Black walnut alley cropping is economically competitive with row crops in the Midwest USA.

The maize-soybean rotation (MSR) dominates the Midwest United States and degrades many ecological functions. Black walnut (Juglans nigra L.) plantation forestry (PF) and alley cropping (AC) are two alternative land-uses that can enhance productivity and restore ecosystem services. Given the lack of robust market mechanisms to monetize ecosystems services, we tested whether the profitability of PF and AC could drive adoption in the Midwest. Publically available data on black walnut soil suitability, timber prices, crop productivity, and cash rents were combined in a high-resolution spatial analysis to identify regions where these alternatives can outcompete MSR. To avoid selecting an arbitrary discount rate at which to make comparisons, we determined the threshold discount rate necessary to make PF or AC economically competitive with MSR. We show that, with a 5% discount rate, PF and AC could be more profitable on 17.0% and 23.4% of MSR land, respectively. Contrary to the common assumption that woody agricultural alternatives should first be adopted in marginal row crop areas, the economic competitiveness of PF and AC was not correlated with MSR productivity. Instead, black walnut growth rate was the central driver of PF and AC competitiveness, underscoring a necessary shift away from the current MSR-centric perspective in defining target regions for land-use alternatives. Results reveal major opportunities for landowners and investors to increase profitability by investing in PF and AC on both "marginal" and productive MSR land.

Frontiers in alley cropping: Transformative solutions for temperate agriculture.

Annual row crops dominate agriculture around the world and have considerable negative environmental impacts, including significant greenhouse gas emissions. Transformative land-use solutions are necessary to mitigate climate change and restore critical ecosystem services. Alley cropping (AC)-the integration of trees with crops-is an agroforestry practice that has been studied as a transformative, multifunctional land-use solution. In the temperate zone, AC has strong potential for climate change mitigation through direct emissions reductions and increases in land-use efficiency via overyielding compared to trees and crops grown separately. In addition, AC provides climate change adaptation potential and ecological benefits by buffering alley crops to weather extremes, diversifying income to hedge financial risk, increasing biodiversity, reducing soil erosion, and improving nutrient- and water-use efficiency. The scope of temperate AC research and application has been largely limited to simple systems that combine one timber tree species with an annual grain. We propose two frontiers in temperate AC that expand this scope and could transform its climate-related benefits: (i) diversification via woody polyculture and (ii) expanded use of tree crops for food and fodder. While AC is ready now for implementation on marginal lands, we discuss key considerations that could enhance the scalability of the two proposed frontiers and catalyze widespread adoption.

Diversity in stomatal function is integral to modelling plant carbon and water fluxes.

Stomatal pores on leaf surfaces respond to environmental and physiological signals to regulate leaf gas exchange. Mathematical models can predict stomatal conductance (g s), with one parameter (m or g l) reflecting the sensitivity of g s to the photosynthetic rate (A), atmospheric carbon dioxide concentration and atmospheric humidity, and a second parameter (g 0) representing the minimum g s. Such models are solved iteratively with a photosynthesis model to form the core of many models of crop or ecosystem carbon and water fluxes. For three decades, g s models have frequently been used assuming fixed parameter values for m or g 1 and g 0 across species and major plant functional types. This study of temperate tree species reveals significant interspecific variation in stomatal function. Applying species-specific parameterizations substantially reduced error in model predictions of g s by 34 to 64% and A by 52 to 60% and resulted in significant correlation between modelled and measured values. This work challenges the long-held assumption of fixed parameter values and, in doing so, suggests an approach for reducing modelling error across a wide range of ecological and agricultural applications.