A spatially explicit assessment on the carrying capacity of livestock under minimum feed imports and artificial fertilizer use in Dutch agriculture

IF 6.1 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
M. Lessmann , A. Kanellopoulos , J. Kros , F. Orsi , M. Bakker
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引用次数: 0

Abstract

CONTEXT

Current agricultural systems in the Netherlands and other parts of Europe depend on large quantities of nutrients from imported feed and artificial fertilizers. This may result in unwanted nutrient accumulation and losses and negative environmental impacts. One way of making these systems more sustainable is to balance livestock numbers with the local feed supply and nutrient requirements for crop production. However, there is currently limited quantitative- and spatially-explicit insight into the effects of reduced imports on livestock numbers and nutrient balances.

OBJECTIVE

The aim of this study is to quantify the number of livestock that can be sustained when minimizing nitrogen (N) imports of feed and artificial fertilizers into Dutch agriculture.

METHODS

We developed a spatially-explicit mathematical programming model to optimize livestock numbers in different scenarios of allowed N imports. The model takes into account current flows of nutrients, related to nutrient supply from livestock manure, feed and fodder, and nutrient requirements in agricultural production.

RESULTS AND CONCLUSIONS

Minimizing N feed imports and artificial N fertilizer use under current land use resulted in an overall reduction of livestock density of 57.4% compared to the current livestock density based on 2020 activity data. In addition, it led to an increase in artificial N fertilizer inputs of 20.5% to maintain the N requirements of agricultural land. In contrast, focusing on minimizing artificial fertilizer use led to a reduction in livestock density of 25.8% compared to the current livestock levels. Depending on the scenario, we found strong regional variation in nutrient balances and livestock numbers. For instance, while currently the application rates of artificial fertilizers and livestock manure are relatively constant in space, this was no longer the case when N import in the form of feed was minimized. In that case, the crop-dominated areas showed a deficit in livestock manure and a substantial increase of artificial fertilizers.

SIGNIFICANCE

The presented model allows for assessing spatially explicit impacts of reduced N imports of feed and artificial fertilizers on livestock density. Using the Netherlands as case study, we show that reducing feed imports is a more effective leverage point to reduce N surplus and external N inputs into agriculture as compared to when reducing artificial fertilizer use. Our findings can inform the development of area-specific strategies that are aimed at reconnecting livestock and agricultural land.

Abstract Image

荷兰农业在最低饲料进口量和人工肥料使用量条件下牲畜承载能力的空间明确评估
荷兰和欧洲其他地区目前的农业系统依赖进口饲料和人工肥料提供的大量养分。这可能导致不必要的养分积累和损失,并对环境造成负面影响。使这些系统更具可持续性的方法之一是平衡牲畜数量与当地饲料供应和作物生产对养分的需求。然而,目前对减少进口对牲畜数量和养分平衡的影响的定量和空间洞察有限。本研究的目的是量化荷兰农业在尽量减少饲料和人工肥料氮(N)进口的情况下可维持的牲畜数量。我们开发了一个空间显式数学编程模型,在允许氮进口的不同情况下优化牲畜数量。该模型考虑到了当前的养分流,与牲畜粪便、饲料和饲草的养分供应以及农业生产的养分需求有关。与基于 2020 年活动数据的当前牲畜密度相比,在当前土地利用条件下最大限度地减少氮饲料进口和人工氮肥使用导致牲畜密度总体降低 57.4%。此外,这还导致人工氮肥投入增加 20.5%,以维持农业用地对氮的需求。相比之下,将重点放在尽量减少人工肥料的使用上,则会导致牲畜密度比目前的牲畜密度降低 25.8%。根据不同的方案,我们发现养分平衡和牲畜数量的地区差异很大。例如,虽然目前人工肥料和牲畜粪便的施用量在空间上相对稳定,但当以饲料形式进口的氮降到最低时,情况就不再是这样了。在这种情况下,作物为主的地区出现了牲畜粪便不足和人工肥料大量增加的情况。该模型可用于评估饲料和人工肥料氮进口减少对牲畜密度的空间影响。以荷兰为例,我们发现,与减少人工肥料使用相比,减少饲料进口是减少氮过剩和外部农业氮投入的更有效杠杆点。我们的研究结果可为制定旨在重新连接畜牧业和农业用地的特定地区战略提供参考。
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来源期刊
Agricultural Systems
Agricultural Systems 农林科学-农业综合
CiteScore
13.30
自引率
7.60%
发文量
174
审稿时长
30 days
期刊介绍: Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.
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