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Differences in litter quality, microbial activity or abiotic conditions cannot fully account for the variability in decomposition rates observed in semiarid ecosystems. Here we tested the role of variation in litter quality, water supply, and UV radiation as drivers of litter decomposition in arid lands. And show that carry-over effects of litter photodegradation during dry periods can regulate decomposition during subsequent wet periods. We present data from a two-phase experiment, where we first exposed litter from a drought-deciduous and an evergreen shrub to natural UV levels during five, rainless summer months and, subsequently, in the laboratory, we assessed the carry-over effects of photodegradation on biomass loss under different irrigation treatments representing the observed range of local rainfall variation among years (15–240 mm). Photodegradation of litter in the field produced average carbon losses of 12%, but deciduous  Proustia pungens  lost >25%, while evergreen  Porlieria chilensis  less than 5%. Natural exposure to UV significantly reduced carbon-to-nitrogen and lignin:N ratios in  Proustia  litter but not in  Porlieria . During the subsequent wet phase, remaining litter biomass was lower in  Proustia  than in  Porlieria . Indeed UV exposure increased litter decomposition of  Proustia  under low and medium rainfall treatments, whereas no carry-over effects were detected under high rainfall treatment. Consequently, for deciduous  Proustia  carry-over effects of UV exposure were negligible under high irrigation. Litter decomposition of the evergreen  Porlieria  depended solely on levels of rainfall that promote microbial decomposers. Our two-phase experiment revealed that both the carry-over effects of photodegradation and litter quality, modulated by inter-annual variability in rainfall, can explain the marked differences in decomposition rates and the frequent decoupling between rainfall and litter decomposition observed in semiarid ecosystems.

Understanding litter decomposition in semiarid ecosystems: linking leaf traits, UV exposure and rainfall variability