Abstract
Abstract. Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.
Highlights
Precipitation (P ) is a key climatic determinant of ecosystem productivity, especially in arid and semi-arid grasslands (Lambers et al, 2008; Sala et al, 1988; Hsu et al, 2012; Beer et al, 2010)
Under normal range of precipitation variability, wet years typically result in aboveground net primary productivity (NPP) (ANPP) gains being larger than ANPP declines in dry years, whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought
Ensemble model results indicate that the slopes of the spatial relationships were steeper than the temporal slopes for gross primary productivity (GPP), NPP and ANPP for the subset of models that simulated this flux, while these differences in slopes were less obvious for belowground NPP (BNPP) (Fig. 1)
Summary
Precipitation (P ) is a key climatic determinant of ecosystem productivity, especially in arid and semi-arid grasslands (Lambers et al, 2008; Sala et al, 1988; Hsu et al, 2012; Beer et al, 2010). Positive empirical relationships between grassland aboveground NPP (ANPP) and precipitation (P ) have been found in spatial gradients across sites (Sala et al, 1988) and from temporal variability at individual sites (Huxman et al, 2004; Knapp and Smith, 2001; Roy et al, 2001; Hsu et al, 2012). Possible mechanisms behind the steeper spatial relationship may be (1) a “vegetation constraint” reflecting the adaptation of plant communities over long timescales in such a way that grasslands make the best use of the typical water received from rainfall for growth (Knapp et al, 2017b) and (2) the spatial variation in structural and functional traits of ecosystems (soil properties, nutrient pools, plant and microbial community composition) that constrain local ANPP–P sensitivities (Lauenroth and Sala, 1992; Smith et al, 2009; Wilcox et al, 2016). For projecting the effect of climate change on grassland productivity in the near to mid-term (coming decades), inter-annual relationships are arguably more informative than spatial relationships because spatial relationships reflect long-term adaptation of ecosystems and Biogeosciences, 15, 3421–3437, 2018 www.biogeosciences.net/15/3421/2018/
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