Effects Of Interannual Climate Variability Research Articles

Climatic influences on fire in Araucaria araucana–Nothofagus forests in the Andean cordillera of south-central Chile

:Tree-ring records of fires were used to examine the effects of inter-annual climatic variability on fire occurrence in forests dominated by the fire-adapted Araucaria araucana in the Andes of south-central Chile. Instrumental as well as tree-ring proxy records of climate indicate that low moisture availability is the main factor influencing fire occurrence. Years of widespread fire are strongly associated with warmer and drier summers. Years of extensive fire also tend to be favoured by one or two preceding years of dry climatic conditions. The El Niño–Southern Oscillation (ENSO) and its strong influence over large-scale climatic features is an important factor promoting fire activity. Years of high fire activity coincide with warm and dry summers following El Niño events. Fire in the Araucarian region is strongly related to inter-annual climatic variation associated primarily with the coupled effect of ENSO events and variations in the intensity and latitudinal position of the southeast Pacific anticyclone.

Interannual Variability of Water Demand and Summer Climate in Albuquerque, New Mexico

Abstract The effects of interannual climate variability on water demand in Albuquerque, New Mexico, are assessed. This city provides an ideal setting for examining the effects of climate on urban water demand, because at present the municipal water supply is derived entirely from groundwater, making supply insensitive to short-term climate variability. There is little correlation between interannual variability of climate and total water demand—a result that is consistent with several previous studies. However, summertime residential demand, which composes about one-quarter of total annual demand in Albuquerque, is significantly correlated with summer-season precipitation and average daily maximum temperature. Furthermore, regressions derived from year-to-year changes in these variables are shown to isolate the climatic modulation of residential water demand effectively. Over 60% of the variance of year-to-year changes in summer residential demand is accounted for by interannual temperature and precipitation changes when using a straightforward linear regression model, with precipitation being the primary correlate. Long-term trends in water demand follow population growth closely until 1994, after which time a major water conservation effort led to absolute decreases in demand in subsequent years. The effectiveness of the conservation efforts can be quantified by applying the regression model, thus removing the year-to-year variations associated with short-term climate fluctuations estimated from the preconservation period. The preconservation regression provides a good fit to interannual summer residential demand in subsequent years, demonstrating that the regression model has successfully isolated the climatic component of water demand. The quality of this fit during a period of sharply reduced demand suggests that the conservation program has effectively targeted the nonclimatically sensitive component of water demand and has sharpened the climatically sensitive component of demand to a level closer to the consumption that is “climatically needed.”

Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests

The effects of disturbance history, climate, and changes in atmospheric carbon dioxide (CO 2) concentration and nitrogen deposition (N dep) on carbon and water fluxes in seven North American evergreen forests are assessed using a coupled water–carbon–nitrogen model, canopy-scale flux observations, and descriptions of the vegetation type, management practices, and disturbance histories at each site. The effects of interannual climate variability, disturbance history, and vegetation ecophysiology on carbon and water fluxes and storage are integrated by the ecosystem process model Biome-BGC, with results compared to site biometric analyses and eddy covariance observations aggregated by month and year. Model results suggest that variation between sites in net ecosystem carbon exchange (NEE) is largely a function of disturbance history, with important secondary effects from site climate, vegetation ecophysiology, and changing atmospheric CO 2 and N dep. The timing and magnitude of fluxes following disturbance depend on disturbance type and intensity, and on post-harvest management treatments such as burning, fertilization and replanting. The modeled effects of increasing atmospheric CO 2 on NEE are generally limited by N availability, but are greatly increased following disturbance due to increased N mineralization and reduced plant N demand. Modeled rates of carbon sequestration over the past 200 years are driven by the rate of change in CO 2 concentration for old sites experiencing low rates of N dep. The model produced good estimates of between-site variation in leaf area index, with mixed performance for between- and within-site variation in evapotranspiration. There is a model bias toward smaller annual carbon sinks at five sites, with a seasonal model bias toward smaller warm-season sink strength at all sites. Various lines of reasoning are explored to help to explain these differences.

Parameters for global ecosystem models

Tian et al. reply — Our model-based analysis of the effects of interannual climate variability and increasing atmospheric CO2concentration on carbon storage in Amazonian ecosystems focused on CO2exchanges between the atmosphere and undisturbed forests and other upland eco-systems of the region1. Crutzen et al. urge us to add the emissions of isoprene and other volatile organic compounds (VOCs) to our analysis. They argue that ignoring these emissions could lead to an overestimation of annual net carbon storage (net ecosystem production) in the Amazon Basin.

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

The Amazon Basin contains almost one-half of the world's undisturbed tropical evergreen forest as well as large areas of tropical savanna1,2. The forests account for about 10 per cent of the world's terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems2,3, and short-term field measurements4 suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Nino episodes in recent decades5. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage6,7,8. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage9,10. Here we use a transient process-based biogeochemical model of terrestrial ecosystems3,11 to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Nino years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation inthe Amazon Basin in the early 1990s12. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Effects of interannual climate variability and climate change on rice yield in Java, Indonesia

Effects of interannual climate variability and climate change on rice yield in Java, Indonesia

The Climatic Sensitivity of ‘Green Revolution’ Wheat Culture in Sonora, Mexico

A statistical model was developed to assess the effects of interannual climatic variability on wheat yields in Sonora, Mexico, where the high-yielding variety (HYV) agricultural ‘package’ was first developed. The approach taken was necessary because of the lack of suitable ‘dynamic’ formulations. The climatic terms in the model—transformed monthly mean temperature and precipitation values—explain almost 37% of the variance in the yield time-series, after allowing for the simultaneously generated base and trend values. This figure is somewhat less than that in similar formulations for North American wheat, where the climatic and yield data may be more reliable.The yields are most sensitive to preplanting moisture input, when the irrigation system is being recharged, and to March temperature, when fertilization can be reduced by heat. The yield response to these two variables was found to increase significantly as more HYV agriculture is adopted. Increases are over twofold for the precipitation term, and nearly threefold for the temperature variable.A variety of arguments suggests that the results truly indicate an increased climatic sensitivity in the yieldresponse, although the formulation is incapable of discriminating between sensitivities that are purely ‘genetic’, and those associated with the cultural practices which the genetic change allows to be established. When impacts upon the consuming population are considered, the distinction between the two becomes somewhat less important.