Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982–2008

Changes in vegetative growing seasons are dominant indicators of the dynamic response of ecosystems to climate change. Therefore, knowledge of growing seasons over the past decades is essential to predict ecosystem changes. In this study, the long‐term changes in the growing seasons of temperate vegetation over the Northern Hemisphere were examined by analyzing satellite‐measured normalized difference vegetation index and reanalysis temperature during 1982–2008. Results showed that the length of the growing season (LOS) increased over the analysis period; however, the role of changes at the start of the growing season (SOS) and at the end of the growing season (EOS) differed depending on the time period. On a hemispheric scale, SOS advanced by 5.2 days in the early period (1982–1999) but advanced by only 0.2 days in the later period (2000–2008). EOS was delayed by 4.3 days in the early period, and it was further delayed by another 2.3 days in the later period. The difference between SOS and EOS in the later period was due to less warming during the preseason (January–April) before SOS compared with the magnitude of warming in the preseason (June–September) before EOS. At a regional scale, delayed EOS in later periods was shown. In North America, EOS was delayed by 8.1 days in the early period and delayed by another 1.3 days in the later period. In Europe, the delayed EOS by 8.2 days was more significant than the advanced SOS by 3.2 days in the later period. However, in East Asia, the overall increase in LOS during the early period was weakened in the later period. Admitting regional heterogeneity, changes in hemispheric features suggest that the longer‐lasting vegetation growth in recent decades can be attributed to extended leaf senescence in autumn rather than earlier spring leaf‐out.     

Effect of precipitation variability on net primary production and soil respiration in a Chihuahuan Desert grassland

Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water‐limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20 mm rain event each month, and (3) ambient rain plus four 5 mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content (θ), soil respiration (R_s), along with leaf‐level photosynthesis (A_net), predawn leaf water potential (Ψ_pd), and seasonal aboveground net primary productivity (ANPP) of the dominant C₄ grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil θ which corresponded with a significant increase in R_s and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle.     

Climate change effects on walnut pests in California

Increasing temperatures are likely to impact ectothermic pests of fruits and nuts. This paper aims to assess changes to pest pressure in California's US$0.7 billion walnut industry due to recent historic and projected future temperature changes. For two past (1950 and 2000) and 18 future climate scenarios (2041–2060 and 2080–2099; each for three General Circulation Models and three greenhouse gas emissions scenarios), 100 years of hourly temperature were generated for 205 locations. Degree‐day models were used to project mean generation numbers for codling moth (Cydia pomonella L.), navel orangeworm (Amyelois transitella Walker), two‐spotted spider mite (Tetranychus urticae Koch), and European red mite (Panonychus ulmi Koch). In the Central Valley, the number of codling moth generations predicted for degree days accumulated between April 1 and October 1 rose from 2–4 in 1950 to 3–5 among all future scenarios. Generation numbers increased from 10–18 to 14–24 for two‐spotted spider mite, from 9–14 to 14–20 for European red mite, and from 2–4 to up to 5 for navel orangeworm. Overall pest pressure can thus be expected to increase substantially. Our study did not include the possibility of higher winter survival rates, leading to higher initial pest counts in spring, or of extended pest development times in the summer, factors that are likely to exacerbate future pest pressure. On the other hand, initiation of diapause may prevent an extension of the season length for arthropods, and higher incidence of heat death in summer may constrain pest population sizes. More information on the impact of climate change on complex agroecological food webs and on the response of pests to high temperatures is needed for improving the reliability of projections.     

Reconciling the optimal and empirical approaches to modelling stomatal conductance

Models of vegetation function are widely used to predict the effects of climate change on carbon, water and nutrient cycles of terrestrial ecosystems, and their feedbacks to climate. Stomatal conductance, the process that governs plant water use and carbon uptake, is fundamental to such models. In this paper, we reconcile two long‐standing theories of stomatal conductance. The empirical approach, which is most commonly used in vegetation models, is phenomenological, based on experimental observations of stomatal behaviour in response to environmental conditions. The optimal approach is based on the theoretical argument that stomata should act to minimize the amount of water used per unit carbon gained. We reconcile these two approaches by showing that the theory of optimal stomatal conductance can be used to derive a model of stomatal conductance that is closely analogous to the empirical models. Consequently, we obtain a unified stomatal model which has a similar form to existing empirical models, but which now provides a theoretical interpretation for model parameter values. The key model parameter, g₁, is predicted to increase with growth temperature and with the marginal water cost of carbon gain. The new model is fitted to a range of datasets ranging from tropical to boreal trees. The parameter g₁ is shown to vary with growth temperature, as predicted, and also with plant functional type. The model is shown to correctly capture responses of stomatal conductance to changing atmospheric CO₂, and thus can be used to test for stomatal acclimation to elevated CO₂. The reconciliation of the optimal and empirical approaches to modelling stomatal conductance is important for global change biology because it provides a simple theoretical framework for analyzing, and simulating, the coupling between carbon and water cycles under environmental change.