We have seen that combining several ecological principles allows us to ‘predict’ some things we already know. As much as we would like to pat ourselves on the back, then pack our bags for the road trip to Stockholm to get our well-deserved Nobel prize for Ecology… we can't yet. To predict what we already know is too easy. It simply does not meet the criteria for even a “well-deserved” Grade School Science Fair Ribbon. We need to predict something we don't yet know. So, back to the drawing boards… so far we have attempted to account for distribution patterns of communities in a reasonably constant environment, specifically yesterday's. What if the environment isn't really all that constant? Many aspects of the environment do tend to be reasonably constant: soil structure, concentrations of chemicals, etc. However, every place I have visited, the locals have assured me that the current weather is not typical; it's never been this hot/cold or wet/dry for as long as the local claims to remember. So, what if global climate really can change? As soon as we realize we should ask this question, we discover that the global climate not only can change, it is changing now! The further back in time we look, across Geologic Time, we fail to find a time when global climate did not change. Yet our ‘fragile’ Ecosystems seems to have survived, even when confronted with seven major extinction events. How this is possible is the subject of the rest of this text.
Assuming you have successfully forgotten everything you learned in Junior High general science, or
physical science, the World has zones of prevailing wind regimes: equatorial calm (low pressure),
tropical (trade) winds (easterly), the ‘doldrums’ (high pressure), the temperate zone
westerlies, a sub-polar calm zone (low pressure), the polar easterlies, and the calm (high pressure)
at the poles.
Within these zones there are deviations from the zonal pattern. Mountains produce an orographic effect, the most spectacular of which is the leeward (down wind for you non-sailors) rain shadow. As air masses go up a mountain on the windward side, adiabatic cooling causes precipitation. On the other side of the mountain (leeward), the descending air masses are subjected to adiabatic warming, lower humidities, less precipitation and more evaporation. On top of this effect, we have ‘slope exposure.’ South-facing slopes get more sunlight due to the low angle between the ground surface and the incoming solar rays, while the north-facing slopes get less sunlight. To simplify this, imagine a circular beam of sun light with an area of 1 square meter (diameter equals approximately 636 mm [25.1 inches]) with an intensity of 1,370 watts per square meter (W m-2 (the solar constant at the Earth surface [downloaded 10 Mar 2011 from Australian Government IPS Radio and Space Servives] A sheet of paper perpendicular to this beam will receive 1,370 W m-2 of solar energy. The same piece of paper lying on flat ground at 36°N (Durham NC, Tulsa OK, Las Vegas NV) at noon on the equinox will be at 54° to the sun ray, and will receive 796 W m-2. If we tilt the paper 5° (on a south-facing slope), it will receive 706 W m-2; and at 5° (on a north-facing slope), it will receive only 119 W m-2, so the north facing slope receives 16.9% of the energy received by a south-facing slope at the same time.
In mountainous regions, nighttime cool air tends to flow down canyons, producing valley fog. Thunderstorms tend to move around high terrain, following the lower ground (it takes more energy to climb a hill, or mountain, than to follow a valley), so the lower ground receives more precipitation and the precipitation on the higher ground flows as ‘runoff’ toward the lower ground. Downwind from a mountain range (even almost 1,000 km [620 miles]), the local climate depends on the global climate zones, and topographic effects. [The reduced rainfall caused by the rain shadow of the Rocky Mountains extends most of the way across Kansas, where the influence of Gulf of Mexico moisture transported by winds extends to the upper Great Lakes].
I stated above that climate change is occurring now. If this were true, we ought to be able to
see it. Using data from the STATE CLIMATE OFFICE OF NORTH CAROLINA; NC CRONOS Database, for the northern
Piedmont region, covering the time frame A.D. 1895 to 2010, we can examine the patterns in a 116-year
record of climate [which closely matches the time during which Human activity is supposed to have become
a significant influence on the climate].
The thin gray line is the actual, observed annual average temperature. I fitted (statistically) three cosine curves [cycle lengths of 950 years, 80 years, and 12 years; each of which has been mentioned in various published papers as natural cycles in climate driven by cycles in the solar constant]. The thicker black line in the graph is the sum of these three cycles. There is a statistically significant correlation (95% confidence) between the sum of the cosine curves and the observed climate data. I also statistically fitted (a least squares linear regression) a linear equation, and an exponential (‘hockey stick,’) curved line to the residual variation in the temperature data [“residual variation” is that variation which is not “explained” by the 3 natural cycles, calculated by substracting the statistical curves from the raw data], to account for the Human influence. Both of these lines (which are not shown in the graph) are not significant at the 95% confidence level.
Not only can we conclude that this describes the climate variations over the 116 years for which we have data, but we can project the curve into the past and the future (The caveat to such projections is that confidence declines as you move further from the data set). Within 50% or so of the data range are as accurate as any weather forecast, so we can assume that the curves are ‘accurate’ from 1837 to 2068. From 1815 to 2090 [adding one 80-year cycle on each end of the data, the projected values would be comparable to weather forecasts for a few months into the future. If we add one 950-year cycle on each end of the data (A.D. 945 to 2960), while tempting, has very low confidence [unless there are other data to confirm the projectiion to the past, and such data do exist in historic descriptions of general climate (the “Little Ice Age”), in cultural anthropology descriptions of the general climate (the “Medieval Warm Period”)…]. Thus we can conclude that this graph accurately portrays the climatic regime in which plant communities have to function in order to persist.
© 2010 TwoOldGuys
revised: 09 Mar 2011