Average niche breadths of species in lake macrophyte communities respond to ecological gradients variably in four regions on two continents
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Different species’ niche breadths in relation to ecological gradients are infrequently examined within the same study and, moreover, species niche breadths have rarely been averaged to account for variation in entire ecological communities. We investigated how average environmental niche breadths (climate, water quality and climate–water quality niches) in aquatic macrophyte communities are related to ecological gradients (latitude, longitude, altitude, species richness and lake area) among four distinct regions (Finland, Sweden and US states of Minnesota and Wisconsin) on two continents. We found that correlations between the three different measures of average niche breadths and ecological gradients varied considerably among the study regions, with average climate and average water quality niche breadth models often showing opposite trends. However, consistent patterns were also found, such as widening of average climate niche breadths and narrowing of average water quality niche breadths of aquatic macrophytes along increasing latitudinal and altitudinal gradients. This result suggests that macrophyte species are generalists in relation to temperature variations at higher latitudes and altitudes, whereas species in southern, lowland lakes are more specialised. In contrast, aquatic macrophytes growing in more southern nutrient-rich lakes were generalists in relation to water quality, while specialist species are adapted to low-productivity conditions and are found in highland lakes. Our results emphasise that species niche breadths should not be studied using only coarse-scale data of species distributions and corresponding environmental conditions, but that investigations on different kinds of niche breadths (e.g., climate vs. local niches) also require finer resolution data at broad spatial extents.
KeywordsAquatic plants Climate Lakes Latitude Niche width Water quality
We thank Konsta Happonen for the assistance with the tables. Sampling of Finnish macrophyte data was a joint contribution of Biological Monitoring of Finnish Freshwaters under diffuse loading project (XPR3304) financed by Ministry of Agriculture and Forestry and national surveillance monitoring programmes of lakes. Swedish macrophyte data were surveyed within the Swedish Monitoring Program of macrophytes in lakes funded by the Swedish Agency for Marine and Water Management. We are grateful for Minnesota and Wisconsin Departments of Natural Resources for collecting the macrophyte data. We especially thank Carol Reschke from the University of Minnesota Duluth for her work in combining and performing quality control for the Minnesota macrophyte data used in the analysis, and the Minnesota DNR staff for collecting the macrophyte data. This study was supported by grants from the Academy of Finland (267995 and 285040). This is contribution number 607 of the Natural Resources Research institute of the University of Minnesota Duluth.
Author contribution statement
JH conceived the original idea, and JH, JA and AV designed the methodology. JA, FE, LBJ and LS provided the data, which was further processed by JA and AV. The data were analysed by JA and AV. JA wrote the manuscript, which was contributed to and approved by other authors.
- Alahuhta J, Vuori K-M, Luoto M (2011) Land use, geomorphology and climate as environmental determinants of emergent aquatic macrophytes in boreal catchments. Boreal Environ Res 16:185–202Google Scholar
- Bartoń K (2016) Model selection and model averaging based on information criteria (AICc and alike). In: MuMIn: Multi-Model Inference. https://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf. Accessed 25 Oct 2016
- Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G, García Marquéz JR, Gruber B, Lafourcade B, Leitão PJ, Münkemüller T, McClean C, Osborne PE, Reineking B, Schröder B, Skidmore AK, Zurell D, Lautenbach S (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46. doi: 10.1111/j.1600-0587.2012.07348.x CrossRefGoogle Scholar
- Elser JJ, Bracken MES, Cleland EE, Gruner DS, Harpole WS, Hillebrand H, Ngai JT, Seabloom EW, Shurin JB, Smith JE (2007) Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems. Ecol Lett 10:1135–1142. doi: 10.1111/j.1461-0248.2007.01113.x CrossRefPubMedGoogle Scholar
- Giraudoux P (2016) Pgirmess: data analysis in ecology. https://CRAN.R-project.org/package=pgirmess
- Heino J, Toivonen H (2008) Aquatic plant biodiversity at high latitudes: patterns of richness and rarity in Finnish freshwater macrophytes. Boreal Environ Res 13:1–14Google Scholar
- Heino J, Melo AS, Bini LM, Altermatt F, Al-Shami SA, Angeler D, Bonada N, Brand C, Callisto M, Cottenie K, Dangles O, Dudgeon D, Encalada A, Göthe E, Grönroos M, Hamada N, Jacobsen D, Landeiro VL, Ligeiro R, Martins RT, Miserendino ML, Md Rawi CS, Rodrigues M, Roque FO, Sandin L, Schmera D, Sgarbi LF, Simaika J, Siqueira T, Thompson RM, Townsend CR (2015b) A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels. Ecol Evol 5:1235–1248. doi: 10.1002/ece3.1439 CrossRefPubMedPubMedCentralGoogle Scholar
- Kraft NJB, Comita LS, Chase JM, Sanders NJ, Swenson NG, Crist TO, Stegen JC, Vellend M, Boyle B, Anderson MJ, Cornell HV, Davies KF, Freestone AL, Inouye BD, Harrison SP, Myers JA (2011) Disentangling the drivers of β-diversity along latitudinal and elevational gradients. Science 333:1755–1758. doi: 10.1126/science.12085584 CrossRefPubMedGoogle Scholar
- MacArthur RH (1968) The theory of the niche. In: Lewontin RC (ed) Population biology and evolution. Syracuse University Press, Syracuse, pp 159–176Google Scholar
- MacArthur RH (1972) Geographical ecology. Princeton University Press, PrincetonGoogle Scholar
- Nathans L, Oswald FL, Nimon K (2012) Interpreting multiple linear regression: a guidebook of variable importance. Pract Assess Res Eval 17:1–19. http://hdl.handle.net/1911/71096
- Naturvårdsverket (2010) Handledning för miljöövervakning - Undersökningstyp: Makrofyter i sjöar. Available at https://www.havochvatten.se/download/18.64f5b3211343cffddb280004851/Makrofyter+i+sj%C3%B6ar.pdf
- Nimon K, Oswald F, Roberts JK (2013) Yhat: interpreting regression effects. https://CRAN.R-project.org/package=yhat
- Petrocelli JV (2003) Hierarchical multiple regression in counselling research: common problems and possible remedies. Meas Eval Couns Dev 36:9–22Google Scholar