Showing papers by "Riccardo Bommarco published in 2022"

Farm performance and input self-sufficiency increases with functional crop diversity on Swedish farms

Abstract: Diversified crop production is a key agroecological practice that enhances ecosystem functions and reduces reliance on costly external inputs, such as for plant protection and nutrition but might also increase labour costs and lower crop yields. We investigate if functional diversification, i.e., cultivation of crop species with contrasting ecological functions, is associated with a higher growth in farm economic performance and input self-sufficiency. This is compared with increased related crop diversity i.e., the cultivation of genetically closely related crop species. We apply the system GMM dynamic panel data estimator to 35,195 medium and large Swedish farms (2001–2018), combining information on crop grown on each field and year with farm financial and individual characteristics. We find growth in farm economic performance and input self-sufficiency to respond positively to functional crop diversification and negatively to related crop diversification. The results highlight that a decomposed assessment of crop diversification provides an enhanced understanding of the build-up of resource-use efficiencies and production- and market risk reductions on Swedish farms.

Beyond body size—new traits for new heights in trait-based modelling of predator-prey dynamics

Abstract: Food webs map feeding interactions among species, providing a valuable tool for understanding and predicting community dynamics. Using species’ body sizes is a promising avenue for parameterizing food-web models, but such approaches have not yet been able to fully recover observed community dynamics. Such discrepancies suggest that traits other than body size also play important roles. For example, differences in species’ use of microhabitat or non-consumptive effects of intraguild predators may affect dynamics in ways not captured by body size. In Laubmeier et al. (2018), we developed a dynamic food-web model incorporating microhabitat and non-consumptive predator effects in addition to body size, and used simulations to suggest an optimal sampling design of a mesocosm experiment to test the model. Here, we perform the mesocosm experiment to generate empirical time-series of insect herbivore and predator abundance dynamics. We minimize least squares error between the model and time-series to determine parameter values of four alternative models, which differ in terms of including vs excluding microhabitat use and non-consumptive predator-predator effects. We use both statistical and expert-knowledge criteria to compare the models and find including both microhabitat use and non-consumptive predator-predator effects best explains observed aphid and predator population dynamics, followed by the model including microhabitat alone. This ranking suggests that microhabitat plays a larger role in driving population dynamics than non-consumptive predator-predator effects, although both are clearly important. Our results illustrate the importance of additional traits alongside body size in driving trophic interactions. They also point to the need to consider trophic interactions and population dynamics in a wider community context, where non-trophic impacts can dramatically modify the interplay between multiple predators and prey. Overall, we demonstrate the potential for utilizing traits beyond body size to improve trait-based models and the value of iterative cycling between theory, data and experiment to hone current insights into how traits affect food-web dynamics.

The coordination of green–brown food webs and their disruption by anthropogenic nutrient inputs

Abstract: Abstract Aim Our goal was to quantify nitrogen flows and stocks in green–brown food webs in different ecosystems, how they differ across ecosystems and how they respond to nutrient enrichment. Location Global. Time period Contemporary. Major taxa studied Plants, phytoplankton, macroalgae, invertebrates, vertebrates and zooplankton. Methods Data from >500 studies were combined to estimate nitrogen stocks and fluxes in green–brown food webs in forests, grasslands, brackish environments, seagrass meadows, lakes and oceans. We compared the stocks, fluxes and metabolic rates of different functional groups within each food web. We also used these estimates to build a dynamical model to test the response of the ecosystems to nutrient enrichment. Results We found surprising symmetries between the green and brown channels across ecosystems, in their stocks, fluxes and consumption coefficients and mortality rates. We also found that nitrogen enrichment, either organic or inorganic, can disrupt this balance between the green and brown channels. Main conclusions Linking green and brown food webs reveals a previously hidden symmetry between herbivory and detritivory, which appears to be a widespread property of natural ecosystems but can be disrupted by anthropogenic nitrogen additions.

Coordinated evaporative demand and precipitation maximize rainfed maize and soybean crop yields in the USA

Abstract: To understand how climate change affects crop yields, we need to identify the climatic indices that best predict yields. Grain yields are most often predicted using precipitation and temperature in statistical models, assuming linear dependences. However, soil water availability is more influential for plant growth than precipitation and temperature, and there is ecophysiological evidence of intermediate yield maximizing conditions. Using rainfed maize and soybean yields for 1970–2010 across the USA, we tested whether the aridity index, that is, the ratio of precipitation and potential evapotranspiration seasonal totals and a proxy of soil water availability, better predicts yield than growing season precipitation total, average temperature and their interaction. We also tested for non‐monotonic responses allowing for intermediate yield‐maximizing conditions. The aridity index alone explained 77% and 72% of maize and soybean yield variability, compared with 78% and 73% explained by temperature, precipitation and their interaction. Yield responses were non‐monotonic, with yields maximized at intermediate precipitation and temperature as well as at intermediate aridity index of 0.79 for maize and 0.98 for soybean. The yield maximizing precipitation also increased with growing season average temperature, faster in maize than soybean. The intermediate yield maximizing conditions show that rainfed maize and soybean yields could both increase and decrease depending on whether climatic conditions come closer to or deviate from the yield maximizing conditions in the future. In most counties, during 1970–2010, the precipitation and aridity index were lower and temperature higher compared with those maximizing yields, suggesting that climate change will reduce yields.

Cold winters drive consistent and spatially synchronous 8-year population cycles of cabbage stem flea beetle.

Abstract: Population cycles have been observed in mammals as well as insects, but consistent population cycling has rarely been documented in agroecosystems and never for a beetle. We analysed the long-term population patterns of the cabbage stem flea beetle Psylliodes chrysocephala in winter oilseed rape over 50 years. Psylliodes chrysocephala larval density from 3045 winter oilseed rape fields in southern Sweden showed strong 8-year population cycles in regional mean density. Fluctuations in larval density were synchronous over time across five subregional populations. Subregional mean environmental variables explained 90.6% of the synchrony in P. chrysocephala populations at the 7-11 year time-scale. The number of days below -10°C showed strong anti-phase coherence with larval densities in the 7-11 year time-scale, such that more cold days resulted in low larval densities. High levels of the North Atlantic Oscillation weather system are coherent and anti-phase with cold weather in Scania, Sweden. At the field-scale, later crop planting date and more cold winter days were associated with decreased overwintering larval density. Warmer autumn temperatures, resulting in greater larval accumulated degree days early in the season, increased overwintering larval density. Despite variation in environmental conditions and crop management, 8-year cycles persisted for cabbage stem flea beetle throughout the 50 years of data collection. Moran effects, influenced by the North Atlantic Oscillation weather patterns, are the primary drivers of this cycle and synchronicity. Insect pest data collected in commercial agriculture fields is an abundant source of long-term data. We show that an agricultural pest can have the same periodic population cycles observed in perennial and unmanaged ecosystems. This unexpected finding has implications for sustainable pest management in agriculture and shows the value of long-term pest monitoring projects as an additional source of time-series data to untangle the drivers of population cycles.