AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (980.7 KB)
Collect
AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

A guide for selecting the appropriate plot design to measure ungulate browsing

Suzanne T.S. van Beeck Calkoena,1( )Jérôme Milcha,b,1Andrea D. KupferschmidcChristian Fiderera,bMarco Heuricha,b,d
Department of Visitor Management and National Park Monitoring, Bavarian Forest National Park, Freyunger Straße 2, 94481 Grafenau, Germany
Wildlife Ecology and Management, Albert-Ludwigs-University of Freiburg, Tennenbacher Str. 4, 79106 Freiburg, Germany
Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland
Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, Institute for Forest and Wildlife Management, Campus Evenstad, Koppang, Norway

1 Both authors contributed equally to the published work.

Show Author Information

Abstract

Ungulate browsing often impairs tree regeneration, thus preventing the achievement of economic or conservation goals. Forest ungulate management would thus benefit from a practical decision tool that facilitates method selection from a wide range of monitoring methods and indicators currently available. In this study, we first provide an overview of the different browsing-impact monitoring methods and indicators currently applied. We then present a newly developed decision matrix for method evaluation that can assist forest stakeholders in choosing the browsing-impact monitoring method best suited to their needs, based on the selected indicators. The first step involved two separate literature reviews to create an overview of the currently applied methods and to select the indicators best suited for measuring browsing impact. Three types of indicator groups with their respective parameters were considered important for method evaluation: browsing indicators (e.g. regeneration density, browsing incidents), performance indicators (e.g. expense, expertise) and data quality indicators (e.g. susceptibility to measurement errors). Subsequently, all parameters defined within each indicator group were categorised and a grade was assigned to each category. To create the final method-indicator matrix, each browsing-impact monitoring method received a grade for each parameter within all indicator groups, reflecting the specific advantages and disadvantages of implementing the respective parameter within a specific method. The utility of the matrix in selecting the most suitable monitoring method was then demonstrated using the example of Germany's national parks. Based on the weights added to the method-indicator matrix, as defined by national park representatives, and considering local requirements the nearest-tree method was favoured over the other two methods. This newly developed matrix provides a more scientific objectification of ungulate browsing-impact measures and can be easily used by forest managers to address their own requirements, based on a consideration of the advantages and disadvantages of the included methods.

References

 

Abrams, M.D., Johnson, S.E., 2012. Long-term impacts of deer exclosures on mixed-oak forest composition at the Valley Forge National Historical Park, Pennsylvania, USA. J. Torrey Bot. Soc. 139, 167-180. https://doi.org/10.3159/torrey-d-11-00075.1.

 

Andreasen, J.K., O'Neill, R.V., Noss, R., Slosser, N.C., 2001. Considerations for the development of a terrestrial index of ecological integrity. Ecol. Indicat. 1, 21-35. https://doi.org/10.1016/S1470-160X(01)00007-3.

 

Angst, J.K., Kupferschmid, A.D., 2023. Assessing browsing impact in beech forests: the importance of tree responses after browsing. Diversity 15, 262.

 

Apollonio, M., Andersen, R., Putman, R., 2010. European ungulates and their management in the 21st century. Cambridge University Press, UK.

 

Archaux, F., Camaret, S., Dupouey, J. -L., Ulrich, E., Corcket, E., Bourjot, L., Brêthes, A., Chevalier, R., Dobremez, J.F., Dumas, Y., Dumé, G., Forêt, M., Forgeard, F., Gallet, M.L., Picard, J.F., Richard, F., Savoie, J.M., Seytre, L., Timbal, J., Touffet, J., 2009. Can we reliably estimate species richness with large plots? an assessment through calibration training. Plant Ecol. 203, 303-315. https://doi.org/10.1007/s11258-008-9551-6.

 

Archaux, F., Gosselin, F., Bergès, L., Chevalier, R., 2006. Effects of sampling time, species richness and observer on the exhaustiveness of plant censuses. J. Veg. Sci. 17, 299-306. https://doi.org/10.1111/j.1654-1103.2006.tb02449.x.

 

Avery, T.E., Burkhart, H.E., 2002. Forest Measurements, fifth ed. Waveland Press, Long Grove, Illinois.

 

Bergqvist, G., Bergström, R., Wallgren, M., 2014. Recent browsing damage by moose on Scots pine, birch and aspen in young commercial forests – effects of forage availability, moose population density and site productivity. Silva Fenn. 48, 1077. https://doi.org/10.14214/sf.1077.

 

Bergström, R., Edenius, L., 2003. From twigs to landscapes – methods for studying ecological effects of forest ungulates. J. Nat. Conserv. 10, 203-211. https://doi.org/10.1078/1617-1381-00020.

 

Bernes, C., Macura, B., Jonsson, B.G., Junninen, K., Müller, J., Sandström, J., Lohmus, A., Macdonald, E., 2018. Manipulating ungulate herbivory in temperate and boreal forests: effects on vegetation and invertebrates. A systematic review. Environ. Evid. 7, 13. https://doi.org/10.1186/s13750-018-0125-3.

 

Bonnot, N.C., Couriot, O., Berger, A., Cagnacci, F., Ciuti, S., De Groeve, J., Gehr, B., Heurich, M., Kjellander, P., Kröschel, M., Morellet, N., Sönnichsen, L., Hewison, A.J.M., 2020. Fear of the dark? Contrasting impacts of humans versus lynx on diel activity of roe deer across Europe. J. Anim. Ecol. 89, 132-145. https://doi.org/10.1111/1365-2656.13161.

 

Boulanger, V., Dupouey, J. -L., Archaux, F., Badeau, V., Baltzinger, C., Chevalier, R., Corcket, E., Dumas, Y., Forgeard, F., Mårell, A., Montpied, P., Paillet, Y., Picard, J.F., Saïd, S., Ulrich, E., 2018. Ungulates increase forest plant species richness to the benefit of non-forest specialists. Global Change Biol. 24, E485-E495. https://doi.org/10.1111/gcb.13899.

 

Bryant, D.M., Ducey, M.J., Innes, J.C., Lee, T.D., Eckert, R.T., Zarin, D.J., 2005. Forest community analysis and the point-centered quarter method. Plant Ecol. 175, 193-203. https://doi.org/10.1007/s11258-005-0013-0.

 

Cailleret, M., Heurich, M., Bugmann, H., 2014. Reduction in browsing intensity may not compensate climate change effects on tree species composition in the Bavarian Forest National Park. For. Ecol. Manag. 328, 179-192. https://doi.org/10.1016/j.foreco.2014.05.030.

 

Cantarello, E., Newton, A.C., 2008. Identifying cost-effective indicators to assess the conservation status of forested habitats in Natura 2000 sites. For. Ecol. Manag. 256, 815-826. https://doi.org/10.1016/J.FORECO.2008.05.031.

 

Churski, M., Bubnicki, J.W., Jędrzejewska, B., Kuijper, D.P.J., Cromsigt, J.P.G.M., 2017. Brown world forests: increased ungulate browsing keeps temperate trees in recruitment bottlenecks in resource hotspots. New Phytol. 214, 158-168. https://doi.org/10.1111/nph.14345.

 

Côté, S.D., Rooney, T.P., Tremblay, J. -P., Dussault, C., Waller, D.M., 2004. Ecological impacts of deer overabundance. Annu. Rev. Ecol. Evol. Syst. 35, 113-147. https://doi.org/10.1146/annurev.ecolsys.35.021103.105725.

 

Cukor, J., Vacek, Z., Linda, R., Vacek, S., Marada, P., Simunek, V., Havránek, F., 2019. Effects of bark stripping on timber production and structure of Norway spruce forests in relation to climatic factors. Forests 10, 320. https://doi.org/10.3390/f10040320.

 

Dale, V.H., Beyeler, S.C., 2001. Challenges in the development and use of ecological indicators. Ecol. Indicat. 1, 3-10. https://doi.org/10.1016/S1470-160X(01)00003-6.

 
Düggelin, C., Abegg, M., Bischof, S., Br€ andli, U.B., Cioldi, F., Fischer, C., Meile, R., 2020. Schweizerisches Landesforstinventar: Anleitung für die Feldaufnahmen der fünften Erhebung 2018-2026. Eidg. Forschungsanstalt für Wald, Schnee und Landschaft WSL.
 

Edenius, L., Danell, K., Nyquist, H., 1995. Effects of simulated moose browsing on growth, mortality, and fecundity in Scots pine: relations to plant productivity. Can. J. For. Res. 25, 529-535. https://doi.org/10.1139/x95-060.

 

Eiberle, K., Nigg, H., 1987. Criteria for permissible browse impact on sycamore maple (Acer pseudoplatanus) in mountain forests. Experientia 43, 127-133. https://doi.org/10.1007/BF01942830.

 

Endress, B.A., Naylor, B.J., Pekin, B.K., Wisdom, M.J., 2016. Aboveground and belowground mammalian herbivores regulate the demography of deciduous woody species in conifer forests. Ecosphere 7, 1-18. https://doi.org/10.1002/ecs2.1530.

 

Failing, L., Gregory, R., 2003. Ten common mistakes in designing biodiversity indicators for forest policy. J. Environ. Manag. 68, 121-132. https://doi.org/10.1016/S0301-4797(03)00014-8.

 

Franklin, J.F., Shugart, H.H., Harmon, M.E., 1987. Tree death as an ecological process. Bioscience 37, 550-556.

 

Gill, R.M.A., 1992. A review of damage by mammals in north temperate forests: 3. Impact on trees and forests. Forestry 65, 363-388. https://doi.org/10.1093/forestry/65.4.363-a.

 

Gill, R.M.A., Beardall, V., 2001. The impact of deer on woodlands: the effects of browsing and seed dispersal on vegetation structure and composition. Forestry 74, 209-218. https://doi.org/10.1093/forestry/74.3.209.

 

Gregoire, T.G., Valentine, H.T., 2007. Sampling Strategies for Natural Resources and the Environment. Chapman and Hall/CRC, New York.

 

Habeck, C.W., Schultz, A.K., 2015. Community-level impacts of white-tailed deer on understorey plants in North American forests: a meta-analysis. AoB Plants 7, plv119. https://doi.org/10.1093/aobpla/plv119.

 

Huber, M.O., Schwyzer, A., Kupferschmid, A.D., 2018. A comparison between plot-count and nearest-tree method in assessing tree regeneration features. Curr. Trends For. Res. https://doi.org/10.29011/2638-0013.100022.

 

Keller, M., 2011. Swiss National Forest Inventory. Manual of the Field Survey 2004–2007. Swiss Federal Research Institute WSL Birmensdorf, p. 269.

 

Kennedy, K.A., Addison, P.A., 1987. Some considerations for the use of visual estimates of plant cover in biomonitoring. J. Ecol. 75, 151. https://doi.org/10.2307/2260541.

 

Kleinn, C., Vilčko, F., 2005. Ein Vergleich von zwei methodischen Konzepten für die Grundgesamtheit von Probeflächen bei Waldinventuren. Allgemeine Forst- und Jagdzeitung 176 (4), 68-74.

 

Kleinn, C., Vilčko, F., 2006a. Design-unbiased estimation for point-to-tree distance sampling. Can. J. For. Res. 36, 1407-1414. https://doi.org/10.1139/X06-038.

 

Kleinn, C., Vilčko, F., 2006b. A new empirical approach for estimation in k-tree sampling. For. Ecol. Manag. 237, 522-533. https://doi.org/10.1016/j.foreco.2006.09.072.

 
Kramer, H., Alparslan, A., 2008. Leitfaden zur Waldmesslehre, 5. überarbeitetete Auflage. J.D. Sauerländer's Verlag, Frankfurt am Main.
 

Krebs, C.J., 2014. Ecological Methodology. Benjamin Cummings, Addison Wesley, CA.

 

Krueger, L.M., Peterson, C.J., Royo, A., Carson, W.P., 2009. Evaluating relationships among tree growth rate, shade tolerance, and browse tolerance following disturbance in an eastern deciduous forest. Can. J. For. Res. 39, 2460-2469.

 

Kuijper, D.P.J., De Kleine, C., Churski, M., van Hooft, P., Bubnicki, J., Jedrzejewska, B., 2013. Landscape of fear in Europe: wolves affect spatial patterns of ungulate browsing in Białowieża Primeval Forest, Poland. Ecography 36, 1263-1275.

 

Kuijper, D.P.J., Jędrzejewska, B., Brzeziecki, B., Churski, M., Jedrzejewski, W., Zybura, H., 2010. Fluctuating ungulate density shapes tree recruitment in natural stands of the Białowieża Primeval Forest, Poland. J. Veg. Sci. 21, 1082-1098. https://doi.org/10.1111/j.1654-1103.2010.01217.x.

 

Kupferschmid, A.D., 2018. Selective browsing behaviour of ungulates influences the growth of Abies alba differently depending on forest type. For. Ecol. Manag. 429, 317-326. https://doi.org/10.1016/j.foreco.2018.06.046.

 

Kupferschmid, A.D., Bugmann, H., 2013. Timing, light availability and vigour determine the response of Abies alba saplings to leader shoot browsing. Eur. J. For. Res. 132, 47-60. https://doi.org/10.1007/s10342-012-0653-2.

 

Kupferschmid, A.D., Bütikofer, L., Hothorn, T., Schwyzer, A., Brang, P., 2020. Ungulate species and abundance as well as environmental factors determine the probability of terminal shoot browsing on temperate forest trees. Forests 11, 764. https://doi.org/10.3390/f11070764.

 

Kupferschmid, A.D., Gmür, P.A., 2020. Methods for estimating the influence of browsing: comparison of the measurements on the k nearest trees with plot-count sampling. Schweiz. Z. Forstwes. 171, 69-78. https://doi.org/10.3188/szf.2020.0069.

 

Kupferschmid, A.D., Greilsamer, R., Brang, P., Bugmann, H., 2022a. Assessment of the impact of ungulate browsing on tree regeneration. Anim. Nutr. IntechOpen. https://doi.org/10.5772/intechopen.108667.

 
Kupferschmid, A.D., Menendez, A., Sands, N., 2017. Compensation capacity of Central European tree species in response to leader shoot browsing. In: Menendez, A., Sands, N. (Eds.), Ungulates Evolution, Diversity and Ecology. Nova Science Publishers, USA.
 

Kupferschmid, A.D., Seitz, L., Josi, J., Hothorn, T., 2022b. Assessment of Ungulate Effects on Trees in the Canton of Vaud. Swiss Federal Research Institute WSL, Birmensdor. https://doi.org/10.55419/wsl:31433.

 

Kupferschmid, A.D., Wasem, U., Bugmann, H., 2015. Browsing regime and growth response of Abies alba saplings planted along light gradients. Eur. J. For. Res. 134, 75-87. https://doi.org/10.1007/s10342-014-0834-2.

 

Legg, C.J., Nagy, L., 2006. Why most conservation monitoring is, but need not be, a waste of time. J. Environ. Manag. 78, 194-199. https://doi.org/10.1016/J.JENVMAN.2005.04.016.

 

Lindenmayer, D.B., Likens, G.E., 2010. Effective Ecological Monitoring. Earthscan, London.

 

Lynch, T.B., Rusydi, R., 1999. Distance sampling for forest inventory in Indonesian teak plantations. For. Ecol. Manag. 113, 215-221. https://doi.org/10.1016/S0378-1127(98)00427-7.

 

Mandallaz, D., 2006. Sampling Techniques for Forest Inventories, Applied En. Chapman and Hall/CRC, Boca Raton.

 

Morin, X., Fahse, L., Jactel, H., Scherer-Lorenzen, M., García-Valdés, R., Bugmann, H., 2018. Long-term response of forest productivity to climate change is mostly driven by change in tree species composition. Sci. Rep. 8, 1-12. https://doi.org/10.1038/s41598-018-23763-y.

 

Morrison, L.W., 2016. Observer error in vegetation surveys: a review. J. Plant Ecol. 9, 367-379. https://doi.org/10.1093/jpe/rtv077.

 

Motta, R., 2003. Ungulate impact on rowan (Sorbus aucuparia L.) and Norway spruce (Picea abies (L.) Karst.) height structure in mountain forests in the eastern Italian Alps. For. Ecol. Manag. 181, 139-150. https://doi.org/10.1016/S0378-1127(03)00128-2.

 

Nichols, J.D., Williams, B.K., 2006. Monitoring for conservation. Trends Ecol. Evol. 21, 668-673.

 

Nomiya, H., Suzuki, W., Kanazashi, T., Shibata, M., Tanaka, H., Nakashizuka, T., 2003. The response of forest floor vegetation and tree regeneration to deer exclusion and disturbance in a riparian deciduous forest, central Japan. Plant Ecol. 164, 263-276. https://doi.org/10.1023/A:1021294021438.

 

Nopp-Mayr, U., Schöll, E.M., Sachser, F., Reimoser, S., Reimoser, F., 2023. Does ungulate herbivory translate into diversity of woody plants? A long-term study in a montane forest ecosystem in Austria. Diversity 15, 165.

 

Noss, R.F., 1990. Indicators for monitoring biodiversity: a hierarchical approach. Conserv. Biol. 4, 355-364.

 

Pellerin, M., Saïd, S., Richard, E., Hamann, J.L., Dubois-Coli, C., Hum, P., 2010. Impact of deer on temperate forest vegetation and woody debris as protection of forest regeneration against browsing. For. Ecol. Manag. 260, 429-437. https://doi.org/10.1016/j.foreco.2010.04.031.

 

Pelletier, F., 2014. Effects of tourist activities on ungulate behaviour in a mountain protected area. J. Mt. Ecol. 8, 15-19.

 

Proffitt, K.M., Grigg, J.L., Hamlin, K.L., Garrott, R.A., 2009. Contrasting effects of wolves and human hunters on elk behavioral responses to predation risk. J. Wildl. Manag. 73, 345-356. https://doi.org/10.2193/2008-210.

 

Ramezani, H., Grafström, A., Naghavi, H., Fallah, A., Shataee, S., Soosani, J., 2016. Evaluation of K-tree distance and fixed-sized plot sampling in zagros forests of western Iran. J. Agric. Sci. Technol. 18, 155-170.

 

Rawinski, T.J., 2018. Monitoring White-tailed Deer Impacts: the Ten-Tallest Method. Newtown Square, PA, USA.

 

Reimoser, F., Armstrong, H., Suchant, R., 1999. Measuring forest damage of ungulates: what should be considered. For. Ecol. Manag. 120, 47-58. https://doi.org/10.1016/S0378-1127(98)00542-8.

 
Reimoser, F., Putman, R., 2011. Impacts of wild ungulates on vegetation: costs and benefits. In: Putman, R., Apollonio, M., Andersen, R. (Eds.), Ungulate Management in Europe. Problems and Practices. Cambridge University Press, Cambridge, pp. 144–191.
 
Reimoser, F., Reimoser, S., Schodterer, H., 2014. In: Erfassung und Beurteilung des Schalenwildeinflusses auf die Waldverjüngung – Vergleich verschiedener Methoden des Wildeinfluss-Monitorings. ("WEM-methodenvergleich"). BFW Publishers, Vienna.
 

Rooney, T.P., Waller, D.M., 2003. Direct and indirect effects of white-tailed deer in forest ecosystems. For. Ecol. Manag. 181, 165-176. https://doi.org/10.1016/s0378-1127(03)00130-0.

 

Royo, A.A., Collins, R., Adams, M.B., Kirschbaum, C., Carson, W.P., 2010. Pervasive interactions between ungulate browsers and disturbance regimes promote temperate forest herbaceous diversity. Ecology 91, 93-105. https://doi.org/10.1890/08-1680.1.

 

Rüegg, D., Nigg, H., 2003. Mehrstufige Verjüngungskontrollen und Grenzwerte für die Verbissintensität | Comparitive regeneration control and limiting value of browsing damage intensity. Schweiz. Z. Forstwes. 154, 314-321. https://doi.org/10.3188/szf.2003.0314.

 

Schulze, E.D., Bouriaud, O., Wäldchen, J., Eisenhauer, N., Walentowski, H., Seele, C., Heinze, E., Pruschitzki, U., Danila, G., Marin, G., Hessenmöller, D., Bouriaud, L., Teodosiu, M., 2014. Ungulate browsing causes species loss in deciduous forests independent of community dynamics and silvicultural management in Central and Southeastern Europe. Ann. For. Res. 57, 267-288. https://doi.org/10.15287/afr.2014.273.

 

Scott, C.T., 1998. Sampling methods for estimating change in forest resources. Ecol. Appl. 8, 228-233. https://doi.org/10.1890/1051-0761(1998)008[0228:SMFECI]2.0.CO;2.

 

Simončič, T., Bončina, A., Jarni, K., Klopčič, M., 2019. Assessment of the long-term impact of deer on understory vegetation in mixed temperate forests. J. Veg. Sci. 30 (1), 108-120.

 
Smit, C., Putman, R., 2010. Large herbivores as 'environmental engineers. In: Putman, R., Apollonio, M., Andersen, R. (Eds.), Ungulate Management in Europe. Problems and Practices. Cambridge University Press, Cambridge, pp. 260–283.
 

Stankowich, T., 2008. Ungulate flight responses to human disturbance: a review and meta-analysis. Biol. Conserv. 141, 2159-2173. https://doi.org/10.1016/j.biocon.2008.06.026.

 
Stein, W.I., 1992. Regeneration Surveys and Evaluation. Forest Research Laboratory, Oregon State University, Corvallis, USA.
 

Theuerkauf, J., Rouys, S., 2008. Habitat selection by ungulates in relation to predation risk by wolves and humans in the Białowieża Forest, Poland. For. Ecol. Manag. 256, 1325-1332.

 

Tremblay, J.-P., Huot, J., Potvin, F., 2007. Density-related effects of deer browsing on the regeneration dynamics of boreal forests. J. Appl. Ecol. 44, 552-562. https://doi.org/10.1111/j.1365-2664.2007.01290.x.

 

Valente, A.M., Acevedo, P., Figueiredo, A.M., Fonseca, C., Torres, R.T., 2020. Overabundant wild ungulate populations in Europe: management with consideration of socio-ecological consequences. Mamm. Rev. 50, 353-366. https://doi.org/10.1111/mam.12202.

 

van Beeck Calkoen, S.T.S., Kreikenbohm, R., Kuijper, D.P.J., Heurich, M., 2021. Olfactory cues of large carnivores modify red deer behavior and browsing intensity. Behav. Ecol. 32, 982-992. https://doi.org/10.1093/beheco/arab071.

 

Vowles, T., Molau, U., Lindstein, L., Molau, M., Bjorkm, R.G., 2016. The impact of shrub browsing by mountain hare and reindeer in subarctic Sweden. Plant Ecol. Divers. 9, 421-428. https://doi.org/10.1080/17550874.2016.1264017.

 
Wotschikowsky, U., 2010. Ungulates ad their management in Germany. In: Apollonio, M., Andersen, R., Putman, R. (Eds.), European Ungulates and Their Management in the 21st Century. Cambridge University Press, Cambridge, p. 604.
Forest Ecosystems
Article number: 100147
Cite this article:
van Beeck Calkoen ST, Milch J, Kupferschmid AD, et al. A guide for selecting the appropriate plot design to measure ungulate browsing. Forest Ecosystems, 2023, 10(6): 100147. https://doi.org/10.1016/j.fecs.2023.100147

183

Views

5

Downloads

0

Crossref

0

Web of Science

0

Scopus

0

CSCD

Altmetrics

Received: 26 May 2023
Revised: 17 October 2023
Accepted: 26 October 2023
Published: 05 November 2023
© 2023 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Return