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Over the past decade, research has intensified on how to evaluate and manage these ES to minimize environmental impacts of business and everyday life. [8] Concepts such as civic ecology, [9] sustainable development, [10][11][12] and the bioeconomy [13,14] are being rapidly operationalized and often integrate ecological practices into their implementation strategies, by way of how we interact with nature. In this regard, philosopher and scientist Aldo Leopold wrote in the mid-20th century: "A thing is right when it tends to preserve the integrity, stability, and beauty of the biotic community. It is wrong when it tends otherwise." [15] Similarly, the paradigm of civic ecology [9] is founded in subjective philosophy, which aims to expand our awareness of the natural world and the systems in place.One of the fundamental practices in civic ecology is systems thinking, with the idea that individuals should form a relation to nature, like they do to a human community. Further, systems thinking is frequently used in science to understand how individuals interact with the system. For instance, an ecosystem shares this attribute, where a dynamically evolving system is influenced by interacting, individual elements including air, water, soil, microbes, plants, and animals. Unfortunately, this notion is often ignored, because the provisioning The current geological epoch is characterized by anthropogenic activity that greatly impacts on natural ecosystems and their integrity. The complex networks of ecosystem services (ESs) are often ignored because the provision of natural resources, such as food and industrial crops, is mistakenly viewed as an independent process separate from ecosystems and ignoring the impacts on ecosystems. Recently, research has intensified on how to evaluate and manage ES to minimize environmental impacts, but it remains unclear how to balance anthropogenic activity and ecosystem integrity. This paper reviews the main ESs at farm level including provisioning, regulating, habitat, and cultural services. For these ESs, synergies are outlined and evaluated along with the respective practices (e.g., cover-and intercropping) and ES suppliers (e.g., pollinators and biocontrol agents). Further, several farm-level ES trade-offs are discussed along with a proposal for their evaluation. Finally, a framework for stakeholder approaches specific to farm-level ES is put forward, along with an outlook on how existing precision agriculture technologies can be adapted for improved assessment of ES bundles. This is believed to provide a useful framework for both decision makers and stakeholders to facilitate the development of more sustainable and resilient farming systems.

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of “still-good yield” (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in the analysis.

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