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Aims: This study investigates how precipitation, temperature and seasonality (as a proxy of plant productivity) affect the temporal and spatial variability of soil CO2 efflux in two dry semiarid grasslands with different degrees of land degradation. Methods: We measured soil CO2 efflux over four years under plant, biological soil crust and bare soil patches and estimated annual soil carbon losses in both, a natural and a degraded grassland, by means of generalised additive mixed models considering temporal autocorrelation in the data. Results: Soil CO2 efflux ranged from 0.08 to 3.70 and from 0.10 to 3.01 μmol CΟ2 m−2 s−1 in the natural and degraded grasslands, respectively. Daily soil CO2 efflux was mostly affected by moisture in the degraded grassland (25.4%), while in the natural grassland was affected jointly by seasonality, temperature and moisture (27.5%). Overall, the highest soil carbon fluxes were measured in soils covered by biological soil crusts (1.24 ± 0.02 and 1.10 ± 0.02) and the lowest in bare soils (1.11 ± 0.02 and 0.82 ± 0.02 μmol CΟ2−2 s−1) in the natural and degraded sites, respectively. Cumulative soil carbon fluxes were mainly driven by temperature and previous precipitation (over three months). The highest soil carbon losses were estimated in the driest year (2009) and the lowest in the wettest (2010) with almost twice the amount of rainfall. The main difference between these years was the timing of the events that mostly occurred in the moments of maximum plant activity with optimum temperatures in spring in the dry year. Conclusions: Changes in precipitation patterns will affect soil carbon fluxes more than rainfall amount, particularly in degraded grasslands. Therefore, considering all climate drivers together with plant activity is essential to predict how climate change will affect soil biological processes in drylands. [ABSTRACT FROM AUTHOR]

The spatial and temporal variation in population sizes of animal colonies are rarely studied simultaneously. I examined factors determining colony size (number of nests) for 23 colonies from the only breeding population of rook Corvus frugilegus in Spain over 7 years. Population sizes within colonies were highly predictable over time, with autocorrelations up to a distance (lag) of 6 years. Autoregressive mixed models were used to explain colony size as a function of environmental factors, while controlling for temporal autocorrelation. These factors included refuse tips, widely used as food resource, and a derived variable that incorporated the two factors most often related to avian colony size (inter-colony competition and foraging habitat around colonies). Autoregressive models provided a better fit to the data than models which did not consider temporal autocorrelation. The information-theoretic (AICc-based) approach revealed uncertainty in the selection of the best model explaining colony-size, but relatively strong support for certain variables. The highest weights of evidence were for year ( ω i = 0.90) and the number of competitors per unit of foraging habitat (i.e., derived variable; ω i = 0.63), showing that the size of rook colonies in Spain was negatively affected by inter-colony competition relative to the foraging habitat surrounding the colonies. This variable measured within a 6-km radius from the colonies had ~30 times higher weight of evidence (more plausible) than the same variable measured within 3 km, indicating that food limitation may occur outside the breeding period. Sizes of colonies tended to decrease when distance between the colony and the nearest refuse tip increased. There was some evidence supporting the idea that the effect of the number of competitors per unit of foraging habitat on colony size varied from year to year, but statistical power was weak. These findings suggest that variation in number of rook nests within colonies reflects spatial and temporal heterogeneity of net food via both inter-colony competition and foraging habitat around the colony. [ABSTRACT FROM AUTHOR]