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 (y), soil respiration (R s ), along with leaf-level photosynthesis (A net ), predawn leaf water potential (C pd ), and seasonal aboveground net primary productivity (ANPP) of the dominant C 4 grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil y 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.

Statistical models for estimating absolute densities of field populations of animals have been widely used over the last century in both scientific studies and wildlife management programs. To date, two general classes of density estimation models have been developed: models that use data sets from capture–recapture or removal sampling techniques (often derived from trapping grids) from which separate estimates of population size (NÌ‚) and effective sampling area (AÌ‚) are used to calculate density (DÌ‚ = NÌ‚/AÌ‚); and models applicable to sampling regimes using distance‐sampling theory (typically transect lines or trapping webs) to estimate detection functions and densities directly from the distance data. However, few studies have evaluated these respective models for accuracy, precision, and bias on known field populations, and no studies have been conducted that compare the two approaches under controlled field conditions. In this study, we evaluated both classes of density estimators on known densities of enclosed rodent populations. Test data sets (n = 11) were developed using nine rodent species from capture–recapture live‐trapping on both trapping grids and trapping webs in four replicate 4.2‐ha enclosures on the Sevilleta National Wildlife Refuge in central New Mexico, USA. Additional “saturation” trapping efforts resulted in an enumeration of the rodent populations in each enclosure, allowing the computation of true densities. Density estimates (DÌ‚) were calculated using program CAPTURE for the grid data sets and program DISTANCE for the web data sets, and these results were compared to the known true densities (D) to evaluate each model's relative mean square error, accuracy, precision, and bias. In addition, we evaluated a variety of approaches to each data set's analysis by having a group of independent expert analysts calculate their best density estimates without a priori knowledge of the true densities; this “blind” test allowed us to evaluate the influence of expertise and experience in calculating density estimates in comparison to simply using default values in programs CAPTURE and DISTANCE. While the rodent sample sizes were considerably smaller than the recommended minimum for good model results, we found that several models performed well empirically, including the web‐based uniform and half‐normal models in program DISTANCE, and the grid‐based models Mb and Mbh in program CAPTURE (with AÌ‚ adjusted by species‐specific full mean maximum distance moved (MMDM) values). These models produced accurate DÌ‚ values (with 95% confidence intervals that included the true D values) and exhibited acceptable bias but poor precision. However, in linear regression analyses comparing each model's DÌ‚ values to the true D values over the range of observed test densities, only the web‐based uniform model exhibited a regression slope near 1.0; all other models showed substantial slope deviations, indicating biased estimates at higher or lower density values. In addition, the grid‐based DÌ‚ analyses using full ...

Climate models suggest that extreme rainfall events will become more common with increased atmospheric warming. Consequently, changes in the size and frequency of rainfall will influence biophysical drivers that regulate the strength and timing of soil CO2 efflux – a major source of terrestrial carbon flux. We used a rainfall manipulation experiment during the summer monsoon season (July–September) to vary both the size and frequency of precipitation in an arid grassland 2 years before and 2 years after a lightning‐caused wildfire. Soil CO2 efflux rates were always higher under increased rainfall event size than under increased rainfall event frequency, or ambient precipitation. Although fire reduced soil CO2 efflux rates by nearly 70%, the overall responses to rainfall variability were consistent before and after the fire. The overall sensitivity of soil CO2 efflux to temperature (Q10) converged to 1.4, but this value differed somewhat among treatments especially before the fire. Changes in rainfall patterns resulted in differences in the periodicity of soil CO2 efflux with strong signals at 1, 8, and 30 days. Increased rainfall event size enhanced the synchrony between photosynthetically active radiation and soil CO2 efflux over the growing season before and after fire, suggesting a change in the temporal availability of substrate pools that regulate the temporal dynamics and magnitude of soil CO2 efflux. We conclude that arid grasslands are capable of rapidly increasing and maintaining high soil CO2 efflux rates in response to increased rainfall event size more than increased rainfall event frequency both before and after a fire. Therefore, the amount and pattern of multiple rain pulses over the growing season are crucial for understanding CO2 dynamics in burned and unburned water‐limited ecosystems.

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

Burrowing, herbivorous mammals play important roles as ecosystem engineers and keystone species of grassland ecosystems around the world, but populations of many species have declined dramatically because of myriad threats from human activities. Prairie dogs (Cynomys spp.) play important roles in shaping the central grasslands of North America, and have declined by about 98% across their range, with consequent losses in associated species and grassland habitat. This has prompted much interest in restoring their populations to protected areas. Managers lack a clear understanding of the long‐term success of reintroductions, however, and how success may vary across different species of prairie dogs and their widespread geographic ranges. We reintroduced over 1,000 Gunnison's prairie dogs (C. gunnisoni) to a semi‐arid grassland ecosystem in the southern portion of their range in central New Mexico, USA, and used standard capture–recapture methods to study their population dynamics over a period of 8 years. Mean adult survival was 27% over the course of the study, with precipitation identified as the primary driver of survival. Estimated survival was below 12% during severe drought periods and during the first few years following initial reintroduction, the latter likely because of high predation. Consequently, multiple releases of animals were required to prevent extirpation, and the long‐term sustainability of this population remains questionable. Over the 8 years of our study, our site experienced 4 severe droughts during spring, the key period for prairie dog mating, pregnancy, and lactation. Production of offspring at the site was low, likely because of the dry and variable conditions that occurred. We show that prairie dog restoration in semi‐arid grassland environments that are typical of the lower elevations and southern extent of their range may not succeed in producing viable colonies, and that dedicated management for multiple years is needed to counteract periods of slow or negative population growth. Our findings underscore the importance of maintaining and expanding existing colonies wherever possible in these more arid regions, and suggest that reintroductions should be treated as a secondary management strategy. Our work also reveals the high vulnerability of prairie dog population extinction due to drought, which has important implications for Gunnison's prairie dog conservation under a warming and drying climate. © 2014 The Wildlife Society.