Best practices in prediction for decision-making : lessons from the atmospheric and earth sciences

Predictions that result from scientific research hold great appeal for decision-makers who are grappling with complex and controversial environmental issues, by promising to enhance their ability to determine a need for and outcomes of alternative decisions. A problem exists in that decision-makers and scientists in the public and private sectors solicit, produce, and use such predictions with little understanding of their accuracy or utility, and often without systematic evaluation or mechanisms of accountability. In order to contribute to a more effective role for ecological science in support of decision-making, this paper discusses three ``best practices'' for quantitative ecosystem modeling and prediction gleaned from research on modeling, prediction, and decision-making in the atmospheric and earth sciences. The lessons are distilled from a series of case studies and placed into the specific context of examples from ecological science

Adjustment and Sensitivity Analyses of a Beta Global Rangeland Model

G-Range is a global model that simulates generalized changes in rangelands through time, created with support from the International Livestock Research Institute. Spatial data and a set of parameters that control plant growth and other ecological attributes in landscape units combine with computer code to represent ecological process such as soil nutrient and water dynamics, vegetation growth, fire, and wild and domestic animal offtake. The model is spatial, with areas of the world divided into square cells

Phosphorus mobilizing consortium Mammoth P enhances plant growth

Global agricultural productivity may be constrained by the finite and limited supply of phosphorus (P), adding to the challenges in meeting the projected needs of a growing human population in the coming decades. In addition, when P fertilizers are added to soils, they can become bound to soils resulting in low fertilizer efficiency. However, P-mobilizing bacteria could potentially liberate soil-bound P, resulting in a higher plant P uptake and increased yield. Bacteria can mobilize P through several mechanisms, suggesting that consortia of P-bacteria may be more effective than single species. Species diversity can have a synergistic, or non-additive, effect on ecosystem functioning ("the whole is more than the sum of its parts") but rarely is the microbial community structure intentionally managed to improve plant nutrient uptake. We investigated whether inoculation of soils with a four-species bacterial community developed to mobilize soil P could increase plant productivity. In wheat and turf trials, we found that Mammoth P was able to deliver yields equivalent to those achieved using conventional fertilizer applications. Herbs and fruits showed that the combination of fertilizer with Mammoth P significantly increased productivity -in some cases productivity doubled. Metabolites produced by the Mammoth P consortium led to increased yields in some cases, suggesting that microbial products (produced in the absence of plants) played a role in enhancing plant productivity. Results from these trials indicate substantial potential of Mammoth P to enhance P supply to plants, improving P fertilizer use-efficiency and increasing agricultural productivity. 19 Agricultural productivity may be constrained in the 21 st Century by the finite supply of global a 20 phosphorus (P), adding to the challenges in meeting the projected needs of a growing human population 21 in the coming decades. In addition, when P fertilizers are added to soils, they can become bound to soils 22 resulting in low fertilizer efficiency. However, bacteria have the ability to mobilize soil bound P through 23 several mechanisms potentially resulting in a higher plant P uptake and increased yield. Furthermore, 24 species diversity can have a synergistic effect on ecosystem functioning ("the whole is more than the sum 25 of its parts") suggesting that bacterial communities, or consortia, may be more effective than single 26 species. However, in agriculture management practices, rarely is the soil microbial community structure 27 effectively manipulated to improve plant nutrient uptake. We investigated whether inoculation of soils 28 with a bacterial consortium developed to mobilize soil P named Mammoth P could increase plant 29 productivity. In turf, herbs and fruits, we showed that the combination of conventional inorganic fertilizer 30 combined with Mammoth P increased productivity up to twofold compared to the fertilizer treatments 31 without the Mammoth P inoculant. In wheat trials, we found that Mammoth P by itself was able to deliver 32 yields equivalent to those achieved with conventional inorganic fertilizer applications. The metabolites 33 produced by the consortium in Mammoth P likely played a role in enhancing plant productivity. Results 34 from this study indicate the substantial potential of Mammoth P to enhance P supply to plants, improving 35 P fertilizer use-efficiency and increasing agricultural productivity. 3

Natural climate solutions

Our thanks for inputs by L. Almond, A. Baccini, A. Bowman, S. CookPatton, J. Evans, K. Holl, R. Lalasz, A. Nassikas, M. Spalding, M. Wolosin, and expert elicitation respondents. Our thanks for datasets developed by the Hansen lab and the NESCent grasslands working group (C. Lehmann, D. Griffith, T. M. Anderson, D. J. Beerling, W. Bond, E. Denton, E. Edwards, E. Forrestel, D. Fox, W. Hoffmann, R. Hyde, T. Kluyver, L. Mucina, B. Passey, S. Pau, J. Ratnam, N. Salamin, B. Santini, K. Simpson, M. Smith, B. Spriggs, C. Still, C. Strömberg, and C. P. Osborne). This study was made possible by funding from the Doris Duke Charitable Foundation. Woodbury was supported in part by USDA-NIFA Project 2011-67003-30205 Data deposition: A global spatial dataset of reforestation opportunities has been deposited on Zenodo (https://zenodo.org/record/883444). This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1710465114/-/DCSupplemental.Peer reviewedPublisher PD

Dynamic Time-Warping Correction for Shifts in Ultrahigh Resolving Power Ion Mobility Spectrometry and Structures for Lossless Ion Manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced in IMS. Such variations can be apparent in higher Rp measurements and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here, we explore data processing approaches employing single value alignment (SVA) and nonlinear dynamic time warping (DTW) to correct for variations between IMS separations, such as due to pressure fluctuations, to enable more effective spectrum summation for improving Rp and detection of low-intensity species. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the SVA approach effectively corrected for such variations and significantly improved Rp for summed separations. However, SVA was much less effective for broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in ions’ arrival times were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed that DTW alignment performed similarly to SVA when used over a narrow mobility range but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found that the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 s were summed. We conclude that DTW is superior to SVA for ultra-high-resolution broad mobility range SLIM IMS separations and leads to a large improvement in effective Rp, correcting for ion arrival time shifts regardless of the cause, as well as improving the detectability of low-abundance species. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files

Greenhouse gas mitigation potentials in the livestock sector

Acknowledgements This paper constitutes an output of the Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1). Financial support from the CGIAR Program on Climate Change, Agriculture and Food Security (CCAFS) and the EU-FP7 AnimalChange project is also recognized. P.K.T. acknowledges the support of a CSIRO McMaster Research Fellowship.Peer reviewedPostprin

Measurement and Theory of Gas-Phase Ion Mobility Shifts Resulting from Isotopomer Mass Distribution Changes

The unanticipated discovery of recent ultra-high-resolution ion mobility spectrometry (IMS) measurements revealing that isotopomers—compounds that differ only in the isotopic substitution sites—can be separated has raised questions as to the physical basis for their separation. A study comparing IMS separations for two isotopomer sets in conjunction with theory and simulations accounting for ion rotational effects provides the first-ever prediction of rotation-mediated shifts. The simulations produce observable mobility shifts due to differences in gas−ion collision frequency and translational-to-rotational energy transfer. These differences can be attributed to distinct changes in the moment of inertia and center of mass between isotopomers. The simulations are in broad agreement with the observed experiments and consistent with relative mobility differences between isotopomers. These results provide a basis for refining IMS theory and a new foundation to obtain additional structural insights through IMS