Species richness and taxonomic distinctness of lake macrophytes along environmental gradients in two continents

TLDR: In this paper, the response of species richness and average taxonomic distinctness of aquatic macrophytes along environmental gradients using linear regression models and Bayesian Information Criterion variable selection method was tested.

Abstract: The biodiversity of aquatic ecosystems is under threat and there is an urgent need to quantify the various facets of biodiversity to assess the conservation value of freshwater ecosystems. The effects of taxonomic relatedness have so far not been taken into account in biodiversity assessments of lake macrophytes. We therefore tested the response of species richness and average taxonomic distinctness (AvTD) of aquatic macrophytes along environmental gradients using linear regression models and Bayesian Information Criterion variable selection method. We selected data from four regions, each with 50–60 lakes, situated in northern Europe (Finland and Sweden) and northern America (Minnesota and Wisconsin). We separately studied all macrophyte species, hydrophytes and helophytes. Species richness and AvTD of aquatic macrophytes were generally negatively related in all regions, although it was not statistically significant. Both biodiversity measures responded to environmental gradients to various degrees among the studied macrophyte groups and regions. Species richness was best explained by alkalinity and lake area in Finland, by elevation, annual mean temperature and total phosphorus in Minnesota, and by alkalinity in Wisconsin. AvTD was best explained by alkalinity, annual mean temperature and total phosphorus in Finland and by alkalinity in Wisconsin. Very weak relationships were found in Sweden. Our findings strongly suggest that complementary indices are needed to indicate more comprehensively the effects of environmental conditions on freshwater biodiversity. Species richness was found to be a better measure than AvTD to account for conservation value in freshwaters. However, further research is required to evaluate the usefulness of AvTD to indicate conservation value (e.g. randomisation tests), because alternative measures are clearly needed for those freshwater taxa lacking complete information on true phylogenetic diversity.

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Table 3. Bivariate Spearman correlation matrix between species richness and average taxonomic distinctness for different functional plant groups and different regions. ***: p ≤ 0.001; **: p ≤ 0.01; *: p ≤ 0.05.

Table 2. Number of studied lakes (n), and mean, minimum, maximum and SD of species richness (S) or average taxonomic distinctness (AvTD) for all taxa, hydrophytes and helophytes in each study region. The number of lakes can vary between different functional macrophyte groups within a region, because average taxonomic distinctness can only be calculated when there are two or more species found in a lake.

Table 4. Summary of analyses explaining the relationship between species richness (S) or average taxonomic distinctness (AvTD) and explanatory variables based on linear regression using Bayesian Information Criterion (BIC) variable selection method. Models with delta <2 are shown. Separate analyses were done for all taxa of aquatic macrophytes, hydrophytes and helophytes. ^2: Quadratic term of explanatory variable. Abbreviations; Alkal: Alkalinity, Area: Lake surface area, Elev: Elevation, TempA: Average annual temperature, TP: total phosphorus, Depth: Maximum depth, Transects: The number of studied transects in a lake.

Table 5. Direction of relationships between species richness (S) or average taxonomic distinctness (AvTD) and explanatory variables in each region. The left side sign refers to S and the right side sign to AvTD (S/AvTD). Note that a predictor can have a linear or unimodal effect on macrophyte variables depending on individual models. L: linear term, Q: quadratic term, ns: variable not selected for a particular biodiversity index, na = parameter was not included among the explanatory variables due to multicollinearity. p values are not given, because they varied among the models.

Full text

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A comparative analysis of the species richness and taxonomic distinctness of lake1
macrophytes in four regions: similarities, differences and randomness along2
environmental gradients3
Janne Alahuhta
*1,2
, Maija Toivanen
1
, Jan Hjort
1
, Frauke Ecke
3,4
, Lucinda B. Johnson
5
, Laura Sass
6
,4
Jani Heino
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1 University of Oulu, Geography Research Unit, P.O. Box 3000, FI-90014 Oulu, Finland7
2 Finnish Environment Institute, Freshwater Centre, Monitoring and Assessment Unit, P.O. Box8
413, FI-90014 Oulu, Finland9
3 Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences10
(SLU), P.O. Box 7050, SE-750 07 Uppsala, Sweden11
4 Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural12
Sciences (SLU), SE-901 83 Umeå, Sweden13
5 University of Minnesota Duluth, Natural Resources Research Institute, 5013 Miller Trunk14
Highway, Duluth, MN 55811, USA15
6 Illinois Natural History Survey, Prairie Research Institute, University of Illinois, 1816 South Oak16
Street, Champaign, IL 61820, USA17
7 Finnish Environment Institute, Natural Environment Centre, Biodiversity, Paavo Havaksen Tie 3,18
FI-90570, Oulu, Finland19
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*Correspondence: Janne Alahuhta, University of Oulu, Geography Research Unit, P.O. Box 3000,21
FI-90014, University of Oulu, Finland.22
E-mail: janne.alahuhta@oulu.fi23
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SUMMARY41
1. There has recently been an intensive search for efficient biodiversity measures to quantify42
conservation value in freshwaters. However, increasing evidence suggests that the performance of43
different biodiversity measures depends on the studied ecosystem, organisms and geographical44
location.45
2. Our study goal was to compare patterns in species richness and average taxonomic distinctness46
(AvTD) of aquatic macrophytes along environmental gradients across four study regions (i.e.,47
Finland, Sweden, US state of Minnesota and US state of Wisconsin) situated on two continents. We48
separately studied all macrophyte species, hydrophytes and helophytes.49
3. We used aquatic macrophyte data along with relevant local (i.e., alkalinity, colour, elevation, lake50
area, maximum lake depth, total phosphorus and number of surveyed transects) and climate (i.e.,51
mean annual temperature) variables surveyed from 50 to 60 lakes using identical methods within52
each region. Based on linear regression models and Bayesian Information Criterion variable53
selection method, we correlated species richness and AvTD of lake macrophytes with local54
environmental and climate variables.55
4. Species richness and AvTD of aquatic macrophytes were mostly negatively but not significantly56
correlated in each region. Both biodiversity measures were correlated with environmental gradients57
to various degrees among the studied macrophyte groups and regions. Species richness was best58
explained by alkalinity and lake area in Finland, by elevation, annual mean temperature and total59
phosphorus in Minnesota, and by alkalinity in Wisconsin. Also, AvTD was best explained by60
alkalinity, annual mean temperature and total phosphorus in Finland and by alkalinity in Wisconsin.61
Very weak correlations were found between species richness or AvTD and environmental variables62
in Sweden.63

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5. Our study suggested that variation in different biodiversity indices along multiple environmental64
gradients can be considerable for the same biological group studied in different regions. This65
finding strongly suggests that a biodiversity measure indicating environmental conditions in one66
study region may not be applicable in another region, but complementary indices are needed to67
effectively indicate the impacts of anthropogenic pressures on freshwater biodiversity. Our results68
further suggested that species richness is a better measure than AvTD to account for conservation69
value in freshwaters. However, further research is required to evaluate the usefulness of AvTD to70
indicate conservation value (e.g., randomization tests), because alternative measures are clearly71
needed for those freshwater taxa lacking complete information on true phylogenetic diversity.72
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Keywords: Aquatic biodiversity, Aquatic plants, Freshwater biodiversity, Taxonomic diversity76
Running head: Biodiversity of lake macrophytes among regions77
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INTRODUCTION85
Freshwater ecosystems harbour much greater levels of biodiversity than terrestrial systems when86
compared by surface area (Dudgeon et al., 2006) and are the source of numerous ecosystem87
services vital to human existence (Millennium Ecosystem Assessment, 2005). These ecosystems are88
also among the most threatened, being exposed to various anthropogenic impacts. The increasing89
pressures from catchment land use, invasive species, pollution and loss of connectivity have90
resulted in rapidly declining biodiversity in lakes, rivers and springs (Dudgeon et al., 2006; Vilmi et91
al., 2017). Climate change will most likely accelerate this negative trend of biodiversity loss in92
freshwater ecosystems, especially in high-latitude regions (Heino, Virkkala & Toivonen, 2009;93
Woodward, Perkins & Brown, 2010). This calls for actions, approaches and measures to help94
conserve threatened freshwater biodiversity across regions (Vilmi et al., 2017). Although the95
general decline in freshwater biodiversity is well-documented in many studies (Dudgeon et al.,96
2006; Cardinale et al., 2012), different approaches to measure biodiversity may yield varying97
information about freshwater biodiversity patterns. Multiple biodiversity indices have been98
developed to quantify natural characteristics and anthropogenic pressures, but these measure aspects99
to various degrees (Warwick & Clarke, 1998; Gallardo et al., 2011). Thus, the use of a single index100
is not typically appropriate in most circumstances. This study provides a complementary approach101
to better understand patterns and document changes in freshwater biodiversity across different102
ecosystems and regions.103
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Species richness is a classical measure of biodiversity across ecosystems and regions (e.g., Gaston,105
2000). This index however has many well-known weaknesses related to, for example, sampling106
effort and habitat type (Warwick & Clarke, 1998; Gotelli & Colwell, 2001). Despite these107
deficiencies, species richness has proved to be a useful measure to indicate conservation values in108