, Volume 191, Issue 4, pp 995–1002 | Cite as

The landscape complexity relevance to farming effect assessment on small mammal occupancy in Argentinian farmlands

  • Vanesa N. Serafini
  • José A. Coda
  • Facundo Contreras
  • Michael J. Conroy
  • María Daniela GomezEmail author
  • José W. Priotto
Ecosystem ecology – original research


The responses of organisms to organic farming depend on the taxonomic group and landscape complexity. Following the intermediate landscape complexity hypothesis, organic farming can compensate for the lack of complexity in simple landscapes. Argentinian farmlands are simple with large fields and scarce linear habitat array, and conventional agriculture is almost the only agriculture practice. We hypothesize that there is an interaction effect of landscape complexity and farming practices on occupancy and species richness of small mammals in farmland of central Argentina. We selected circular landscapes under organic farming and low- and high-intensity conventional farming and quantified heterogeneity in each landscape considering different cover types (crops, resting plots, fallow land, border habitats, grasslands and man-made structures). We used multi-species occupancy models accounting for multiple seasons with a Bayesian approach to make the estimates. Landscapes under organic farms had the highest level of landscape heterogeneity. In simple Argentinian farmlands, organic farming benefited species richness and occupancy of all small mammal species. Some management strategies used in organic farming (wide and vegetated border habitats, diversity in types of production, winter cover crops, natural or semi-natural patches) should be taken into account to increase landscape complexity in conventional farming.


Organic and conventional farming Landscape heterogeneity Multi-species occupancy models Species richness Bayesian approach 



We are thankful to Javier Escudero for fieldwork assistance. We thank Foundation Rachel and Pamela Schiele, Las Gaviotas, Altos Verdes, El Piquete, El Chañarito y La Aurora farms that allowed us to carry out the surveys.

Author contribution statement

VNS, MDG and JWP designed the study and wrote the manuscript. VNS, JC, FC, MDG and JWP performed the research. VNS and MJC analyzed the data. VNS, MJC, MDG and JWP interpreted the data. VNS, MJC, MDG and JWP provided critical revision.


This work was supported by Consejo Nacional de Investigación Científica y Técnica (CONICET) [PIP CONICET No. 11220150100034] and Universidad Nacional de Río Cuarto, Córdoba, Argentina.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interests. The datasets generated and/or analyzed during the current study are available in the Open Science Framework ( repository.

Supplementary material

442_2019_4545_MOESM1_ESM.pdf (535 kb)
Supplementary material 1 (PDF 534 kb)
442_2019_4545_MOESM2_ESM.pdf (56 kb)
Supplementary material 2 (PDF 56 kb)


  1. Baldi G, Guerschman JP, Paruelo JM (2006) Characterizing fragmentation in temperate South America grasslands. Agric Ecosyst Environ 116:197–208. CrossRefGoogle Scholar
  2. Batáry P, Báldi A, Kleijn D, Tscharntke T (2011) Landscape-moderated biodiversity effects of agri-environmental management: a meta-analysis. Proc R Soc B 278:1894–1902. CrossRefPubMedGoogle Scholar
  3. Coda J, Gomez D, Steinmann A, Priotto J (2014) The effects of agricultural management on the reproductive activity of female rodents in Argentina. Basic Appl Ecol 15:407–415. CrossRefGoogle Scholar
  4. Coda JA, Gomez D, Steinmann AR, Priotto JW (2015) Small mammals in farmlands of Argentina: responses to organic and conventional farming. Agric Ecosyst Environ 211:17–23. CrossRefGoogle Scholar
  5. Copernicus Sentinel Data (2017) Copernicus Open Access Data. Accessed 21 Apr 2019
  6. Dobrovolski R, Diniz-Filho JAF, Loyola RD, De Marco Júnior P (2011) Agricultural expansion and the fate of global conservation priorities. Biodivers Conserv 20(11):2445–2459CrossRefGoogle Scholar
  7. Dorazio RM, Royle JA (2005) Estimating size and composition of biological communities by modeling the occurrence of species. J Am Stat Assoc 100:389–398. CrossRefGoogle Scholar
  8. Duflot R, Georges R, Ernoult A et al (2014) Landscape heterogeneity as an ecological filter of species traits. Acta Oecologica 56:19–26. CrossRefGoogle Scholar
  9. Fahrig L, Baudry J, Brotons LL et al (2011) Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecol Lett 14:101–112. CrossRefPubMedGoogle Scholar
  10. Fischer C, Thies C, Tscharntke T (2011) Mixed effects of landscape complexity and farming practice on weed seed removal. Perspect Plan Ecol Evol Syst 13:297–303CrossRefGoogle Scholar
  11. Gallé R, Happe AK, Baillod AB et al (2019) Landscape configuration, organic management, and within-field position drive functional diversity of spiders and carabids. J Appl Ecol 56:63–72. CrossRefGoogle Scholar
  12. Gelman A, Rubin DB (1992) Inference from iterative simulation using multiple sequences. Stat Sci 7:457–472. CrossRefGoogle Scholar
  13. Gomez MD, Coda JA, Simone I et al (2015) Agricultural land-use intensity and its effects on small mammals in the central region of Argentina. Mammal Res 60:415–423. CrossRefGoogle Scholar
  14. Gomez MD, Goijman AP, Coda JA et al (2018) Small mammal responses to farming practices in central Argentinian agroecosystems: the use of hierarchical occupancy models. Aust Ecol. CrossRefGoogle Scholar
  15. Guillera-Arroita G, Kéry M, Lahoz-Monfort JJ (2019) Inferring species richness using multispecies occupancy modeling: estimation performance and interpretation. Ecol Evol 9:780–792. CrossRefPubMedPubMedCentralGoogle Scholar
  16. Hevia V, Carmona CP, Azcárate FM et al (2015) Effects of land use on taxonomic and functional diversity: a cross-taxon analysis in a Mediterranean landscape. Oecologia 181:959–970. CrossRefPubMedGoogle Scholar
  17. Kellner K (2017) jagsUI: a wrapper around ‘RJAGS’ to streamline ‘JAGS’ analyses. R package version 1.4.9.
  18. Kéry M, Royle JA (2016) Applied hierarchical modeling in ecology: analysis of distribution, abundance and species richness in R and BUGS, Prelude and static models, vol 1. Elsevier Inc, New YorkGoogle Scholar
  19. Monck-Whipp L, Martin AE, Francis CM, Fahrig L (2018) Farmland heterogeneity benefits bats in agricultural landscapes. Agric Ecosyst Environ 253:131–139CrossRefGoogle Scholar
  20. Neumann JL, Griffiths GH, Hoodless A, Holloway GJ (2016) The compositional and configurational heterogeneity of matrix habitats shape woodland carabid communities in wooded-agricultural landscapes. Landsc Ecol 31:301–315. CrossRefGoogle Scholar
  21. Poggio SL, Chaneton EJ, Ghersa CM (2010) Landscape complexity differentially affects alpha, beta, and gamma diversities of plants occurring in fencerows and crop fields. Biol Conserv 143:2477–2486. CrossRefGoogle Scholar
  22. QGIS Development Team (2018) QGIS geographic information system. Open source geospatial foundation project. Accessed 17 Jul 2017
  23. R Development Core Team (2018) R: a language and environment for statistical computing. Vienna, Austria: R foundation for statistical computing. R version 3.5.1.
  24. Royle JA, Dorazio RM (2008) Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Elsevier Inc, New YorkGoogle Scholar
  25. Satorre EH (2005) Cambios tecnológicos en la agricultura argentina actua. Cienc hoy 15:6Google Scholar
  26. Serafini VN, Priotto JW, Gomez MD (2019) Effects of agroecosystem landscape complexity on small mammals: a multi-species approach at different spatial scales. Landsc Ecol 34:1117–1129. CrossRefGoogle Scholar
  27. Smith HG, Dänhardt J, Lindström A, Rundlöf M (2010) Consequences of organic farming and landscape heterogeneity for species richness and abundance of farmland birds. Oecologia 162:1071–1079. CrossRefPubMedGoogle Scholar
  28. Tilman D (1994) Competition and biodiversity in spatially structured habitats. Ecology 75:2–16CrossRefGoogle Scholar
  29. Tscharntke T, Klein AM, Kruess A et al (2005) Landscape perspectives on agricultural intensification and biodiversity—ecosystem service management. Ecol Lett 8:857–874. CrossRefGoogle Scholar
  30. Tscharntke T, Tylianakis JM, Rand TA et al (2012) Landscape moderation of biodiversity patterns and processes—eight hypotheses. Biol Rev 87:661–685. CrossRefPubMedGoogle Scholar
  31. Tuck SL, Winqvist C, Mota F et al (2014) Land-use intensity and the effects of organic farming on biodiversity: a hierarchical meta-analysis. J Appl Ecol 51:746–755. CrossRefPubMedPubMedCentralGoogle Scholar
  32. Zipkin EF, Dewan A, Royle JA (2009) Impacts of forest fragmentation on species richness: a hierarchical approach to community modelling. J Appl Ecol 46:815–822. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Grupo de Investigaciones en Ecología Poblacional y Comportamental (GIEPCO), Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente (ICBIA)Universidad Nacional de Río Cuarto-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Río CuartoArgentina
  2. 2.Warnell School of Forestry and Natural ResourcesUniversity of GeorgiaAthensUSA

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