Search for: All records

In dryland soils, spatiotemporal variation in surface soils (0–10 cm) plays an important role in the function of the “critical zone” that extends from canopy to groundwater. Understanding connections between soil microbes and biogeochemical cycling in surface soils requires repeated multivariate measurements of nutrients, microbial abundance, and microbial function. We examined these processes in resource islands and interspaces over a two‐month period at a Chihuahuan Desert bajada shrubland site. We collected soil inProsopis glandulosa(honey mesquite),Larrea tridentata(creosote bush), and unvegetated (interspace) areas to measure soil nutrient concentrations, microbial biomass, and potential soil enzyme activity. We monitored the dynamics of these belowground processes as soil conditions dried and then rewetted due to rainfall. Most measured variables, including inorganic nutrients, microbial biomass, and soil enzyme activities, were greater under shrubs during both wet and dry periods, with the highest magnitudes under mesquite followed by creosote bush and then interspace. One exception was nitrate, which was highly variable and did not show resource island patterns. Temporally, rainfall pulses were associated with substantial changes in soil nutrient concentrations, though resource island patterns remained consistent during all phases of the soil moisture pulse. Microbial biomass was more consistent than nutrients, decreasing only when soils were driest. Potential enzyme activities were even more consistent and did not decline in dry periods, potentially helping to stimulate observed pulses in CO₂efflux following rain events observed at a co‐located eddy flux tower. These results indicate a critical zone with organic matter cycling patterns consistently elevated in shrub resource islands (which varied by shrub species), high decomposition potential that limits soil organic matter accumulation across the landscape, and nitrate fluxes that are decoupled from the organic matter pathways.

Synchrony is broadly important to population and community dynamics due to its ubiquity and implications for extinction dynamics, system stability, and species diversity. Investigations of synchrony in community ecology have tended to focus on covariance in the abundances of multiple species in a single location. Yet, the importance of regional environmental variation and spatial processes in community dynamics suggests that community properties, such as species richness, could fluctuate synchronously across patches in a metacommunity, in an analog of population spatial synchrony. Here, we test the prevalence of this phenomenon and the conditions under which it may occur using theoretical simulations and empirical data from 20 marine and terrestrial metacommunities. Additionally, given the importance of biodiversity for stability of ecosystem function, we posit that spatial synchrony in species richness is strongly related to stability. Our findings show that metacommunities often exhibit spatial synchrony in species richness. We also found that richness synchrony can be driven by environmental stochasticity and dispersal, two mechanisms of population spatial synchrony. Richness synchrony also depended on community structure, including species evenness and beta diversity. Strikingly, ecosystem stability was more strongly related to richness synchrony than to species richness itself, likely because richness synchrony integrates information about community processes and environmental forcing. Our study highlights a new approach for studying spatiotemporal community dynamics and emphasizes the spatial dimensions of community dynamics and stability.

Regional long‐term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space‐for‐time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, regions defined by the scarcity of water that cover 45% of Earth's land surface and face increasingly drier and more variable climates. We analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland ecosystems in the southwestern USA. Two time series (1995–2006 and 2004–2013) coincided with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20%–35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004–2013, with losses of 5% of animals captured. During the first time series (wetter climate), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (drier climate), climate best explained variation in abundance for 60% of taxa. Temporal dynamics in diversity and abundance differed spatially among ecosystems, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Which species were winners or losers under increasing drought and amplified interannual variability in drought depended on ecosystem type and the phase of the PDO. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among ecosystems for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995–2013. Whether these changes portend future declines in drought‐sensitive consumers in the southwestern USA will depend on the climate during the next major PDO cycle.

Shrub encroachment is transforming arid and semiarid grasslands worldwide. Such transitions should influence predator–prey interactions because vegetation cover often affects risk perception by prey and contributes to their landscape of fear. We examined how the landscape of fear of two desert lagomorphs (black‐tailed jackrabbit,Lepus californicus; desert cottontail,Sylvilagus audubonii) changes across grassland‐to‐shrubland gradients at Jornada Basin Long Term Ecological Research site in the Chihuahuan Desert of southern New Mexico. We test whether shrub encroachment shapes risk differently for these two lagomorphs because of differences in body size and predator escape tactics. We also examine whether an ecosystem engineer of grasslands (banner‐tailed kangaroo rat,Dipodomys spectabilis) mediates risk perception through the creation of escape refuge and whether trade‐offs exist between shrub encroachment and the local reduction of banner‐tailed kangaroo rats caused by shrub expansion. We measured perceived predation risk with flight initiation distances (FIDs) and then used structural equation modeling to tease apart the hypothesized direct and indirect pathways for how shrub encroachment could affect perceived risk. A total negative effect of shrub cover on FID was supported for jackrabbits and cottontails, suggesting both species perceive shrubbier habitat as safer. Increases in fine‐scale concealment also reduced risk for cottontails, but not jackrabbits, likely because cottontails rely on crypsis to avoid predator detection whereas jackrabbits rely on speed and agility to outrun predators. Perceived risk was reduced when individuals were near kangaroo rat mounds only for cottontails because the smaller species can use banner‐tailed kangaroo rat mounds as refuge. Shrub encroachment greatly reduced the availability of mounds. Thus, a trade‐off exists for cottontails in which shrub encroachment directly reduced perceived risk, but indirectly increased perceived risk through the local extirpation of an ecosystem engineer. Our work illustrates how the expansion of shrub encroachment can create a dynamic landscape of fear for populations of prey species involving direct and indirect pathways contingent on prey body size, escape tactics, and activities of an ecosystem engineer.

Drone-based multispectral sensing is a valuable tool for dryland spatial ecology, yet there has been limited investigation of the reproducibility of measurements from drone-mounted multispectral camera array systems or the intercomparison between drone-derived measurements, field spectroscopy, and satellite data. Using radiometrically calibrated data from two multispectral drone sensors (MicaSense RedEdge (MRE) and Parrot Sequoia (PS)) co-located with a transect of hyperspectral measurements (tramway) in the Chihuahuan desert (New Mexico, USA), we found a high degree of correspondence within individual drone data sets, but that reflectance measurements and vegetation indices varied between field, drone, and satellite sensors. In comparison to field spectra, MRE had a negative bias, while PS had a positive bias. In comparison to Sentinel-2, PS showed the best agreement, while MRE had a negative bias for all bands. A variogram analysis of NDVI showed that ecological pattern information was lost at grains coarser than 1.8 m, indicating that drone-based multispectral sensors provide information at an appropriate spatial grain to capture the heterogeneity and spectral variability of this dryland ecosystem in a dry season state. Investigators using similar workflows should understand the need to account for biases between sensors. Modelling spatial and spectral upscaling between drone and satellite data remains an important research priority.