Bohan, David and Schmucki, Reto and Abay, Abrha and Termansen, Mette and Bane, Miranda and Charalabiis, Alice and Cong, Rong-Gang and Derocles, Stephane and Dorner, Zita and Forster, Matthieu and Gibert, Caroline and Harrower, Colin and Oudoire, Geoffroy and Therond, Olivier and Young, Juliette and Zalai, Mihaly and Pocock, Michael (2020): Designing farmer-acceptable rotations that assure ecosystem service provision inthe face of climate change. Published in: Advances in ecological research
Preview |
PDF
MPRA_paper_112313.pdf Download (589kB) | Preview |
Abstract
We believe that approaches to landscape modification should explicitly include farmers, given their understanding of landscape management practices, and consider climate change, so that the landscapes are designed for future environmental conditions. Climate change is an existential threat to farmers and current patterns of arable agriculture, which will lead to increases in the variability of agricultural productivity and crop failure. The performance of many of the crops that are currently highly productive will decline significantly and the geographical envelopes within which these crops can be grown are expected to shift northwards in Europe. Farmers will likely be faced with a choice: either leave farming or modify the crops that are grown, adopting new cultivars or species able to be cultivated profitably under future climatic conditions. We hypothesised that farmers do not adopt new crops or cultivars individually but use crops within sequences, called rotations, which are agronomically well understood. We know from past research that changes to rotations will lead to changes in biodiversity and the ecosystem services furnished by farmland, both within a field and at landscape scales. Here, we show how we might: use farmer knowledge of crop agronomy to propose future crop rotations in the light of climate change predictions; model these crop rotations to estimate likely effects on economy, biodiversity and ecosystem services; and validate these predictions through empirical study in regions where the rotations are already used. A workflow of co-development would have the benefit of generating practical rotations built on farmer knowledge and demonstrate empirically the predicted economic and ecological effects, markedly increasing the likely credibility of the results for farmers. Such a methodology has the potential to transform future sustainable agricultural landscapes.
Item Type: | MPRA Paper |
---|---|
Original Title: | Designing farmer-acceptable rotations that assure ecosystem service provision inthe face of climate change |
Language: | English |
Keywords: | crop rotation; ecological economics |
Subjects: | Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q0 - General Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics |
Item ID: | 112313 |
Depositing User: | Rong-Gang Cong |
Date Deposited: | 09 Mar 2022 08:15 |
Last Modified: | 09 Mar 2022 08:15 |
References: | Aizen MA, Arbetman MP, Chacoff NP, et al (2020) Invasive bees and their impact on agriculture. Advances in Ecological Research 63:49–92. Albizua A, Williams A, Hedlund K, Pascual U (2015) Crop rotations including ley and manure can promote ecosystem services in conventional farming systems. Applied Soil Ecology 95:54–61. Aramburu Merlos F, Hijmans RJ (2020) The scale dependency of spatial crop species diversity and its relation to temporal diversity. Proceedings of the National Academy of Sciences 117:26176–26182. Asseng S, Ewert F, Rosenzweig C, et al (2013) Uncertainty in simulating wheat yields under climate change. Nature Climate Change 3:827–832. Austerlitz F, Smouse PE (2001) Two-Generation Analysis of Pollen Flow Across a Landscape. II. Relation Between Φft, Pollen Dispersal and Interfemale Distance. Genetics 157:851. Bane MS, Pocock MJO, Gibert C, et al Farmer flexibility concerning future rotation planning is affected by the framing of climate predictions. Barbieri P, Pellerin S, Nesme T (2017) Comparing crop rotations between organic and conventional farming. Scientific Reports 7:570–10. Bennett E, et al (this issue) Ecosystem services and the resilience of agricultural landscapes Benvenuti S (2007) Weed seed movement and dispersal strategies in the agricultural environment. Weed Biology and Management 7:141–157. Bihaly ÁD, Hostyánszki AK, Szalai M, Sárospataki M (2020) Nesting activity of cavity‐nesting bees and wasps is lower in small‐scale apple orchards compared to nearby semi‐natural habitats. Agr Forest Entomol 12:331. Blöschl G, Hall J, Viglione A, et al (2019) Changing climate both increases and decreases European river floods. Nature 573:108–111. Bohan DA, Bohan AC, Glen DM, et al (2000) Spatial dynamics of predation by carabid beetles on slugs. J Anim Ecol 69:367–379. Bohan DA, Boffey CWH, Brooks DR, et al (2005) Effects on weed and invertebrate abundance and diversity of herbicide management in genetically modified herbicide-tolerant winter-sown oilseed rape. Proc R Soc Biol Sci Ser B 272:463–474. Bohan DA, Boursault A, Brooks DR, Petit S (2011a) National-scale regulation of the weed seedbank by carabid predators. J Appl Ecol 48:888–898. Bohan DA, Powers SJ, Champion GT, et al (2011b) Modelling rotations: can crop sequences explain arable weed seedbank abundance? Weed Research 51:422–432. Brooks DR, Storkey J, Clark SJ, et al (2011) Trophic links between functional groups of arable plants and beetles are stable at a national scale. J Anim Ecol 81:4–13. Brooks DR, Bohan DA, et al (2003) Invertebrate responses to the management of genetically modified herbicide–tolerant and conventional spring crops. I. Soil-surface-active invertebrates. Philos Trans R Soc Lond Ser B Biol Sci 358:1847–1862. Brown J, et al (this issue) How bioregional history could shape the future of agriculture Bullock DG (2008) Crop rotation. Critical Reviews in Plant Sciences 11:309–326. Bürkner, P.-C. (2018). Advanced Bayesian Multilevel Modeling with the R Package brms. The R Journal 10, 395–411. Carbonne B, Petit S, Neidel V, et al (2020) The resilience of weed seedbank regulation by carabid beetles, at continental scales, to alternative prey. Scientific Reports 10:1–14. Carpenter B, Gelman A, Hoffman MD, et al (2017) Stan: A Probabilistic Programming Language. Journal of Statistical Software 76:1–32. Ceglar A, Zampieri M, Toreti A, Dentener F (2019) Observed Northward Migration of Agro‐Climate Zones in Europe Will Further Accelerate Under Climate Change. Earth's Future 7:1088–1101. Champion GT, May MJ, Bennett S, et al (2003) Crop management and agronomic context of the Farm Scale Evaluations of genetically modified herbicide–tolerant crops. Philos Trans R Soc Lond Ser B Biol Sci 358:1801–1818. Chan SC, Kahana R, Kendon EJ, Fowler HJ (2018) Projected changes in extreme precipitation over Scotland and Northern England using a high-resolution regional climate model. Clim Dyn 51:3559–3577. Chao A, Jost L (2012) Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size. Ecology 93:2533–2547. Chao A, Jost L (2015) Estimating diversity and entropy profiles via discovery rates of new species. Methods in Ecology and Evolution 6:873–882. doi: 10.1111/2041-210X.12349 Chase JM, McGill BJ, McGlinn DJ, et al (2018) Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities. Ecol Letters 21:1737–1751. Chèze B, David M, Martinet V (2020) Understanding farmers' reluctance to reduce pesticide use: A choice experiment. Ecological Economics 167:106349. Clark SJ, Rothery P, Perry JN (2005) Farm Scale Evaluations of spring-sown genetically modified herbicide-tolerant crops: a statistical assessment. Proc R Soc Biol Sci Ser B 273:237–243. Clark SJ, Rothery P, Perry JN, Heard MS (2007) Farm Scale Evaluations of herbicide-tolerant crops: assessment of within-field variation and sampling methodology for arable weeds. Weed Research 47:157–163. Colwell RK, Mao CX, Chang J (2004) interpolating, extrapolating, and comparing incidence-based species accumulation curves. Ecology 85:2717–2727. Cong R, Ekroos J, Smith G, Brady M (2014) What land-use pattern emerges with landscape-scale management? An ecosystem-service perspective. Crist TO, Veech JA (2006) Additive partitioning of rarefaction curves and species–area relationships: unifying α-, β- and γ-diversity with sample size and habitat area. Ecol Letters 9:923–932. Crossman ND, Bryan BA, Cooke DA (2011) An invasive plant and climate change threat index for weed risk management: Integrating habitat distribution pattern and dispersal process. Ecological Indicators 11:183–198. Dauer JT, Mortensen DA, Vangessel MJ (2007) Temporal and spatial dynamics of long‐distance Conyza canadensis seed dispersal. J Appl Ecol 44:105–114. de Wit A, Boogaard H, Fumagalli D, et al (2019) 25 years of the WOFOST cropping systems model. Agricultural Systems 168:154–167. Duru M, Therond O, Fares M (2015a) Designing agroecological transitions; A review. Agron Sustain Dev 35:1237–1257. Duru M, Therond O, Martin G, et al (2015b) How to implement biodiversity-based agriculture to enhance ecosystem services: a review. Agron Sustain Dev 35:1259–1281. Eklöf A, Jacob U, Kopp J, et al (2013) The dimensionality of ecological networks. Ecol Letters 16:577–583. Engel J, Hertzog L, Tiede J, et al (2017) Pitfall trap sampling bias depends on body mass, temperature, and trap number: insights from an individual‐based model. Ecosphere 8:121. European Environment Agency (2019) Climate change adaptation in the agriculture sector in Europe. European Commission (2020) https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/income-support/greening_en Fahrig L, Girard J, Duro D, et al (2015) Farmlands with smaller crop fields have higher within-field biodiversity. Agric Ecosyst Environ 200:219–234. Faichnie R, et al. (this issue) Scales matter: maximising the effectiveness of interventions for pollinators and pollination Feola G, Binder CR (2010) Towards an improved understanding of farmers' behaviour: The integrative agent-centred (IAC) framework. Ecological Economics 69:2323–2333. Feola G, Lerner AM, Jain M, et al (2015) Researching farmer behaviour in climate change adaptation and sustainable agriculture: Lessons learned from five case studies. Journal of Rural Studies 39:74–84. Firbank LG, Heard MS, Woiwod IP, et al (2003) An introduction to the Farm-Scale Evaluations of genetically modified herbicide-tolerant crops. J Appl Ecol 40:2–16. Fisher RA (1972) The Design Of Experiments. Macmillan Publishing Company. Forster M, Bane M, Derocles S, et al (2020) FACCE SURPLUS PREAR project – Farmer questionnaire. Francis CA (2005) Crop Rotations. Encyclopedia of Soils in the Environment 318–322. Frei B, Guenay Y, Bohan DA, et al (2019) Molecular analysis indicates high levels of carabid weed seed consumption in cereal fields across Central Europe. J Pest Sci 92:935–942. Fuhrer J (2003) Agroecosystem responses to combinations of elevated CO2, ozone, and global climate change. Agric Ecosyst Environ 97:1–20. Gaba S, Deroulers P, Bretagnolle F, Bretagnolle V (2019) Lipid content drives weed seed consumption by ground beetles (Coleoptera, Carabidae) within the smallest seeds. Weed Research 59:170–179. Gaggiotti OE, Chao A, Neto PP, et al (2018) Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales. Evolutionary Applications 11:1176–1193. Geiger F, Bengtsson J, Berendse F, et al (2010) Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Bas Appl Ecol 11:97–105. Gendron RP (1987) Models and Mechanisms of Frequency-Dependent Predation. The American Naturalist 130:603–623. Gibbons DW, Bohan DA, Rothery P, et al (2006) Weed seed resources for birds in fields with contrasting conventional and genetically modified herbicide-tolerant crops. Proc R Soc Biol Sci Ser B 273:1921–1928. Grass I, et al. (this issue) Combining land-sparing and land-sharing in European landscapes Gray C, Ma A, McLaughlin Ó, et al (2021) Ecological plasticity governs ecosystem services in multilayer networks. Communications Biology. Hails RS (2000) Genetically modified plants – the debate continues. Trends in Ecology & Evolution 15:14–18. Hald AB (1999) The impact of changing the season in which cereals are sown on the diversity of the weed flora in rotational fields in Denmark. J Appl Ecol 36:24–32. Halsall NB, Wratten SD (1988) The efficiency of pitfall trapping for polyphagous predatory Carabidae. Ecological Entomology 13:293–299. Haan NL, et al. (this issue) Designing agricultural landscapes for arthropod-based ecosystem services in North America Haan NL, Zhang Y, & Landis DA (2020) Predicting Landscape Configuration Effects on Agricultural Pest Suppression. Trends in Ecology & Evolution 35: 175–186. Hassen A, Talore DG, Tesfamariam EH, et al (2017) Potential use of forage-legume intercropping technologies to adapt to climate-change impacts on mixed crop-livestock systems in Africa: a review. Reg Environ Change 17:1713–1724. Haughton AJ, Champion GT, Hawes C, et al (2003) Invertebrate responses to the management of genetically modified herbicide–tolerant and conventional spring crops. II. Within-field epigeal and aerial arthropods. Philos Trans R Soc Lond Ser B Biol Sci 358:1863–1877. Heard MS, Hawes C, et al (2003) Weeds in fields with contrasting conventional and genetically modified herbicide–tolerant crops. II. Effects on individual species. Philos Trans R Soc Lond Ser B Biol Sci 358:1833–1846. Hennessy DA (2006) On Monoculture and the Structure of Crop Rotations. American Journal of Agricultural Economics 88:900–914. Helfenstein J, Diogo V, Bürgi M, et al (2020) Conceptualizing pathways to sustainable agricultural intensification. Advances in Ecological Research 63:161–192. Holland JM, Sutter L, Albrecht M, et al (2020) Moderate pollination limitation in some entomophilous crops of Europe. Agric Ecosyst Environ 302:107002. Honek A, Martinkova Z, Jarosik V (2003) Ground beetles (Carabidae) as seed predators. Eur J Entomol 100:531–544. Honek A, Martinkova Z, Saska P, Pekar S (2007) Size and taxonomic constraints determine the seed preferences of Carabidae (Coleoptera). Bas Appl Ecol 8:343–353. Howlett BG, et al (this issue) Using non-bee and bee pollinator - plant species interactions to design diverse plantings benefiting crop pollination services Hurlbert SH (1971) The Nonconcept of Species Diversity: A Critique and Alternative Parameters. Ecology 52:577–586. IPBES (2019): Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. E. S. Brondizio, J. Settele, S. Díaz, and H. T. Ngo (editors). IPBES secretariat, Bonn, Germany. 56 pages. IPCC, 2018. Summary for Policymakers. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Jarosik V (1989) Mass vs. length relationship for carabid beetles (Col., Carabidae). Pedobiologia (Jena) 33:87–90. Jamieson S (2004) Likert scales: how to (ab)use them. Medical Education 38:1217–1218. Jones P, Thornton P (2003) The potential impacts of climate change on maize production in Africa and Latin America in 2055. Global Environmental Change 13:51–59. Jost L (2007) partitioning diversity into independent alpha and beta components. Ecology 88:2427–2439. Kleijn D, Biesmeijer KJC, Klaassen RHG, et al (2020) Integrating biodiversity conservation in wider landscape management: Necessity, implementation and evaluation. Advances in Ecological Research 63:127–159. Kondoh M (2003) Foraging Adaptation and the Relationship Between Food-Web Complexity and Stability. Science 299:1388–1391. Kremen C (2020) Ecological intensification and diversification approaches to maintain biodiversity, ecosystem services and food production in a changing world. Emerging Topics in Life Sciences 4:229–240. Land M, Haddaway NR, Hedlund K, et al (2017) How do selected crop rotations affect soil organic carbon in boreo-temperate systems? A systematic review protocol. Environ Evid 6:1–8. Levavasseur F, Martin P, Bouty C, et al (2016) RPG Explorer: A new tool to ease the analysis of agricultural landscape dynamics with the Land Parcel Identification System. Computers and Electronics in Agriculture 127:541–552. Leenhardt D, Angevin F, Biarnès A, et al (2010) Describing and locating cropping systems on a regional scale. A review. Agron Sustain Dev 30:131–138. Leng G, Huang M (2017) Crop yield response to climate change varies with crop spatial distribution pattern. Scientific Reports 7:1–10. doi: 10.1038/s41598-017-01599-2 Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529:84–87. Luff, M. L. (2007). The Carabidae (Ground Beetles) of Britain and Ireland. St Albans, UK: Royal Entomological Society. Ma A, Lu X, Gray C, et al (2018) Ecological networks reveal resilience of agro-ecosystems to changes in farming management. Nature Ecology & Evolution 2018 3:260–264. MacLaren C, Storkey J, Menegat A, et al (2020) An ecological future for weed science to sustain crop production and the environment. A review. Agron Sustain Dev 40:39–29. Mahaut L, Gaba S, Fried G (2019) A functional diversity approach of crop sequences reveals that weed diversity and abundance show different responses to environmental variability. J Appl Ecol 56:1400–1409. Mahé I, Cordeau S, Bohan DA, et al (2020) Soil seedbank: Old methods for new challenges in agroecology? Ann App Biol 69:497. Mancini F, Woodcock BA, Redhead J, et al (2020) Detecting landscape scale consequences of insecticide use on invertebrate communities. Advances in Ecological Research 63:93–126. Manly BFJ, Miller P, Cook LM (1972) Analysis of a Selective Predation Experiment. The American Naturalist 106:719–736. Marrec R, Caro G, Miguet P, et al (2017) Spatiotemporal dynamics of the agricultural landscape mosaic drives distribution and abundance of dominant carabid beetles. Landscape Ecol 32:2383–2398. Marshall EJP, Brown VK, Boatman ND, et al (2003) The role of weeds in supporting biological diversity within crop fields. Weed Research 43:77–89. McGlinn DJ, Xiao X, May F, et al (2019) Measurement of Biodiversity (MoB): A method to separate the scale‐dependent effects of species abundance distribution, density, and aggregation on diversity change. Methods in Ecology and Evolution 10:258–269. Melander B, Munier-Jolain N, Charles R, et al (2017) European Perspectives on the Adoption of Nonchemical Weed Management in Reduced-Tillage Systems for Arable Crops. Weed technol 27:231–240. Mendelsohn R, Nordhaus WD, Shaw D, (1994) The impact of global warming on agriculture: a ricardian analysis. The American Economic Review, 753–771. Merkle EC, Fitzsimmons E, Uanhoro J, Goodrich B (2020) Efficient Bayesian Structural Equation Modeling in Stan. https://arxiv.org/abs/2008.07733v1 Merkle EC, Furr D, Rabe-Hesketh S (2018) Bayesian comparison of latent variable models: Conditional vs marginal likelihoods. Psychometrika 84:802–829. Mgendi G, Shiping M, Xiang C (2019) A Review of Agricultural Technology Transfer in Africa: Lessons from Japan and China Case Projects in Tanzania and Kenya. Sustainability 11:6598. Möhring N, Dalhaus T, Enjolras G, Finger R (2020) Crop insurance and pesticide use in European agriculture. Agricultural Systems 184:102902. Moorcroft D, Whittingham MJ, Bradbury RB, Wilson JD (2002) The selection of stubble fields by wintering granivorous birds reflects vegetation cover and food abundance. J Appl Ecol 39:535–547. Morgounov A, Sonder K, Abugalieva A, et al (2018) Effect of climate change on spring wheat yields in North America and Eurasia in 1981-2015 and implications for breeding. PLoS ONE 13:e0204932. Mulder C, Sechi V, Woodward G, Bohan DA (2017) Ecological Networks in Managed Ecosystems: Connecting Structure to Services. In: Adaptive Food Webs: Stability and Transitions of Real and Model Ecosystems, 1st edn. Cambridge University Press, pp 214–227 Opdam P (2020) Implementing human health as a landscape service in collaborative landscape approaches. Landscape and Urban Planning 199:103819. Ouin A, et al. (this issue) Building a shared vision of the future for multifunctional agricultural landscapes - Lessons from a Long Term Socio-Ecological Research site in south-western France. Pankhurst CE, Lynch JM (2005) Biocontrol of soil-borne plant diseases. Encyclopedia of Soils in the Environment 129–136. Pannell DJ, Stewart V, Bennett A, et al (2004) RIM: a bioeconomic model for integrated weed management of Lolium rigidum in Western Australia. Agricultural Systems 79:305–325. Paradis E, Baillie SR, Sutherland WJ (2002) Modeling large-scale dispersal distances. Ecol Model 151:279–292. Perry JN, Rothery P, Clark SJ, et al (2003) Design, analysis and statistical power of the Farm‐Scale Evaluations of genetically modified herbicide‐tolerant crops. J Appl Ecol 40:17–31. Petit S, Boursault A, Bohan DA (2014) Weed seed choice by carabid beetles (Coleoptera: Carabidae): Linking field measurements with laboratory diet assessments. Eur J Entomol 111:615–620. Petit S, Cordeau S, Chauvel B, et al (2018) Biodiversity-based options for arable weed management. A review. Agron Sustain Dev 38:1–21. Petit S, Muneret L, Carbonne B, et al (2020) Landscape-scale expansion of agroecology to enhance natural pest control: A systematic review. Advances in Ecological Research 63:1–48. Pocock MJO, Evans DM, Memmott J (2012) The Robustness and Restoration of a Network of Ecological Networks. Science 335:973–977. Pocock MJO, Schmucki R, Bohan DA (2020) Inferring species interactions from ecological survey data: a mechanistic approach to predict quantitative food webs of seed-feeding by carabid beetles. bioRxiv 33:2020.11.09.375402. Poggi S, et al. (this issue) How can models foster the transition towards future agricultural landscapes? Pyke GH, Pulliam HR, Charnov EL (1977) Optimal Foraging: A Selective Review of Theory and Tests. The Quarterly Review of Biology 52:137–154. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Raseduzzaman M, Steen Jensen E (2017) Does intercropping enhance yield stability in arable crop production? A meta-analysis. European Journal of Agronomy 91:25–33. Ritchie PDL, Harper AB, Smith GS, et al (2019) Large changes in Great Britain’s vegetation and agricultural land-use predicted under unmitigated climate change. Environ Res Lett 14:114012. Rizzo D, Therond O, Lardy R, et al (2019) A rapid, spatially explicit approach to describe cropping systems dynamics at the regional scale. Agricultural Systems 173:491–503. Robinson RA, Sutherland WJ (2002) Post-war changes in arable farming and biodiversity in Great Britain. J Appl Ecol 39:157–176. Rosseel Y (2012) lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software 48:1–36. Roubinet E, Jonsson T, Malsher G, et al (2018) High Redundancy as well as Complementary Prey Choice Characterize Generalist Predator Food Webs in Agroecosystems. Scientific Reports 8:689–10. Saska P, Honek A, Martinkova Z (2019) Preferences of carabid beetles (Coleoptera: Carabidae) for herbaceous seeds. Acta Zool Acad Sci H 65:57–76. Sebastián-González E, Pires MM, Donatti CI, et al (2017) Species traits and interaction rules shape a species-rich seed-dispersal interaction network. Ecol Evol 7:4496–4506. Schellhorn NA, Gagic V, Bommarco R (2015) Time will tell: resource continuity bolsters ecosystem services. Trends in Ecology & Evolution 30:524–530. Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proceedings of the National Academy of Sciences 106:15594–15598. Schmucki R, Bohan DA, Pocock MJO (2020) Combined effect of crop rotation and carabid beetles on weed dynamics in arable fields. bioRxiv 2020.12.04.411918. Schüpbach B, Weiß SB, Jeanneret P, et al (2021) What determines preferences for semi-natural habitats in agrarian landscapes? A choice-modelling approach across two countries using attributes characterising vegetation. Landscape and Urban Planning 206:103954. Scott RJ, Baker P, Bell D, et al (2012a) Farm scale evaluations of herbicide tolerant genetically modified crops—Beet. NERC Environmental Information Data Centre. Scott RJ, Baker P, Bell D, et al (2012b) Farm scale evaluations of herbicide tolerant genetically modified crops—Maize. NERC Environmental Information Data Centre. Scott RJ, Baker P, Bell D, et al (2012c) Farm scale evaluations of herbicide tolerant genetically modified crops—Spring oilseed rape. NERC Environmental Information Data Centre. Scott RJ, Baker P, Bell D, et al (2012d) Farm scale evaluations of herbicide tolerant genetically modified crops—Winter oilseed rape. NERC Environmental Information Data Centre. Sint D, Guenay Y, Mayer R, et al (2018) The effect of plant identity and mixed feeding on the detection of seed DNA in regurgitates of carabid beetles. Ecol Evol 8:10834–10846. Skamarock WC, Klemp JB, Dudhia J, et al (2008). A description of the advanced research WRF version 3. NCAR Technical note-475+ STR. pp. 113. Skrimizea E, Lecuyer L, Bunnefeld N, et al (2020) Sustainable agriculture: Recognizing the potential of conflict as a positive driver for transformative change. Advances in Ecological Research 63:255–311. Sloat LL, Davis SJ, Gerber JS, et al (2020) Climate adaptation by crop migration. Nat Comms 11:1–9. Smid SC, McNeish D, Miočević M, van de Schoot R (2019) Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review. Structural Equation Modeling: A Multidisciplinary Journal 27:131–161. Smith V, Bohan DA, Clark SJ, et al (2008) Weed and invertebrate community compositions in arable farmland. Arthropod-Plant Interactions 2:21–30. Smith RG, Mortensen DA, Ryan MR (2010) A new hypothesis for the functional role of diversity in mediating resource pools and weed–crop competition in agroecosystems. Weed Research 50:37–48. Spence A, Pidgeon N (2010) Framing and communicating climate change: The effects of distance and outcome frame manipulations. Global Environmental Change 20:656–667. Staudacher K, Rubbmark OR, Birkhofer K, et al (2018) Habitat heterogeneity induces rapid changes in the feeding behaviour of generalist arthropod predators. Funct Ecol 32:809–819. Stein S, Steinmann H-H (2018) Identifying crop rotation practice by the typification of crop sequence patterns for arable farming systems – A case study from Central Europe. European Journal of Agronomy 92:30–40. Stephens DW, Lynch JF, Sorensen AE, Gordon C (1986) Preference and Profitability: Theory and Experiment. The American Naturalist 127:533–553. Storkey J, Bruce TJA, McMillan VE, Neve P (2019) The Future of Sustainable Crop Protection Relies on Increased Diversity of Cropping Systems and Landscapes. In: Agroecosystem Diversity. Academic Press, pp 199–209 Storkey J, Neve P (2018) What good is weed diversity? Weed Research 58:239–243. Tamburini G, Bommarco R, Wanger TC, et al (2020) Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci Adv 6:eaba1715. Teixeira EI, de Ruiter J, Ausseil A-G, et al (2018) Adapting crop rotations to climate change in regional impact modelling assessments. Science of The Total Environment 616-617:785–795. Therond O, Duru M, Roger-Estrade J, Richard G (2017) A new analytical framework of farming system and agriculture model diversities. A review. Agron Sustain Dev 37:1–24. Thomas CFG, Brown NJ, Kendall DA (2006) Carabid movement and vegetation density: Implications for interpreting pitfall trap data from split-field trials. Agric Ecosyst Environ 113:51–61. Tigchelaar M, Battisti DS, Naylor RL, Ray DK (2018) Future warming increases probability of globally synchronized maize production shocks. Proceedings of the National Academy of Sciences 115:6644–6649. Tinbergen L (1960) The Natural Control of Insects in Pinewoods. Arch Néerl Zool 13:265–343. Trichard A, Alignier A, Biju-Duval L, Petit S (2013) The relative effects of local management and landscape context on weed seed predation and carabid functional groups. Bas Appl Ecol 14:235–245. Vanbergen AJ, Aizen MA, Cordeau S, et al (2020) Transformation of agricultural landscapes in the Anthropocene: Nature's contributions to people, agriculture and food security. Advances in Ecological Research 63:193–253. van Erp S, Mulder J, Oberski DL (2018) Prior sensitivity analysis in default Bayesian structural equation modeling. Psychological Methods 23:363–388. van Etten J, de Sousa K, Aguilar A, et al (2019) Crop variety management for climate adaptation supported by citizen science. Proceedings of the National Academy of Sciences 116:4194–4199. Vasileiadis VP, Sattin M, Otto S, et al (2011) Crop protection in European maize-based cropping systems: Current practices and recommendations for innovative Integrated Pest Management. Agricultural Systems 104:533–540. Vialatte A, Barnaud C, Blanco J, et al (2019) A conceptual framework for the governance of multiple ecosystem services in agricultural landscapes. Landscape Ecol 34:1653–1673. Vogel E, Donat MG, Alexander LV, et al (2019) The effects of climate extremes on global agricultural yields. Environ Res Lett 14:054010. Wallinger C, Sint D, Baier F, et al (2015) Detection of seed DNA in regurgitates of granivorous carabid beetles. Bull Entomol Res 105:728–735. Watkinson AR, Freckleton RP, Robinson RA, et al (2000) Predictions of Biodiversity Response to Genetically Modified Herbicide-Tolerant Crops. Science 289:1554–1557. Westerman PR, Dixon PM, Liebman M (2009) Burial rates of surrogate seeds in arable fields. Weed Research 49:142–152. Weisberger D, Nichols V, Liebman M (2019) Does diversifying crop rotations suppress weeds? A meta-analysis. PLoS ONE 14:e0219847. Wilson JD, Morris AJ, Arroyo BE, et al (1999) A review of the abundance and diversity of invertebrate and plant foods of granivorous birds in northern Europe in relation to agricultural change. Agric Ecosyst Environ 75:13–30. Wilson S, Mitchell GW, Pasher J, et al (2017) Influence of crop type, heterogeneity and woody structure on avian biodiversity in agricultural landscapes. Ecological Indicators 83:218–226. Winder L, Alexander CJ, Holland JM, et al (2005) Predatory activity and spatial pattern: the response of generalist carabids to their aphid prey. J Anim Ecol 74:443–454. Wolf. J, 2011. Climate Change Adaptation in Developed Nations: From Theory to Practice, Advances in Global Change Research. Springer Netherlands, Dordrecht. https://doi.org/10.1007/978-94-007-0567-8 Woznicki SA, Nejadhashemi AP, Parsinejad M (2015) Climate change and irrigation demand: Uncertainty and adaptation. Journal of Hydrology: Regional Studies 3:247–264. Yates F (1964) Sir Ronald Fisher and the Design of Experiments. Biometrics 20:307. Young JC, Rose DC, Mumby HS, et al (2018) A methodological guide to using and reporting on interviews in conservation science research. Methods in Ecology and Evolution 9:10–19. Zhang X, Cai X (2011) Climate change impacts on global agricultural land availability. Environ Res Lett 6:014014. Zohry A, Ouda S (2018) Crop Rotation Defeats Pests and Weeds. In: Crop Rotation. Springer, Cham, Cham, pp 77–88 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/112313 |