Water availability is the primary constraint to aboveground net primary productivity (ANPP) in many terrestrial biomes, and it is an ecosystem driver that will be strongly altered by future climate change. Global circulation models predict a shift in precipitation patterns to growing season rainfall events that are larger in size but fewer in number. This "repackaging" of rainfall into large events with long intervening dry intervals could be particularly important in semi-arid grasslands because it is in marked contrast to the frequent but small events that have historically defined this ecosystem. We investigated the effect of more extreme rainfall patterns on ANPP via the use of rainout shelters and paired this experimental manipulation with an investigation of long-term data for ANPP and precipitation. Experimental plots (n = 15) received the long-term (30-year) mean growing season precipitation quantity; however, this amount was distributed as 12, six, or four events applied manually according to seasonal patterns for May-September. The long-term mean (1940-2005) number of rain events in this shortgrass steppe was 14 events, with a minimum of nine events in years of average precipitation. Thus, our experimental treatments pushed this system beyond its recent historical range of variability. Plots receiving fewer, but larger rain events had the highest rates of ANPP (184 +/- 38 g m(-2)), compared to plots receiving more frequent rainfall (105 +/- 24 g m(-2)). ANPP in all experimental plots was greater than long-term mean ANPP for this system (97 g m(-2)), which may be explained in part by the more even distribution of applied rain events. Soil moisture data indicated that larger events led to greater soil water content and likely permitted moisture penetration to deeper in the soil profile. These results indicate that semi-arid grasslands are capable of responding immediately and substantially to forecast shifts to more extreme precipitation patterns.
Climate models predict, and empirical evidence confirms, that more extreme precipitation regimes are occurring in tandem with warmer atmospheric temperatures. These more extreme rainfall patterns are characterized by increased event size separated by longer within season drought periods and represent novel climatic conditions whose consequences for different ecosystem types are largely unknown. Here, we present results from an experiment in which more extreme rainfall patterns were imposed in three native grassland sites in the Central Plains Region of North America, USA. Along this 600 km precipitation-productivity gradient, there was strong sensitivity of temperate grasslands to more extreme growing season rainfall regimes, with responses of aboveground net primary productivity (ANPP) contingent on mean soil water levels for different grassland types. At the mesic end of the gradient (tallgrass prairie), longer dry intervals between events led to extended periods of below-average soil water content, increased plant water stress and reduced ANPP by 18%. The opposite response occurred at the dry end (semiarid steppe), where a shift to fewer, but larger, events increased periods of above-average soil water content, reduced seasonal plant water stress and resulted in a 30% increase in ANPP. At an intermediate mixed grass prairie site with high plant species richness, ANPP was most sensitive to more extreme rainfall regimes (70% increase). These results highlight the inherent complexity in predicting how terrestrial ecosystems will respond to forecast novel climate conditions as well as the difficulties in extending inferences from single site experiments across biomes. Even with no change in annual precipitation amount, ANPP responses in a relatively uniform physiographic region differed in both magnitude and direction in response to within season changes in rainfall event size/frequency.
Soil biota play key roles in the functioning of terrestrial ecosystems, however, compared to our knowledge of above-ground plant and animal diversity, the biodiversity found in soils remains largely uncharacterized. Here, we present an assessment of soil biodiversity and biogeographic patterns across Central Park in New York City that spanned all three domains of life, demonstrating that even an urban, managed system harbours large amounts of undescribed soil biodiversity. Despite high variability across the Park, below-ground diversity patterns were predictable based on soil characteristics, with prokaryotic and eukaryotic communities exhibiting overlapping biogeographic patterns. Further, Central Park soils harboured nearly as many distinct soil microbial phylotypes and types of soil communities as we found in biomes across the globe (including arctic, tropical and desert soils). This integrated cross-domain investigation highlights that the amount and patterning of novel and uncharacterized diversity at a single urban location matches that observed across natural ecosystems spanning multiple biomes and continents.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.