Grasslands account for a large proportion of global terrestrial productivity and play a critical role in carbon and water cycling. Within grasslands, photosynthetic pathway is an important functional trait yielding different rates of productivity along environmental gradients. Recently, C3-C4 sorting along spatial environmental gradients has been reassessed by controlling for confounding traits in phylogenetically structured comparisons. C3 and C4 grasses should sort along temporal environmental gradients as well, resulting in differing phenologies and growing season lengths. Here we use 10 years of satellite data (NDVI) to examine the phenology and greenness (as a proxy for productivity) of C3 and C4 grass habitats, which reflect differences in both environment and plant physiology. We perform phylogenetically structured comparisons based on 3,595 digitized herbarium collections of 152 grass species across the Hawaiian Islands. Our results show that the clade identity of grasses captures differences in their habitats better than photosynthetic pathway. Growing season length (GSL) and associated productivity (GSP) were not significantly different when considering photosynthetic type alone, but were indeed different when considering photosynthetic type nested within clade. The relationship between GSL and GSP differed most strongly between C3 clade habitats, and not between C3-C4 habitats. Our results suggest that accounting for the interaction between phylogeny and photosynthetic pathway can help improve predictions of productivity, as commonly used C3-C4 classifications are very broad and appear to mask important diversity in grassland ecosystem functions.
The Hawaiian Islands are an ideal location to study the response of tropical forests to climate variability because of their extreme isolation in the middle of the Pacific, which makes them especially sensitive to El Niño-Southern Oscillation (ENSO). Most research examining the response of tropical forests to drought or El Niño have focused on rainforests, however, tropical dry forests cover a large area of the tropics and may respond very differently than rainforests. We use satellite-derived Normalized Difference Vegetation Index (NDVI) from February 2000-February 2009 to show that rainforests and dry forests in the Hawaiian Islands exhibit asynchronous responses in leaf phenology to seasonal and El Niño-driven drought. Dry forest NDVI was more tightly coupled with precipitation compared to rainforest NDVI. Rainforest cloud frequency was negatively correlated with the degree of asynchronicity (Delta(NDVI)) between forest types, most strongly at a 1-month lag. Rainforest green-up and dry forest brown-down was particularly apparent during the 2002-003 El Niño. The spatial pattern of NDVI response to the NINO 3.4 Sea Surface Temperature (SST) index during 2002-2003 showed that the leeward side exhibited significant negative correlations to increased SSTs, whereas the windward side exhibited significant positive correlations to increased SSTs, most evident at an 8 to 9-month lag. This study demonstrates that different tropical forest types exhibit asynchronous responses to seasonal and El Niño-driven drought, and suggests that mechanisms controlling dry forest leaf phenology are related to water-limitation, whereas rainforests are more light-limited.
A number of studies have demonstrated the ecological sorting of C3 and C4 grasses along temperature and moisture gradients. However, previous studies of C3 and C4 grass biogeography have often inadvertently compared species in different and relatively unrelated lineages, which are associated with different environmental settings and distinct adaptive traits. Such confounded comparisons of C3 and C4 grasses may bias our understanding of ecological sorting imposed strictly by photosynthetic pathway. Here, we used MaxEnt species distribution modeling in combination with satellite data to understand the functional diversity of C3 and C4 grasses by comparing both large clades and closely related sister taxa. Similar to previous work, we found that C4 grasses showed a preference for regions with higher temperatures and lower precipitation compared with grasses using the C3 pathway. However, air temperature differences were smaller (2 °C vs. 4 °C) and precipitation and % tree cover differences were larger (1783 mm vs. 755 mm, 21.3% vs. 7.7%, respectively) when comparing C3 and C4 grasses within the same clade vs. comparing all C4 and all C3 grasses (i.e., ignoring phylogenetic structure). These results were due to important differences in the environmental preferences of C3 BEP and PACMAD clades (the two main grass clades). Winter precipitation was found to be more important for understanding the distribution and environmental niche of C3 PACMADs in comparison with both C3 BEPs and C4 taxa, for which temperature was much more important. Results comparing closely related C3 -C4 sister taxa supported the patterns derived from our modeling of the larger clade groupings. Our findings, which are novel in comparing the distribution and niches of clades, demonstrate that the evolutionary history of taxa is important for understanding the functional diversity of C3 and C4 grasses, and should have implications for how grasslands will respond to global change.
Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically "track" climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlier-active competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced their phenology with warming also increased their performance, whereas those that did not advance tended to decline in performance with warming. This indicates that species that cannot phenologically "track" climate may be at increased risk with future climate change, and it suggests that phenological monitoring may provide an important tool for setting future conservation priorities.
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