#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Effects of forest management and roe deer impact on a mountain forest development in the Italian Apennines: A modelling approach using LANDIS-II


Autoři: Andrea Marcon aff001;  David J. Mladenoff aff002;  Stefano Grignolio aff001;  Marco Apollonio aff001
Působiště autorů: Department of Veterinary Medicine, University of Sassari, Sassari, Italy aff001;  Department of Forest & Wildlife Ecology, University of Wisconsin-Madison, Russell Labs, Madison, Wisconsin, United States of America aff002
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0224788

Souhrn

Forest development is a complex phenomenon which, for the number of actors involved and the response time expressed by forests, is difficult to understand and explore. Forests in Italy, as in several areas of Europe, are experiencing intensive management and recently, an increasing impact by ungulates. The effects on forest development of these two disturbances combined are difficult to predict, and consequently to be properly managed. We used a forest landscape change model, LANDIS-II, to simulate forest development as driven by forestry practices and roe deer impact for 200 years in a mountain forest of the Italian Apennines. We found that each disturbance alters forest tree species richness, forest type abundance and distribution, and forest structure. When considered combined, the two disturbances show additive behavior, enhancing or moderating each other’s effects. Forest management has a negative effect on tree species richness. We expected roe deer to have a negative effect on harvest yields, but this result was significant only for two of seven harvesting treatments. On the other hand, roe deer presence had a positive effect on tree species richness. All the simulation scenarios returned some extent of forest loss. The amount of the forest loss is lowest in the scenario without disturbances, and greatest when both disturbances are considered. However, the two disturbances combined, with the magnitude modelled in our simulations, have relatively low effects on the forest dynamics we analyzed in our study area. LANDIS-II was an effective approach for simulating combined management and ungulate driven trends of forest development, and to help understand the dynamics that lay behind it.

Klíčová slova:

Conifers – Deer – Forest ecology – Forests – Invasive species – Pines – Species diversity – Trees


Zdroje

1. Sanderson EW, Jaiteh M, Levy MA, Redford KH, Wannebo AV, Woolmer G. The Human Footprint and the Last of the WildThe human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. BioScience. 2002;52: 891–904. doi: 10.1641/0006-3568(2002)052[0891:THFATL]2.0.CO;2

2. Bengtsson J, Nilsson SG, Franc A, Menozzi P. Biodiversity, disturbances, ecosystem function and management of European forests. Forest Ecology and Management. 2000;132: 39–50. doi: 10.1016/S0378-1127(00)00378-9

3. Hannah L, Carr JL, Lankerani A. Human disturbance and natural habitat: a biome level analysis of a global data set. Biodivers Conserv. 1995;4: 128–155. doi: 10.1007/BF00137781

4. Johann E. Forest History in Europe. In: Werner D, editor. Biological Resources and Migration. Springer Berlin Heidelberg; 2004. pp. 73–82.

5. Apollonio M, Andersen R, Putman R. European Ungulates and Their Management in the 21st Century. Cambridge University Press; 2010.

6. Coulson T. The Science of Overabundance: Deer Ecology and Population Management. Biodiversity and Conservation. 1999;8: 1719–1721. doi: 10.1023/A:1008918913491

7. Côté SD, Rooney TP, Tremblay J-P, Dussault C, Waller DM. Ecological Impacts of Deer Overabundance. Annual Review of Ecology, Evolution, and Systematics. 2004;35: 113–147. doi: 10.1146/annurev.ecolsys.35.021103.105725

8. Kaji K, Miyaki M, Saitoh T, Ono S, Kaneko M. Spatial Distribution of an Expanding Sika Deer Population on Hokkaido Island, Japan. Wildlife Society Bulletin (1973–2006). 2000;28: 699–707.

9. Kaji K, Okada H, Yamanaka M, Matsuda H, Yabe T. Irruption of a colonizing Sika deer population. Morgart, editor. Journal of Wildlife Management. 2004;68: 889–899. doi: 10.2193/0022-541X(2004)068[0889:IOACSD]2.0.CO;2

10. Gill RMA, Morgan G. The effects of varying deer density on natural regeneration in woodlands in lowland Britain. Forestry (Lond). 2010;83: 53–63. doi: 10.1093/forestry/cpp031

11. Hobbs NT. Modification of Ecosystems by Ungulates. The Journal of Wildlife Management. 1996;60: 695–713. doi: 10.2307/3802368

12. Husheer SW, Coomes DA, Robertson AW. Long-term influences of introduced deer on the composition and structure of New Zealand Nothofagus forests. Forest Ecology and Management. 2003;181: 99–117. doi: 10.1016/S0378-1127(03)00120-8

13. Rooney TP, Waller DM. Direct and indirect effects of white-tailed deer in forest ecosystems. Forest Ecology and Management. 2003;181: 165–176. doi: 10.1016/S0378-1127(03)00130-0

14. Weisberg PJ, Bugmann H. Forest dynamics and ungulate herbivory: from leaf to landscape. Forest Ecology and Management. 2003;181: 1–12. doi: 10.1016/S0378-1127(03)00123-3

15. Joys AC, Fuller RJ, Dolman PM. Influences of deer browsing, coppice history, and standard trees on the growth and development of vegetation structure in coppiced woods in lowland England. Forest Ecology and Management. 2004;202: 23–37. doi: 10.1016/j.foreco.2004.06.035

16. O’brien EA. Human values and their importance to the development of forestry policy in Britain: a literature review. Forestry (Lond). 2003;76: 3–17. doi: 10.1093/forestry/76.1.3

17. Reimoser F, Gossow H. Impact of ungulates on forest vegetation and its dependence on the silvicultural system. Forest ecology and Management. 1996;88: 107–119.

18. Ward AI, White PCL, Smith A, Critchley CH. Modelling the cost of roe deer browsing damage to forestry. Forest Ecology and Management. 2004;191: 301–310. doi: 10.1016/j.foreco.2003.12.018

19. Gerhardt P, Arnold JM, Hackländer K, Hochbichler E. Determinants of deer impact in European forests–A systematic literature analysis. Forest Ecology and Management. 2013;310: 173–186. doi: 10.1016/j.foreco.2013.08.030

20. Gough L, Grace JB. Herbivore Effects on Plant Species Density at Varying Productivity Levels. Ecology. 1998;79: 1586–1594. doi: 10.1890/0012-9658(1998)079[1586:HEOPSD]2.0.CO;2

21. Hurley PM, Webster CR, Flaspohler DJ, Parker GR. Untangling the landscape of deer overabundance: Reserve size versus landscape context in the agricultural Midwest. Biological Conservation. 2012;146: 62–71. doi: 10.1016/j.biocon.2011.10.034

22. Kramer K, Groot Bruinderink GWTA, Prins HHT. Spatial interactions between ungulate herbivory and forest management. Forest Ecology and Management. 2006;226: 238–247. doi: 10.1016/j.foreco.2006.01.037

23. Moore NP, Hart JD, Langton SD. Factors influencing browsing by fallow deer Dama dama in young broad-leaved plantations. Biological Conservation. 1999;87: 255–260. doi: 10.1016/S0006-3207(98)00055-X

24. Schippers P, van Teeffelen AJA, Verboom J, Vos CC, Kramer K, WallisDeVries MF. The impact of large herbivores on woodland–grassland dynamics in fragmented landscapes: The role of spatial configuration and disturbance. Ecological Complexity. 2014;17: 20–31. doi: 10.1016/j.ecocom.2013.07.002

25. Chollet S, Baltzinger C, Ostermann L, Saint-André F, Martin J-L. Importance for forest plant communities of refuges protecting from deer browsing. Forest Ecology and Management. 2013;289: 470–477. doi: 10.1016/j.foreco.2012.10.043

26. Perea R, Gil L. Tree regeneration under high levels of wild ungulates: The use of chemically vs. physically-defended shrubs. Forest Ecology and Management. 2014;312: 47–54. doi: 10.1016/j.foreco.2013.10.022

27. Putman RJ. Grazing in Temperate Ecosystems: Large Herbivores and the Ecology of the New Forest. Springer Science & Business Media; 2012.

28. Shelton AL, Henning JA, Schultz P, Clay K. Effects of abundant white-tailed deer on vegetation, animals, mycorrhizal fungi, and soils. Forest Ecology and Management. 2014;320: 39–49. doi: 10.1016/j.foreco.2014.02.026

29. Jorritsma ITM, van Hees AFM, Mohren GMJ. Forest development in relation to ungulate grazing: a modeling approach. Forest Ecology and Management. 1999;120: 23–34. doi: 10.1016/S0378-1127(98)00540-4

30. Newton AC, Echeverría C, Cantarello E, Bolados G. Projecting impacts of human disturbances to inform conservation planning and management in a dryland forest landscape. Biological Conservation. 2011;144: 1949–1960. doi: 10.1016/j.biocon.2011.03.026

31. White MA. Long-term effects of deer browsing: Composition, structure and productivity in a northeastern Minnesota old-growth forest. Forest Ecology and Management. 2012;269: 222–228. doi: 10.1016/j.foreco.2011.12.043

32. Fyllas NM, Phillips OL, Kunin WE, Matsinos YG, Troumbis AI. Development and parameterization of a general forest gap dynamics simulator for the North-eastern Mediterranean Basin (GREek FOrest Species). Ecological Modelling. 2007;204: 439–456. doi: 10.1016/j.ecolmodel.2007.02.006

33. Mladenoff DJ, Baker WL. Spatial Modeling of Forest Landscape Change: Approaches and Applications. Cambridge University Press; 1999.

34. Scheller RM, Mladenoff DJ. An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems. Landscape Ecol. 2007;22: 491–505. doi: 10.1007/s10980-006-9048-4

35. Seidl R, Fernandes PM, Fonseca TF, Gillet F, Jönsson AM, Merganičová K, et al. Modelling natural disturbances in forest ecosystems: a review. Ecological Modelling. 2011;222: 903–924. doi: 10.1016/j.ecolmodel.2010.09.040

36. Scheller RM, Domingo JB, Sturtevant BR, Williams JS, Rudy A, Gustafson EJ, et al. Design, development, and application of LANDIS-II, a spatial landscape simulation model with flexible temporal and spatial resolution. Ecological Modelling. 2007;201: 409–419. doi: 10.1016/j.ecolmodel.2006.10.009

37. Mladenoff D, Host G, Boeder J, Crow T. A spatial model of forest landscape disturbance, succession and management. GIS and Environmental Modeling: progress and research issues. Ft. Collins, CO; 1996. pp. 175–179.

38. Mladenoff DJ, He HS. Design, behavior and application of LANDIS, an object-oriented model of forest landscape disturbance and succession. Spatial Modeling of Forest Landscape Change: Approaches and Applications. Cambridge University Press; 1999. pp. 125–162.

39. Mladenoff DJ. LANDIS and forest landscape models. Ecological Modelling. 2004;180: 7–19. doi: 10.1016/j.ecolmodel.2004.03.016

40. de Bruijn A, Gustafson EJ, Sturtevant BR, Foster JR, Miranda BR, Lichti NI, et al. Toward more robust projections of forest landscape dynamics under novel environmental conditions: Embedding PnET within LANDIS-II. Ecological Modelling. 2014;287: 44–57. doi: 10.1016/j.ecolmodel.2014.05.004

41. Gustafson EJ, Shvidenko AZ, Sturtevant BR, Scheller RM. Predicting global change effects on forest biomass and composition in south-central Siberia. Ecological Applications. 2010;20: 700–715. doi: 10.1890/08-1693.1 20437957

42. Karam SL, Weisberg PJ, Scheller RM, Johnson DW, Miller WW. Development and evaluation of a nutrient cycling extension for the LANDIS-II landscape simulation model. Ecological Modelling. 2013;250: 45–57. doi: 10.1016/j.ecolmodel.2012.10.016

43. Scheller RM, Mladenoff DJ. A spatially interactive simulation of climate change, harvesting, wind, and tree species migration and projected changes to forest composition and biomass in northern Wisconsin, USA. Global Change Biology. 2005;11: 307–321. doi: 10.1111/j.1365-2486.2005.00906.x

44. Marinis AMD, Chirichella R, Bottero E, Apollonio M. Ecological conditions experienced by offspring during pregnancy and early post-natal life determine mandible size in roe deer. PLOS ONE. 2019;14: e0222150. doi: 10.1371/journal.pone.0222150 31509573

45. Scheller RM, Mladenoff DJ. A forest growth and biomass module for a landscape simulation model, LANDIS: design, validation, and application. Ecological Modelling. 2004;180: 211–229. doi: 10.1016/j.ecolmodel.2004.01.022

46. Gustafson EJ, Shifley SR, Mladenoff DJ, Nimerfro KK, He HS. Spatial simulation of forest succession and timber harvesting using LANDIS. Can J For Res. 2000;30: 32–43. doi: 10.1139/x99-188

47. R. Core Team. R: A language and environment for statistical computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2015. 2015.

48. Bernetti G. Selvicoltura speciale. Unione Tipografico-Editrice Torinese; 1995.

49. Brzeziecki B, Kienast F. Classifying the life-history strategies of trees on the basis of the Grimian model. Forest Ecology and Management. 1994;69: 167–187. doi: 10.1016/0378-1127(94)90227-5

50. Bugmann HKM. On the ecology of mountainous forests in a changing climate: a simulation study. PhD Thesis, ETH Zurich. 1994. doi: 10.3929/ethz-a-000946508

51. Burns RM, Honkala BH. Silvics of north America. Washington, D.C.: United States Department of Agriculture; 1990.

52. Diaz S, Hodgson JG, Thompson K, Cabido M, Cornelissen JHC, Jalili A, et al. The plant traits that drive ecosystems: Evidence from three continents. Journal of Vegetation Science. 2004;15: 295–304. doi: 10.1111/j.1654-1103.2004.tb02266.x

53. Fernandes PM, Vega JA, Jiménez E, Rigolot E. Fire resistance of European pines. Forest Ecology and Management. 2008;256: 246–255. doi: 10.1016/j.foreco.2008.04.032

54. Grime JP, Hodgson JG, Hunt R. Comparative Plant Ecology: A Functional Approach to Common British Species.(Agrostis spp., pp. 58–65.) Unwin Hyman. London, England, UK. 1988.

55. Henne PD, Elkin C, Colombaroli D, Samartin S, Bugmann H, Heiri O, et al. Impacts of changing climate and land use on vegetation dynamics in a Mediterranean ecosystem: insights from paleoecology and dynamic modeling. Landscape Ecol. 2013;28: 819–833. doi: 10.1007/s10980-012-9782-8

56. Lischke H, Zimmermann NE, Bolliger J, Rickebusch S, Löffler TJ. TreeMig: A forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale. Ecological Modelling. 2006;199: 409–420. doi: 10.1016/j.ecolmodel.2005.11.046

57. Niinemets Ü, Valladares F. Tolerance to Shade, Drought, and Waterlogging of Temperate Northern Hemisphere Trees and Shrubs. Ecological Monographs. 2006;76: 521–547. doi: 10.1890/0012-9615(2006)076[0521:TTSDAW]2.0.CO;2

58. Ordóñez García JL. Análisis y modelización del reclutamiento de Pinus nigra en zonas afectadas por grandes incendios. PhD Thesis, Universitat Autònoma de Barcelona,. 2004. Available: https://ddd.uab.cat/record/38508

59. Paula S, Arianoutsou M, Kazanis D, Tavsanoglu Ç, Lloret F, Buhk C, et al. Fire-related traits for plant species of the Mediterranean Basin. Ecology. 2009;90: 1420–1420. doi: 10.1890/08-1309.1

60. Schumacher S, Reineking B, Sibold J, Bugmann H. Modeling the Impact of Climate and Vegetation on Fire Regimes in Mountain Landscapes. Landscape Ecol. 2006;21: 539–554. doi: 10.1007/s10980-005-2165-7

61. Verdú M. Age at Maturity and Diversification in Woody Angiosperms. Evolution. 2002;56: 1352–1361. doi: 10.1111/j.0014-3820.2002.tb01449.x 12206237

62. Vittoz P, Engler R. Seed dispersal distances: a typology based on dispersal modes and plant traits. Bot Helv. 2007;117: 109–124. doi: 10.1007/s00035-007-0797-8

63. Kattge J, Díaz S, Lavorel S, Prentice IC, Leadley P, Bönisch G, et al. TRY–a global database of plant traits. Global Change Biology. 2011;17: 2905–2935. doi: 10.1111/j.1365-2486.2011.02451.x

64. LAMMA. Realizzazione delle unità di paesaggio, delle tipologie pedologiche e unità cartografiche del bacino idrografico del fiume Arno. LAMMA, Consortium; 2010.

65. Chianucci F, Mattioli L, Amorini E, Giannini T, Marcon A, Chirichella R, et al. Early and long-term impacts of browsing by roe deer in oak coppiced woods along a gradient of population density. Annals of Silvicultural Research. 2015 [cited 14 May 2018]. doi: 10.12899/asr-945

66. Cutini A, Chianucci F, Giannini T, Tiberi R, Amorini E. Effetti del morso di capriolo sull’accrescimento di cedui di cerro e di castagno. Ann CRA-Centro Ric Selv. 2009;36: 79–86.

67. Cutini A, Bongi P, Chianucci F, Pagon N, Grignolio S, Amorini E, et al. Roe deer (Capreolus capreolus L.) browsing effects and use of chestnut and Turkey oak coppiced areas. Annals of Forest Science. 2011;68: 667–674. doi: 10.1007/s13595-011-0072-4

68. Szmidt A. Food preference of roe deer in relation to principal species of forest trees and shrubs. Acta Theriol. 1975;20: 255–266. doi: 10.4098/AT.arch.75-22

69. Katona K, Kiss M, Bleier N, Székely J, Nyeste M, Kovács V, et al. Ungulate browsing shapes climate change impacts on forest biodiversity in Hungary. Biodivers Conserv. 2013;22: 1167–1180. doi: 10.1007/s10531-013-0490-8

70. Ward BC. Landscape-level effects of the interaction between residential development and public forest management in northern Wisconsin, USA. Master Thesis, University of Wisconsin–Madison. 2004.

71. Kaufman L, Rousseeuw PJ. Partitioning around medoids (program pam). Finding groups in data: an introduction to cluster analysis. 1990; 68–125.

72. Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K. cluster: Cluster Analysis Basics and Extensions. R package version 2.0. 1. 2015. 2017.

73. Jaccard P. Étude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull Soc Vaudoise Sci Nat. 1901;37: 547–579.

74. Aber J, Ollinger S, Federer C, Reich P, Goulden M, Kicklighter D, et al. Predicting the effects of climate change on water yield and forest production in the northeastern United States. Climate Research. 1995;5: 207–222. doi: 10.3354/cr005207

75. Xu C, Gertner GZ, Scheller RM. Uncertainties in the response of a forest landscape to global climatic change. Global Change Biology. 2009;15: 116–131. doi: 10.1111/j.1365-2486.2008.01705.x

76. Busing RT, White PS. Species Diversity and Small-Scale Disturbance in an Old-Growth Temperate Forest: A Consideration of Gap Partitioning Concepts. Oikos. 1997;78: 562–568. doi: 10.2307/3545618

77. Brokaw NVL. The Definition of Treefall Gap and Its Effect on Measures of Forest Dynamics. Biotropica. 1982;14: 158–160. doi: 10.2307/2387750

78. Pellerin M, Saïd S, Richard E, Hamann J-L, Dubois-Coli C, Hum P. Impact of deer on temperate forest vegetation and woody debris as protection of forest regeneration against browsing. Forest Ecology and Management. 2010;260: 429–437. doi: 10.1016/j.foreco.2010.04.031

79. Burnham KP, Anderson DR. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer Science & Business Media; 2003.

80. Shang Z, He HS, Xi W, Shifley SR, Palik BJ. Integrating LANDIS model and a multi-criteria decision-making approach to evaluate cumulative effects of forest management in the Missouri Ozarks, USA. Ecological Modelling. 2012;229: 50–63. doi: 10.1016/j.ecolmodel.2011.08.014


Článek vyšel v časopise

PLOS One


2019 Číslo 11
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

KOST
Koncepce osteologické péče pro gynekology a praktické lékaře
nový kurz
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Svět praktické medicíny 5/2023 (znalostní test z časopisu)

Imunopatologie? … a co my s tím???
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D.

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#