figures below are from the Bandfield Mountain, MT station (Elev. 5300 ft).
We see some interesting correlations between berry production and temperature. Production is generally higher in years with cool springs (lower growing-degree days). We can only speculate as to why, but early snowmelt and warm springs could increase the likelihood of frost damage during flowering. We also see a reasonably strong relationship between berry production and the amount of solar radiation during the summer months. Attempts to grow wild berries domestically note the need for sunny conditions.
Using these 2 variables, we can develop a reasonable statistical model explains around 72% of annual berry production. The equivalence testing plot below (developed by Andrew Robinson, Remko Duursma and John Marshall at the U. Idaho) allows us to compare model predictions with actual berry observations each year. And a leave-one-out cross-validation tells us that we predict berry production with an RMSE of around .3 berrries/plot.
As we’ve learned from John’s climate summaries, it’s been a very cool spring and summer. Although the cool spring was good for berries, the summer wasn’t warm, dry or sunny enough to produce a good berry crop. The model above predicts around 20% below average production. However, in many places I’ve seen widespread berry failure. Vendors at the local farmers market have also reported a bad berry year. Perhaps coincidentally, there has been a lot of bear activity at low elevations this year and a number of bear-human encounters. There are no doubt other factors behind these bear activity patterns, but it’s interesting nonetheless to observe and explore potential connections between climate, vegetation and wildlife.
These results are from a paper that is now “accepted” in the journal: Wildlife Society Bulletin, with Wayne Kasworm, Chris Servheen, Beth Hahn and Solomon Dobrowski as coauthors.