Aboveground net primary production (ANPP) dynamics are a key element in the understanding of ecosystem processes. For semiarid environments, the pulse-reserve framework links ANPP to variable and unpredictable precipitation events contingent on surficial hydrology, soil moisture dynamics, biodiversity structure, trophic dynamics, and landscape context. Consequently, ANPP may be decoupled periodically from processes such as decomposition and may be subjected to complex feedbacks and thresholds at broader scales. As currently formulated, the pulse-reserve framework may not encompass the breadth of ANPP response to seasonal patterns of precipitation and heat inputs. Accordingly, we examined a 6-year (1999-2004), seasonal record of ANPP with respect to precipitation, soil moisture dynamics, and functional groups in a black grama (Bouteloua eriopoda) grassland and a creosotebush (Larrea tridentata) shrubland in the northern Chihuahuan Desert. Annual ANPP was similar in the grassland (51.1 g/m(2)) and shrubland (59.2 g/m(2)) and positively correlated with annual precipitation. ANPP differed among communities with respect to life forms and functional groups and responses to abiotic drivers. In keeping with the pulse-reserve model, ANPP in black grama grassland was dominated by warm-season C(4) grasses and subshrubs that responded to large, transient summer storms and associated soil moisture in the upper 30 cm. In contrast, ANPP in creosotebush shrubland occasionally responded to summer moisture, but the predominant pattern was slower, non-pulsed growth of cool-season C(3) shrubs during spring, in response to winter soil moisture accumulation and the breaking of cold dormancy. Overall, production in this Chihuahuan Desert ecosystem reflected a mix of warm-temperate arid land pulse dynamics during the summer monsoon and non-pulsed dynamics in spring driven by winter soil moisture accumulation similar to that of cool-temperate regions.

Summary Severe or extreme droughts occurred about 10% of the time over a 105‐year record from central New Mexico, U.S.A., based on the Palmer Drought Severity Index. Drought lowers water tables, creating extensive areas of groundwater recharge and fragmenting reaches of streams and rivers. Deeper groundwater inputs predominate as sources of surface flows during drought. Nutrient inputs to streams and rivers reflect the biogeochemistry of regional ground waters with longer subsurface residence times. Inputs of bioavailable dissolved organic carbon to surface waters decrease during drought, with labile carbon limitation of microbial metabolism a byproduct of drought conditions. Decreased inputs of organic forms of carbon, nitrogen and phosphorus and a decrease in the organic : inorganic ratio of nutrient inputs favours autotrophs over heterotrophs during drought. The fate of autotrophic production during drought will be strongly influenced by the structure of the aquatic food web within impacted sites.

Understanding controls on net primary production (NPP) has been a long-standing goal in ecology. Climate is a well-known control on NPP, although the temporal differences among years within a site are often weaker than the spatial pattern of differences across sites. Climate sensitivity functions describe the relationship between an ecological response (e.g., NPP) and both the mean and variance of its climate driver (e.g., aridity index), providing a novel framework for understanding how climate trends in both mean and variance vary with NPP over time. Nonlinearities in these functions predict whether an increase in climate variance will have a positive effect (convex nonlinearity) or negative effect (concave nonlinearity) on NPP. The influence of climate variance may be particularly intense at ecosystem transition zones, if species reach physiological thresholds that create nonlinearities at these ecotones. Long-term data collected at the confluence of three dryland ecosystems in central New Mexico revealed that each ecosystem exhibited a unique climate sensitivity function that was consistent with long-term vegetation change occurring at their ecotones. Our analysis suggests that rising temperatures in drylands could alter the nonlinearities that determine the relative costs and benefits of variance in precipitation for primary production.

Measuring environmental variables at appropriate temporal and spatial scales remains an important challenge in ecological research. New developments in wireless sensors and sensor networks will free ecologists from a wired world and revolutionize our ability to study ecological systems at relevant scales. In addition, sensor networks can analyze and manipulate the data they collect, thereby moving data processing from the end user to the sensor network itself. Such embedded processing will allow sensor networks to perform data analysis procedures, identify outlier data, alter sampling regimes, and ultimately control experimental infrastructure. We illustrate this capability using a wireless sensor network, the Sensor Web, in a study of microclimate variation under shrubs in the Chihuahuan Desert. Using Sensor Web data, we propose simple analytical protocols for assessing data quality “on‐the‐fly” that can be programmed into sensor networks. The ecological community can influence the evolution of environmental sensor networks by working across disciplines to infuse new ideas into sensor network development.

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