Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years.

Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of 'Drought-Net', a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites - a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process-level understanding of ecosystem sensitivity to precipitation extremes.

Occurrence and depositional history of organochlorine pesticides in the sediments of the Zayandehrud River in the arid region of Central Iran.

In this study, surface sediments along the Zayandehrud River (14 samples), and two dated core sediments (46 samples) from small artificial urban lakes at the middle section of the Zayandehrud River in the Gavkhooni basin in the central arid regions of Iran were analyzed for residual levels of 20 organochlorine pesticide (OCP) compounds. Total OCP concentrations ranged from 0.1 to 50.1 ng g-1 dry weight and from 1.9 to 51.5 ng g-1 dry weight in surface and core sediments, respectively. Dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD) were found to be the predominant OCPs in these sediments. The calculated metabolic and isomeric ratios confirmed the aged nature of residual dichlorodiphenyltrichloroethane (DDT) in sediments. Moreover, the isomeric ratios indicated the aged nature of technical HCH (hexachlorocyclohexane), while the contribution of γ- HCH (lindane) as a main source has increased, especially in the last two decades. Past usage, as well as current usage of endosulfan technical mixture in the Gavkhooni basin, has been found in the last four decades. Analyses of sedimentary cores, as natural archives, have shown the successful ban on the use of organochlorine pesticides (especially DDT) in the Gavkhooni basin, and to some extent, in the central plateau of Iran. In general, it can be concluded that natural factors (i.e., floods and wet years) lead to soil leachate and play an essential role in remobilization and transfer of residual OCPs from soil to inland aquatic ecosystems in the Gavkhooni basin, which is an arid region.