@article{WebberLischeidSommeretal.2020,
  author    = {Webber, Heidi and Lischeid, Gunnar and Sommer, Michael and Finger, Robert and Nendel, Claas and Gaiser, Thomas and Ewert, Frank},
  title     = {No perfect storm for crop yield failure in Germany},
  series = {Environmental research letters},
  volume    = {15},
  journal   = {Environmental research letters},
  number    = {10},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/aba2a4},
  pages     = {14},
  year      = {2020},
  abstract  = {Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management (pest, weed and nutrient management and possible interactions with weather) explaining yield failures. Models to inform adaptation planning at farm, market or policy levels are here suggested to require consideration of cumulative resource capture and use, as well as effects of extreme events, the latter largely missing in process-based models. However, increasingly novel combinations of weather events under climate change may limit the extent to which data driven methods can replace process-based models in risk assessments.},
  language  = {en}
}
@article{GilingNejstgaardBergeretal.2017,
  author    = {Giling, Darren P. and Nejstgaard, Jens C. and Berger, Stella A. and Grossart, Hans-Peter and Kirillin, Georgiy and Penske, Armin and Lentz, Maren and Casper, Peter and Sareyka, Joerg and Gessner, Mark O.},
  title     = {Thermocline deepening boosts ecosystem metabolism: evidence from a large-scale lake enclosure experiment simulating a summer storm},
  series = {Global change biology},
  volume    = {23},
  journal   = {Global change biology},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1354-1013},
  doi       = {10.1111/gcb.13512},
  pages     = {1448 -- 1462},
  year      = {2017},
  abstract  = {Extreme weather events can pervasively influence ecosystems. Observations in lakes indicate that severe storms in particular can have pronounced ecosystem-scale consequences, but the underlying mechanisms have not been rigorously assessed in experiments. One major effect of storms on lakes is the redistribution of mineral resources and plankton communities as a result of abrupt thermocline deepening. We aimed at elucidating the importance of this effect by mimicking in replicated large enclosures (each 9 m in diameter, ca. 20 m deep, ca. 1300 m 3 in volume) a mixing event caused by a severe natural storm that was previously observed in a deep clear-water lake. Metabolic rates were derived from diel changes in vertical profiles of dissolved oxygen concentrations using a Bayesian modelling approach, based on high-frequency measurements. Experimental thermocline deepening stimulated daily gross primary production (GPP) in surface waters by an average of 63\% for > 4 weeks even though thermal stratification re-established within 5 days. Ecosystem respiration (ER) was tightly coupled to GPP, exceeding that in control enclosures by 53\% over the same period. As GPP responded more strongly than ER, net ecosystem productivity (NEP) of the entire water column was also increased. These protracted increases in ecosystem metabolism and autotrophy were driven by a proliferation of inedible filamentous cyanobacteria released from light and nutrient limitation after they were entrained from below the thermocline into the surface water. Thus, thermocline deepening by a single severe storm can induce prolonged responses of lake ecosystem metabolism independent of other storm-induced effects, such as inputs of terrestrial materials by increased catchment run-off. This highlights that future shifts in frequency, severity or timing of storms are an important component of climate change, whose impacts on lake thermal structure will superimpose upon climate trends to influence algal dynamics and organic matter cycling in clear-water lakes. Keywords: climate variability, ecosystem productivity, extreme events, gross primary production, mesocosm, respiration stratified lakes},
  language  = {en}
}