Modelling the dynamics of feral alfalfa populations and its management implications

Landscape-scale approaches for enhancing biological pest control in agricultural systems

Over the last decades, land management options have been investigated that aim at enhancing services to agriculture delivered by biodiversity and its associated biotic interactions. Such services can be promoted through land management strategies ranging from in-field single agricultural practices, long-term strategies compiling these agricultural practices at the crop rotation scale, to management strategies at the landscape scale. In this paper, we provide an overview of the land management options that can be implemented at multiple scales, with a specific focus on the provision of one service that is key in agriculture, i.e. pest control. We present existing knowledge and highlight current gaps and limitations in our understanding of pest control response to land management. Based on this analysis, we propose two promising and complementary research approaches that could help filling existing knowledge gaps and provide guidelines for designing landscapes for agroecological services: (1) landscape monitoring networks (LMN), based on long-term monitoring of ecological and managerial processes within sets of landscapes located in contrasted production contexts; (2) agroecological system experiments (ASE), which design and assess combinations of land management options at multiple embedded spatial scales.

A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent-Based Population Models for Ecological Risk Assessment

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC.

Outcrossing potential between 11 important genetically modified crops and the Chilean vascular flora

The potential impact of genetically modified (GM) crops on biodiversity is one of the main concerns in an environmental risk assessment (ERA). The likelihood of outcrossing and pollen-mediated gene flow from GM crops and non-GM crops are explained by the same principles and depend primarily on the biology of the species. We conducted a national-scale study of the likelihood of outcrossing between 11 GM crops and vascular plants in Chile by use of a systematized database that included cultivated, introduced and native plant species in Chile. The database included geographical distributions and key biological and agronomical characteristics for 3505 introduced, 4993 native and 257 cultivated (of which 11 were native and 246 were introduced) plant species. Out of the considered GM crops (cotton, soya bean, maize, grape, wheat, rice, sugar beet, alfalfa, canola, tomato and potato), only potato and tomato presented native relatives (66 species total). Introduced relative species showed that three GM groups were formed having: a) up to one introduced relative (cotton and soya bean), b) up to two (rice, grape, maize and wheat) and c) from two to seven (sugar beet, alfalfa, canola, tomato and potato). In particular, GM crops presenting introduced noncultivated relative species were canola (1 relative species), alfalfa (up to 4), rice (1), tomato (up to 2) and potato (up to 2). The outcrossing potential between species [OP; scaled from 'very low' (1) to 'very high' (5)] was developed, showing medium OPs (3) for GM-native relative interactions when they occurred, low (2) for GMs and introduced noncultivated and high (4) for the grape-Vitis vinifera GM-introduced cultivated interaction. This analytical tool might be useful for future ERA for unconfined GM crop release in Chile.

Ectopic expression of GsPPCK3 and SCMRP in Medicago sativa enhances plant alkaline stress tolerance and methionine content

So far, it has been suggested that phosphoenolpyruvate carboxylases (PEPCs) and PEPC kinases (PPCKs) fulfill several important non-photosynthetic functions. However, the biological functions of soybean PPCKs, especially in alkali stress response, are not yet well known. In previous studies, we constructed a Glycine soja transcriptional profile, and identified three PPCK genes (GsPPCK1, GsPPCK2 and GsPPCK3) as potential alkali stress responsive genes. In this study, we confirmed the induced expression of GsPPCK3 under alkali stress and investigated its tissue expression specificity by using quantitative real-time PCR analysis. Then we ectopically expressed GsPPCK3 in Medicago sativa and found that GsPPCK3 overexpression improved plant alkali tolerance, as evidenced by lower levels of relative ion leakage and MDA content and higher levels of chlorophyll content and root activity. In this respect, we further co-transformed the GsPPCK3 and SCMRP genes into alfalfa, and demonstrated the increased alkali tolerance of GsPPCK3-SCMRP transgenic lines. Further investigation revealed that GsPPCK3-SCMRP co-overexpression promoted the PEPC activity, net photosynthetic rate and citric acid content of transgenic alfalfa under alkali stress. Moreover, we also observed the up-regulated expression of PEPC, CS (citrate synthase), H⁺-ATPase and NADP-ME genes in GsPPCK3-SCMRP transgenic alfalfa under alkali stress. As expected, we demonstrated that GsPPCK3-SCMRP transgenic lines displayed higher methionine content than wild type alfalfa. Taken together, results presented in this study supported the positive role of GsPPCK3 in plant response to alkali stress, and provided an effective way to simultaneously improve plant alkaline tolerance and methionine content, at least in legume crops.