Paper · 2020 · Journal of Vegetation Science

Environmental variables driving species composition in subarctic springs in the face of climate change

Tara K. Miller; Einar Heegaard; Kristian Hassel; et al.

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Open access · other-oa

Abstract

Abstract Questions Which environmental variables are most important in determining plant species composition in subarctic springs? Do observed patterns differ between typical wetland and general matrix‐derived species? Location Helocrenic (seepage) springs, Northern Norway. Methods We sampled 49 helocrenic spring sites, measuring environmental variables (water temperature, water pH, electrical conductivity, discharge volume, geographic position) and recording all species present. We performed a partial canonical correspondence analysis (pCCA) to determine the relative importance of water quality, spatial, and climatic variables for patterns in species composition and to compare the differences in these patterns between wetland and matrix‐derived species. Results We found that climatic and water quality variables were almost equally important in determining species composition in subarctic springs, with climatic variables explaining 26.62% of variation in species composition and water quality variables explaining 26.14%. Spatial variables explained the least variation (21.53%). When looking at the variables individually, altitude (10.93%) and mean summer temperature (9.25%) explained the most variation. The trend was the same for matrix‐derived species and wetland species, with climatic variables explaining the most variation (matrix‐derived: 27.26%; wetland: 24.42%), followed by water quality (matrix‐derived: 26.40%; wetland: 24.13%) and spatial variables (matrix‐derived: 24.87%; wetland: 16.27%). The main difference between matrix‐derived species and typical wetland species was that the spatial variables explained less variation for wetland species. Conclusions The close relationship of species composition (total vegetation as well as separated into wetland and matrix‐derived species) with climatic and water quality conditions indicates a sensitivity of subarctic springs to future climate change. In combination with altitude, which was found to be the most important individual variable, it is likely that the future distribution of spring species tracking climate change will be limited by the occurrence of suitable spring habitats, especially at high altitudes.

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Claims 13

Associationobservedoriginal resultmeasured

Claim · model-written summary

Climate explained 26.62% of variation in spring species composition.

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variation in species compositione0
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“climatic variables explaining 26.62% of variation in species composition”

✓ located verbatim in the source · abstract, characters 916–988 · show in text ↑
Associationobservedoriginal resultmeasured

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Water quality explained 26.14% of variation in spring species composition.

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water quality variablese0
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“water quality variables explaining 26.14%”

✓ located verbatim in the source · abstract, characters 993–1034 · show in text ↑
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Spatial variables explained 21.53% of composition variation.

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“Spatial variables explained the least variation (21.53%)”

✓ located verbatim in the source · abstract, characters 1036–1092 · show in text ↑
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Altitude explained 10.93% of composition variation.

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“altitude (10.93%) and mean summer temperature (9.25%) explained the most variation”

✓ located verbatim in the source · abstract, characters 1138–1220 · show in text ↑
Associationobservedoriginal resultmeasured

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Mean summer temperature explained 9.25% of composition variation.

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“mean summer temperature (9.25%) explained the most variation”

✓ located verbatim in the source · abstract, characters 1160–1220 · show in text ↑
Associationobservedoriginal resultmeasured

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Climate explained 27.26% of composition variation among matrix-derived species.

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“climatic variables explaining the most variation (matrix‐derived: 27.26%; wetland: 24.42%)”

✓ located verbatim in the source · abstract, characters 1298–1388 · show in text ↑
Associationobservedoriginal resultmeasured

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Climate explained 24.42% of composition variation among wetland species.

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“climatic variables explaining the most variation (matrix‐derived: 27.26%; wetland: 24.42%)”

✓ located verbatim in the source · abstract, characters 1298–1388 · show in text ↑
Associationobservedoriginal resultmeasured

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Water quality explained 26.40% for matrix-derived species.

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“water quality (matrix‐derived: 26.40%; wetland: 24.13%)”

✓ located verbatim in the source · abstract, characters 1402–1457 · show in text ↑
Associationobservedoriginal resultmeasured

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Water quality explained 24.13% for wetland species.

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“water quality (matrix‐derived: 26.40%; wetland: 24.13%)”

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Associationobservedoriginal resultmeasured

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Spatial variables explained 24.87% for matrix-derived species.

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“spatial variables (matrix‐derived: 24.87%; wetland: 16.27%)”

✓ located verbatim in the source · abstract, characters 1462–1521 · show in text ↑
Associationobservedoriginal resultmeasured

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Spatial variables explained 16.27% for wetland species.

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“spatial variables (matrix‐derived: 24.87%; wetland: 16.27%)”

✓ located verbatim in the source · abstract, characters 1462–1521 · show in text ↑
Associationobservedoriginal resultmeasured

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Wetland species showed less variation explained by spatial variables than matrix-derived species.

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“the spatial variables explained less variation for wetland species”

✓ located verbatim in the source · abstract, characters 1611–1677 · show in text ↑
Associationauthor interpretationoriginal resultprojected

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The authors infer spring species distribution tracking climate change may be limited by suitable high-altitude habitat.

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suitable spring habitatse0

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“future distribution of spring species tracking climate change will be limited by the occurrence of suitable spring habitats, especially at high altitudes”

✓ located verbatim in the source · abstract, characters 2045–2198 · show in text ↑