Back

Quantifying the hydrological niche of swamp vegetation communities using indicator species

Deane, D. C.; Mason, T.; Krogh, M.; Cairns, J.; Keith, D.

2025-05-19 ecology
10.1101/2025.05.18.653618 bioRxiv
Show abstract

Indicator species are typically used to infer the presence of other biota or specific environmental conditions. Here we use indicator species to quantify the hydrological niche of their corresponding vegetation communities within Coastal Upland Swamps of the Sydney Basin Bioregion, Australia. Swamp vegetation organizes naturally into five recognised communities, thought to occupy distinct positions along a hydrological gradient. However, longwall mining reduces hydro-period, potentially impacting the observed vegetation. We modelled the hydrological niche for each community using the relative frequency of 20 vascular plant indicator species (four for each community) and time series soil moisture data from 11 unmined sites across four swamps. We then used this model to predict indicator species frequencies in 3 mine-impacted sites. Indicator species were modelled as a function of the average number of days-per-year that swamps remained saturated at the base of the root zone (30 cm below surface). Hydrological niches were well differentiated for four communities with the estimated optimal mean annual days-per-year saturated ranging from Restioid heath at 16 [<16, 29] (mean {+/-} [95% uncertainty]) to Ti-tree thicket at 352 [322, >353]. Banksia thicket 96 [65, 154] and Cyperoid heath 257 [204, 297] communities were intermediate. However, Sedgeland indicator species showed limited variation with changing saturation, and their hydrological niche remains unclear. The model under-predicted the frequency of Cyperoid heath and over-predicted Banksia thicket indicator species in mine-impacted sites, suggesting vegetation is not yet in equilibrium with hydrology. Results suggest indicator species can provide a reliable basis for determining the hydrological niche of wetland plant communities, which can in turn predict community-level impacts of hydrological change.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Science of The Total Environment
179 papers in training set
Top 0.6%
12.0%
2
Ecography
50 papers in training set
Top 0.1%
12.0%
3
PLOS ONE
4510 papers in training set
Top 21%
8.9%
4
Ecosphere
53 papers in training set
Top 0.1%
8.1%
5
Journal of Applied Ecology
35 papers in training set
Top 0.1%
4.7%
6
PLOS Computational Biology
1633 papers in training set
Top 7%
4.7%
50% of probability mass above
7
Global Change Biology
69 papers in training set
Top 0.5%
3.5%
8
Methods in Ecology and Evolution
160 papers in training set
Top 0.9%
3.5%
9
Scientific Reports
3102 papers in training set
Top 39%
3.5%
10
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 2%
3.0%
11
Journal of Ecology
47 papers in training set
Top 0.2%
2.0%
12
Journal of The Royal Society Interface
189 papers in training set
Top 2%
2.0%
13
Ecological Applications
28 papers in training set
Top 0.2%
2.0%
14
Ecology and Evolution
232 papers in training set
Top 3%
1.6%
15
Environmental Research Letters
15 papers in training set
Top 0.4%
1.4%
16
PeerJ
261 papers in training set
Top 10%
1.3%
17
Journal of Environmental Management
11 papers in training set
Top 0.6%
1.2%
18
Biological Conservation
43 papers in training set
Top 0.6%
1.2%
19
eLife
5422 papers in training set
Top 50%
1.2%
20
Agriculture, Ecosystems & Environment
15 papers in training set
Top 0.2%
0.9%
21
Landscape Ecology
12 papers in training set
Top 0.2%
0.9%
22
Frontiers in Ecology and Evolution
60 papers in training set
Top 3%
0.9%
23
Communications Earth & Environment
14 papers in training set
Top 0.8%
0.9%
24
Global Ecology and Biogeography
41 papers in training set
Top 0.6%
0.8%
25
Environment International
42 papers in training set
Top 1%
0.7%
26
Frontiers in Plant Science
240 papers in training set
Top 5%
0.7%
27
Oikos
74 papers in training set
Top 0.8%
0.7%
28
Ecological Modelling
24 papers in training set
Top 0.6%
0.7%
29
Philosophical Transactions of the Royal Society B: Biological Sciences
53 papers in training set
Top 1%
0.7%
30
Forest Ecology and Management
25 papers in training set
Top 0.4%
0.7%