Search bioRxiv⌕ Search

bioRxiv · 10.1101/788240

Long-term research needed to avoid spurious and misleading trends in sustainability attributes of no-till

Abstract

Agricultural management recommendations based on short-term studies can produce findings inconsistent with long-term reality. Here, we test the long-term relative profitability and environmental sustainability of continuous no-till agriculture practices on crop yield, soil moisture, and N2O fluxes. Using a moving window approach, we investigate the development and stability of several attributes of continuous no-till as compared to conventional till agriculture over a 29-year period at a site in the upper Midwest, U.S. We find that over a decade is needed to detect the consistent benefits of no-till on important attributes at this site. Both crop yield and soil moisture required periods 15 years or longer to generate patterns consistent with 29-year trends. Only marginally significant trends for N2O fluxes appeared in this period. Importantly, significant but misleading short-term trends appeared in more than 20% of the periods examined. Relative profitability analysis suggests that 10 years after initial implementation, 86% of periods recuperated the initial expense of no-till implementation, with the probability of higher relative profit increasing with longevity. Results underscore the essential importance of decade and longer studies for revealing the long-term dynamics and emergent outcomes of agricultural practices for different sustainability attributes and are consistent with recommendations to support the long-term adoption of no-till management.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC=\"FIGDIR/small/788240v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (42K):\norg.highwire.dtl.DTLVardef@1e7529eorg.highwire.dtl.DTLVardef@1e11268org.highwire.dtl.DTLVardef@17f8995org.highwire.dtl.DTLVardef@2196fe_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIWe test long-term effects of no-till on yield, soil moisture, and N2O fluxes\nC_LIO_LIWe examine 29 years of data with a moving window and relative profitability method\nC_LIO_LIIt takes at least a decade to detect consistent benefits of no-till\nC_LIO_LIShorter studies can produce significant but misleading findings\nC_LIO_LILong studies are essential to reveal the dynamics of agricultural management\nC_LI

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Cusser, S., Bahlai, C., Swinton, S. M., Robertson, G. P., Haddad, N. M.. 2019-10-08. Long-term research needed to avoid spurious and misleading trends in sustainability attributes of no-till. https://doi.org/10.1101/788240

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Invasion analysis for structured populations: analytical principles and numerical workflows

All real populations show some form of structure--differences among individuals, such as life stage or physiological condition, that shape a species' ability to persist. Yet it remains challenging to incorporate population structure into models of species interactions. We provide a general framework for studying competition in structured populations by quantifying species' invasion growth rates. The crux of our approach is separation of timescales: the initial dynamics of a structured population depend on how exactly it is introduced, but these transient differences do not affect long-term invasion success. Depending on the research question, the relevant long-term growth rate when rare may equivalently be derived using analytical separation of timescales, matrix population theory, or numerical simulations. Using case studies spanning developmental stage, environmental state, and infection status, we illustrate how our methodology derives simple, ecologically meaningful invasion conditions for a variety of systems. Finally, we extend the approach to fluctuating resident dynamics, showing how to use simulations or a general mathematical framework known as Floquet theory to correctly quantify invasion growth. By unifying the quantitative methods of population biology and community ecology, our framework will allow ecologists to study species persistence and coexistence across a greater variety of demographically complex systems.

ecology↗

Interspecific social contacts spread gut microbiota in wild rodent communities

Background: The mammalian gut microbiota influences a wide array of host phenotypes and varies substantially among individuals. Among conspecifics, microbiota composition is strongly shaped by microbial transmission through social interactions, yet the extent to which such transmission also occurs across species boundaries remains poorly understood. Here, we combine high-resolution tracking data collected over more than 10 months with gut microbiota profiling to examine social associations, space use, and microbiota similarity among individuals of three sympatric rodent species - wood mice (Apodemus sylvaticus), yellow-necked mice (A. flavicollis) and bank voles (Myodes glareolus), in two woodlands. By integrating multi-species social networks and spatial overlap with individual microbiota data, we test how both conspecific and interspecific interactions shape gut microbiota composition. Results: At both study sites, social associations strongly predicted microbiota similarity among conspecific individuals, whereas spatial proximity consistently predicted microbiota similarity among interspecific pairs. In addition, social associations between mice of different species predicted microbiota similarity, although this effect was weaker than that observed within species and was asymmetric, with evidence for stronger microbial transmission from wood mice to yellow-necked mice than vice versa. By focusing on species-indicative bacterial taxa, we further show that wood mice with more social connections to yellow-necked mice harboured a greater richness of gut bacteria typical of yellow-necked mice. Conclusions: Together, these results demonstrate that individual-level social behaviour can influence gut microbial transmission across species boundaries, particularly among closely related species with overlapping ecological niches. Interspecific social interactions may therefore represent an underappreciated pathway for the acquisition of novel gut symbionts in multi-species communities.

ecology↗

Microscale nonrandomness revisited: An overlooked predictor of ecological change

Abrupt ecological transitions have driven the development of early warning signal metrics that track how ecological systems respond as external conditions gradually change and systems approach transitions between states. However, their generality and applicability remain uncertain, particularly for short-term ecological dynamics that can occur without directional external change. To address this gap, we propose a general framework based on the hypothesis that microscale nonrandomness, quantified from frequency distributions or spatial patterns, predicts subsequent short-term rates of change in populations and interactions, as well as current macroscale ecosystem states. We applied the framework to four datasets: time series from an incubation experiment of phytoplankton-parasitic chytrid interactions; spatiotemporal field observations of leaf beetles on willow trees and aphids in a crop system; and spatial snapshot data linking soil surface characteristics with aboveground and soil ecosystem properties in a forest vegetations-soil system. We quantified microscale nonrandomness using Morisita I_{delta} from frequency distributions and Moran's I and SADIE from spatial patterns. Across all systems, models incorporating microscale nonrandomness metrics consistently showed greater cross-validated predictive performance than those based on macroscale variables or spatial averages alone. Although their relative performance varied among systems, frequency-based metrics performed as well as or better than spatially explicit metrics in some cases. The consistent improvement across contrasting systems supports the broad applicability of this framework, including under limited data conditions. This framework broadens ecological forecasting to short-term, continuous dynamics beyond those associated with directional environmental change.

ecology↗