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\begin{document}

\title{Disrupted connectivity in biotic and geomorphic patterns in stream-lake
systems}



\author[1]{Lina Polvi}%
\author[2]{Lovisa Lind}%
\affil[1]{Umeå Universitet Teknisk-Naturvetenskaplig Fakultet}%
\affil[2]{Karlstad University}%


\vspace{-1em}



  
  \date{June 10, 2024}


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\selectlanguage{english}
\begin{abstract}
Ecological and geomorphic theory assume longitudinal connectivity; we
test whether these concepts apply in a naturally disconnected stream
network with mainstem lakes and coarse glacial legacy sediment. We
determined downstream hydraulic geometry relationships for channel width
and inventoried riparian vegetation in each new process-domain (rapids,
slow-flowing, lakes) along a continuous \textasciitilde{}10 km segment
in two catchments in northern Sweden. Hydraulic geometry relationships
for width were very weak, indicating that although channel width does
increase in the downstream direction, there is very large local
variation in width, within and among process domains. Riparian
vegetation richness did not increase markedly downstream as expected in
a connected stream network, and there are very weak relationships
between riparian vegetation composition similarity among reaches and
distance between reaches, indicating that hydrochory plays a minor role
plays in metacommunity organization. Formerly continentally-glaciated
catchments are thus highly fragmented and local factors steer geomorphic
form and biotic organization.%
\end{abstract}%



\sloppy


\textbf{Title Page}

\textbf{Title:} Disrupted connectivity in biotic and geomorphic patterns
in stream-lake systems

\textbf{Authors:} Lina E. Polvi\textsuperscript{1} \& Lovisa
Lind\textsuperscript{1,2}

\textsuperscript{1}Department of Ecology and Environmental Science, Ume\selectlanguage{ngerman}å
University, Umeå, Sweden, lina.polvi@umu.se

\textsuperscript{2}Department of Environmental and Life Sciences,
Karlstad University, Karlstad, Sweden, lovalind@gmail.com

\textbf{Running title:} Lakes disrupt connectivity of streams

\textbf{Keywords:} downstream hydraulic geometry; river continuum
concept; lakes; Sweden; riparian vegetation; channel width; biodiversity

Tel: +46 90 786 6190

Mobile: +46 70~256 3446

E-mail: lina.polvi@umu.se

\textbf{Type of Article:} Letter

\textbf{Word count:} Abstract: 150, Main text: 4555

\textbf{Number of references:} 51

\textbf{Number of figures, tables \& text boxes:} 4 figures \& 2 tables

\textbf{Corresponding author:} Lina Polvi, Umeå University, Department
of Ecology \& Environmental Science, Linnaeus väg 6, 907 36 Umeå, Sweden

\textbf{Statement of authorship:} LEP designed the study and oversaw
collection of data. LEP analyzed geomorphic data and LL analyzed
vegetation data. LEP and LL wrote and revised the manuscript.

\textbf{Data accessibility statement:} ~We will make data available in a
public repository (Swedish National Data Service) after provisional
acceptance of the manuscript and the data DOI will be included at the
end of the article.

\textbf{Abstract Page}

Ecological and geomorphic theory assume longitudinal connectivity; we
test whether these concepts apply in a naturally disconnected stream
network with mainstem lakes and coarse glacial legacy sediment. We
determined downstream hydraulic geometry relationships for channel width
and inventoried riparian vegetation in each new process-domain (rapids,
slow-flowing, lakes) along a continuous \textasciitilde{}10 km segment
in two catchments in northern Sweden. Hydraulic geometry relationships
for width were very weak, indicating that although channel width does
increase in the downstream direction, there is very large local
variation in width, within and among process domains. Riparian
vegetation richness did not increase markedly downstream as expected in
a connected stream network, and there are very weak relationships
between riparian vegetation composition similarity among reaches and
distance between reaches, indicating that hydrochory plays a minor role
plays in metacommunity organization. Formerly continentally-glaciated
catchments are thus highly fragmented and local factors steer geomorphic
form and biotic organization.

\textbf{Main text}

\textbf{INTRODUCTION}

At large spatial scales, a stream's geomorphic and ecological form and
behavior can be predicted based on longitudinal trends (e.g., Downing et
al., 2012). From a geomorphic perspective, at the catchment scale, the
concept of downstream hydraulic geometry (DHG) shows that several
channel form parameters, including width and depth, increase as a power
function of bankfull discharge (Leopold \& Maddock, 1953), which in turn
increases with drainage area. Due to predicted decreases in slope and
thus shear stress, bed material grain size should also decrease
(Gasparini et al., 1999). Within stream ecology, Vannote et al., 1980
built on the idea of downstream hydraulic geometry by extending the idea
of longitudinal patterns or adjustments from the ``physical system of
geomorphologists into a biological analog''(Vannote et al., 1980),
developing the river continuum concept (RCC). The RCC predicts
longitudinal patterns in multiple stream ecosystem factors, including
the type of macroinvertebrates present, the ratio of photosynthesis to
respiration and the relative amount of coarse and fine particulate
organic matter, all of which are strongly coupled to the predicted
increase in channel width. Furthermore, biodiversity (species richness)
often shows a predictable downstream increasing trend towards the middle
of the catchment due to dispersal effects and more favorable growing
conditions (e.g., Nilsson et al., 1989, Dunn et al., 2011, Kuglerová et
al., 2015).

Since the establishment of the DHG and RCC concepts, exceptions to
unidirectional

downstream trends have been described, including the geomorphic process
domain concept (Montgomery, 1999), the serial discontinuity concept
(Ward \& Stanford, 1995), patch dynamics (Townsend, 1989; Poole, 2002),
the river wave concept (Humphries et al., 2014), and the mighty
headwater hypothesis (Finn et al., 2011). However, these concepts of
downstream trends, implying longitudinal connectivity, still form the
basis for multiple assumptions and concepts within river science (e.g.,
Surian, 2002; Frings, 2008; Dunne \& Jerolmack, 2020). For example, the
amount of allochthonous material input into a stream tends to decrease
with increased channel width due to the greater percentage of the
channel covered by canopy compared to larger channels (Vannote et al.,
1980, Doi, 2009). To study these changes, rather than measuring channel
width and canopy cover, studies commonly rely on drainage area as a
proxy (e.g., Jonsson et al., 2018). If these basic longitudinal
gradients do not exist in a certain catchment, then we must re-examine
which geomorphic and ecological processes drive longitudinal stream
patterns. The serial discontinuity concept, predicts local diversity to
increase with increasing distance to dams (Ward \& Stanford, 1995), and
Green et al. (n.d.) found the same pattern for invertebrates but along a
lake-stream system with lakes disrupting the continuity. However,
geomorphic and ecological trends are often not examined simultaneously
to explain organization of a stream network, even though they are
intertwined with each other. Hence, the objective of this study was to
examine whether geomorphic and ecological longitudinal trends, as
defined by channel width and riparian vegetation richness and community
composition, exist in a naturally disconnected catchment consisting of
lakes and streams. By understanding the geomorphic and biotic
longitudinal organization of a stream network, we can set expectations
for recovery after stream restoration.

\textbf{Background}

Downstream hydraulic geometry can predict several aspects of stream
properties including mean velocity and depth (Leopold \& Maddock, 1953;
Lee \& Julien, 2006), however, channel width is most widely studied due
to the ease of making remote or simple field measurements (e.g., Fisher
et al., 2013; Dunne \& Jerolmack, 2020). Longitudinal increases in
channel width show a consistent scaling relationship with bankfull
discharge, in that the exponent (b) commonly approximates 0.5 (Equation
(1)); whereas, the coefficient (a) reflects local variations in
streambank erosivity, controlled by sediment texture, vegetation type,
flow regime, etc. (Anderson et al., 2004). Although downstream hydraulic
geometry relationships are commonly well-developed in alluvial channels,
strong downstream hydraulic geometry relationships are evident even in
regions with external non-alluvial controls, such as in bedrock channels
with local variations due to variations in bedrock erosivity (Montgomery
\& Gran, 2001), and in those with discontinuous colluvial input (Wohl \&
Wilcox, 2005). However, in cases where the substrate resisting forces
exceed hydraulic driving forces, downstream hydraulic geometry
relationships are not as well developed, such as in mountain streams
with very coarse sediment relative to hydraulic forces (where the stream
power to sediment size ratio (\selectlanguage{english}/D\textsubscript{84}) \textless{} 10,000
kg/s\textsuperscript{3}) (Wohl, 2004). Lakes can also contribute to
overall poor DHG relationships, with higher width to depth ratios
directly downstream of lakes, as a result of lakes trapping sediment
(Arp et al., 2007). In cases where bankfull discharge data are
unavailable, drainage area can be used a proxy for bankfull discharge
(Equation (2) \& (3)) (Soar \& Thorne, 2001; Faustini et al., 2009).
Because there may be additional factors to drainage area controlling
bankfull discharge, DHG relationships using drainage area tend to show
significantly more scatter, yet is still a powerful tool since only a
digital elevation model is required as input data (Faustini et al.,
2009). However, although drainage area-based DHG relationships are poor
in some regions, in a review of regression coefficients for width vs.
drainage area relationships (Eq. 3), all R\textsuperscript{2} values
exceed 0.24 and most \textgreater{}0.6; exponent-values (beta), which
should be less than b (commonly \textasciitilde{}0.5) since the
relationship between drainage area and discharge (Eq. 2) where the
exponent-value (y) is commonly slightly less than 1 (Faustini et al.,
2009), mostly ranged from 0.3-0.45.

\(w=aQ^{b}\),~ (1)

where w is bankfull width, a is a regional coefficient, Q is bankfull
discharge, and b is a regional exponent (commonly \textasciitilde{}0.5).

\(Q=xA^{y}\), (2)

where A is drainage area, and x and y are regional coefficients and
exponents, and y is commonly slightly \textless{} 1.

\(w=\alpha A^{\beta}\), (3)

where \selectlanguage{greek}α \selectlanguage{english}and \selectlanguage{greek}β \selectlanguage{english}are empirical parameters and \selectlanguage{greek}β \selectlanguage{english}is commonly \textless{}0.5.

Moreover, adjustment of geomorphic parameters assume an alluvial channel
where self-adjustment of channel form based on the current flow regime
is possible (Leopold \& Maddock, 1953, Phillips \& Jerolmack, 2016).
Therefore, semi-alluvial channels, which contain cohesive or coarse
sediment deposited by non-fluvial geomorphic processes (Polvi et al.,
2014; Pike et al., 2018; Polvi, 2021) could also contribute to
poor-fitting relationships between geomorphic and ecological
longitudinal patterns rather than fitting the established patterns from
highly connected stream networks with alluvial channels.

Geomorphic and ecological longitudinal trends are intertwined with one
another, depending on connectivity of flows and sediment in addition to
ecological meta-communities, through migration of organisms and
dispersal of seeds and propagules. Because hydrochory is dependent on
longitudinal connectivity for dispersion, the organization of passively
dispersing organisms (e.g., riparian vegetation), provides a natural
test of functional connectivity. Through~hydrochory, species accumulate
downstream, which leads to higher species richness or densities
downstream (e.g., Nilsson et al., 1989, Dunn et al., 2011, Kuglerov\selectlanguage{ngerman}á et
al., 2015). In anthropogenically-fragmented catchments (e.g., due to
dams), hydrochoric seed dispersal is interrupted, thus altering the
biotic communities, causing proximal reaches on either side of a dam to
form dissimilar riparian vegetation species compositions (Jansson et
al., 2005). ~Although anthropogenic factors can create barriers in
connectivity (e.g. dams) (Nilsson, 2005; Nilsson et al., 2010) and
stream restoration has focused on increasing connectivity, many
geomorphic and ecological engineering processes serve to create natural
forms of longitudinal disconnectivity. These spatially and sometimes
temporally intermittent barriers or buffers to flow, sediment and
propagule fluxes, have received much less attention in the hydrochory
literature and how they influence metacommunity organization. Once
prevalent beaver dams and log jams cause widespread `leaky' barriers
(Wohl \& Beckman, 2014), serving to trap sediment, carbon, and attenuate
flows. Similarly lakes, which are widespread in northern latitudes
(Messager et al., 2016), particularly where Pleistocene glaciation has
eroded bedrock and deposited moraine dams, can have substantial effects
on stream topology and form and function of rivers where they are
connected to stream networks (Gardner et al., 2019), such as the
connectivity of sediment (Arp et al., 2007), seed dispersal (Su et al.,
2019a, b), and diversity of invertebrates (Green et al., n.d.) .

We focused our study on two catchments in boreal northern Sweden that
are heavily influenced by past continental glaciation, creating a stream
network with multiple instream lakes and coarse till deposits (Nilsson
et al., 2002; Polvi et al., 2014; Su et al., 2019a, b). The stream
networks can be divided into three process domains, defined by
Montgomery (1999) as zones with distinct geomorphic processes that
structure ecological disturbances and thus organize biotic communities:
rapids, slow-flowing reaches, and lakes (Nilsson et al., 2002; Su et
al., 2019a, b) (Figure 1a). Rapids are steep (S\textsubscript{0}:
0.1-5\%) gravel- to boulder-bed channels with coarse glacial legacy
sediment (cobbles and boulders) and bedforms that do not conform to
alluvial bedform-channel slope relationships, \emph{sensu} Montgomery \&
Buffington (1997); slow-flowing reaches (S\textsubscript{0} \textless{}
0.1\%) are straight or meandering channels flowing through peat or fine
sediment with wetland vegetation riparian zones; lakes have inlets and
outlets and are lined with either fine sediment or coarse till. Within
our study catchments, we examined the longitudinal distribution of
process domains along nearly the entire mainstem channel, evaluated how
channel width changes downstream and examined how riparian vegetation
communities change along the channel in each new process domain. Our aim
was to determine whether these glaciated, boreal stream networks fit
established patterns of geomorphic and ecological longitudinal changes.
We test the functional geomorphic and ecological connectivity of these
catchments with high-resolution spatial data of riparian vegetation
communities and channel width.

\textbf{MATERIALS AND METHODS}

\textbf{Study location and study setup}

Our study was located in the boreal region of northern Sweden in two
catchments of similar size (\textasciitilde{}350 km\textsuperscript{2}):
Hjuksån and Bjurbäcken (\emph{ån} and \emph{bäcken} both mean `stream'/
`creek'), both of which are tributaries of the free-flowing Vindel River
that in turn flows into the Ume River \textasciitilde{}30 km upstream of
its outlet in the Baltic Sea (Figure 2). In addition to glaciation
shaping the catchment through numerous mainstem lakes and large amounts
of coarse glacial sediment, the landscape is divided into two
regions---above and below the former highest coast-line (FHC). The FHC
divides areas that have been only affected by glaciation and contains
undisturbed glacial sediment from areas that have been under sea level
after glaciation and affected by deltaic processes and subsequently
uplifted by post-glacial isostatic rebound (Fredén, 1994). Hjuksån
catchment (64° 25'N, 19° 45'E, alt. 245 m) is located nearly entirely
below the FHC, whereas Bjurbäcken (65° 6'N, 18° 4'E, alt. 320 m) is
completely above the FHC. The upland vegetation in the study area is
dominated by boreal forest with Scots pine (\emph{Pinus sylvestris} )
and Norway spruce (\emph{Picea abies} ) and the riparian vegetation is
dominated by deciduous trees, tall herb, and graminoid communities.

We started collecting geomorphic and ecological data directly downstream
of the furthest upstream lake, encompassing 18 process domain reaches in
Bjurbäcken and 20 process domain reaches in Hjuksån catchment.
Geomorphic data were collected along the entire mainstem channel of
Bjurbäcken and Hjuksån, starting below the upstream lake, to the
tributary junction with the Vindel River. Riparian vegetation data were
collected starting at the same point and \textasciitilde{}18 km
downstream in Bjurbäcken and \textasciitilde{}9 km downstream in
Hjuksån.

\textbf{Geomorphic study}

In order to obtain a large set of data points, active channel width was
measured using current orthophotos with GIS software (ArcMap 10.5,
2017). Active channel width was measured between the channel banks,
perpendicular to the downstream direction, every 50 m. Several other
geomorphic factors were also recorded, including the process domain as
identified from the orthophoto, the surficial geology, and proximity to
glacial features (e.g., eskers, moraines). Surficial geological deposits
were recorded in four different categories (bedrock, peat, subglacial
and deltaic fine sediment (including postglacial clay, silt and sand and
subglacial sands), coarse till). Using a 2-m digital elevation model, we
determined the channel slope and the drainage area at each measured
transect, the latter of which was used as a proxy for bankfull
discharge. We then plotted the power relationships between drainage area
and channel width for all transects and each process domain separately
to determine whether the stream networks conform to expected downstream
hydraulic geometry relationships.

To predict channel width we used multiple regression models, based on
drainage area distance downstream from lake, channel slope, proximity to
glacial feature, and type of surficial geology deposits (categorical).
Selection was based on lowest AIC with backward-step selection. The
relationship between channel width and drainage area were analysed using
power regressions. Multiple linear regressions were used to determine
logged values of power regression. All statistical analyses were
performed in R studio version 3.6.0 (R Core Team, 2021).

\textbf{Ecological study}

For each new process domain reach, we identified all vascular plants in
the riparian zone between the summer low water mark and the edge of the
riparian zone (as defined by the dominance of \emph{Vaccinium
myrtillus}(bilberries)). The identification of plant species followed
the taxonomy in Krok and Almquist (2013). In the following cases, two or
more species were treated as one taxon: \emph{Carex juncella} +
\emph{Carex nigra} ,\emph{Callitriche} spp. (difficult to identify in
the absence of floral characters), \emph{Hieracium} spp.,
\emph{Taraxacum} spp. (apomictic),\emph{Sparganium} spp. (common with
hybrids). All vegetation inventories took place in June-August 2016. For
large lakes, we only inventoried riparian plants found in the first and
last 300 m along the shoreline. We calculated richness (number of
species) and species density for each reach/lake and determined
community composition. We used regression analyses to study the
relationship between changes in species density and richness with
geographical distance downstream. We also examined whether there were
relationships between community similarity, using Jaccard's index, and
distance between reaches to determine whether hydrochoric dispersal is a
potential control on riparian metacommunity organization. All
statistical analyses were performed in R studio version 3.6.0 (R Core
Team, 2021).

\textbf{RESULTS}

\textbf{Weak downstream hydraulic geometry relationships}

Along the mainstem of Bjurbäcken, over 1300 measurements of channel
width and drainage area were made with drainage areas ranging from
\textasciitilde{}50- 360 km\textsuperscript{2}, and along the mainstem
of Hjuksån, \textasciitilde{}900 measurements were made with drainage
areas ranging from \textasciitilde{}8 to 360 km\textsuperscript{2}. As
expected, when lake widths are included, downstream hydraulic geometry
relationships between drainage area and channel width, as defined by a
power relationship, are extremely poor, with one catchment even showing
an overall decrease in channel width. When lakes are excluded, the
relationships remain poor but weakly positive. When lakes are excluded
in Bjurbäcken, located above the FHC with coarser glacial sediment,
there is still a very weak relationship with an R\textsuperscript{2} of
0.08 with an exponent (\selectlanguage{greek}β-\selectlanguage{english}value) of 0.34 (Figure 3). When only focusing
on rapids, the R\textsuperscript{2} value increases to 0.30, and the
\selectlanguage{greek}β-\selectlanguage{english}value is 0.56. In Hjuks\selectlanguage{ngerman}ån, located below the FHC, the power
relationship excluding lakes is stronger than in Bjurbäcken with an
R\textsuperscript{2} value of 0.43 and a \selectlanguage{greek}β-\selectlanguage{english}value of 0.68, and the
relationship with only rapids even decreases in explanatory power to an
R\textsuperscript{2} of 0.42 and a \selectlanguage{greek}β-\selectlanguage{english}value of 0.39 (Figure 3). The two
catchments show opposing directions of explanatory power for the two
reach types: Hjuks\selectlanguage{ngerman}ån has stronger explanatory power for slow-flowing
reaches (R\textsuperscript{2} = 0.57), whereas Bjurbäcken has very low
explanatory power for slow-flowing reaches (R\textsuperscript{2} =
0.04).

Significant multiple linear regression models including combinations of
factors of downstream distance from a lake and categorical variables of
surficial geology types were found for both catchments, increasing
explanatory power of width predictions, in particular in the Hjuksån
catchment. Downstream distance from a lake was only a significant factor
in Hjuksån (below the FHC), where increased distance downstream from a
lake decreases predicted channel width. Furthermore in the Hjuksån
catchment, for both rapids and slow-flowing reaches combined, the
surficial geology types of coarse glacial till and bedrock lowered
channel width, whereas deltaic and fine subglacial sediment increased
channel width. The relationship for only rapids contained peat as the
only significant surficial geology type, which increases channel width.
Exponent (\selectlanguage{greek}β-\selectlanguage{english}) values ranged from 0.51-0.65, and
R\textsuperscript{2}-values ranged from 0.47-0.69, where the
relationship for only slow-flowing reaches was the strongest. In the
Bjurb\selectlanguage{ngerman}äcken catchment, the downstream distance from a lake was not a
significant factor, but various combinations of surficial geology types
were significant factors. The presence of peat or coarse till decreased
the predicted width, while the presence of bedrock had opposite effects
for relationships of only rapids (decreasing channel width) compared to
slow-flowing reaches (increasing channel width). Even with the
additional explanatory parameters, the drainage area-width relationships
for Bjurbäcken were very poor with very flow
R\textsuperscript{2}-values, ranging from 0.10 to 0.33, where the
relationship for rapids had the highest explanatory power. Exponent (\selectlanguage{greek}β\selectlanguage{english})
values were much lower in Bjurb\selectlanguage{ngerman}äcken, than for Hjuksån, at 0.18 to 0.26,
indicating a more gradual increase in channel width with increasing
drainage area.

\textbf{Low connectivity of riparian vegetation communities}

There are no statistically significant trends in richness of vascular
riparian plants with downstream distance in Hjuksån with all the reaches
combined or for each process domain separately. In Bjurbäcken, there was
a significant relationship between richness and distance downstream for
all reaches combined (p= 0.003, R\textsuperscript{2}= 0.43) with a slope
indicating two new species per kilometer; however, there are no
significant relationships for each process domain, separately. However,
to control for the large difference in area between the different
reaches we focus our results on species density. We found an increase in
cumulative species richness (Figure 4) but a negative relationship
between species density of vascular riparian plants with downstream
distance in Hjuksån with all the reaches combined (R\textsuperscript{2}=
0.21, p = 0.0471, mean = 0.05) (Figure 4a-b); however, there are no
significant relationships in Bjurbäcken or for each process domain
separately in Hjuksån (Bjurbäcken: R\textsuperscript{2}= 0.009, p =
0.694, mean = 0.06). In examining relationships of reach similarity (in
terms of riparian vegetation species composition) by distance between
reaches, a few relationships can be found. There are significant
relationships when all process domains are combined for both Hjuksån (p
= 0.003 R\textsuperscript{2} = 0.05) and Bjurbäcken (p \textgreater{}
0.001, R\textsuperscript{2} = 0.09) (Figure 4 c-d). There is also a
significant relationship between riparian vegetation similarity and
distance between reaches for lakes in Hjuksån (p = 0.002,
R\textsuperscript{2} = 0.176) and for rapids in Bjurbäcken (p
\textless{}0.001, R\textsuperscript{2} = 0.226) (Table 2).

\textbf{DISCUSSION}

We found longitudinal trends in geomorphic and ecological parameters to
be very weak in these naturally disconnected study catchments, which
contains disparate channel types that segment the stream. Our study also
finds the geomorphic difference between the catchments to be visible in
the riparian vegetation along the different catchments.

Downstream hydraulic geometry relationships of width- drainage area
power functions explain at most 57\% of variability in width for
slow-flowing reaches in Hjuksån, and a minimum of only 4\% of
variability in width for slow-flowing reaches in Bjurbäcken. Combining
all reach types, only 8\% of variability in width is explained in
Bjurbäcken and 43\% of variability is explained in Hjuksån. According to
Faustini et al. (2009), all of these regressions classify as `poor'
fits, except for slow-flowing reaches in Hjuksån; and the power
relationships in Bjurbäcken have poorer fits than for any region in the
conterminous United States (Faustini et al., 2009). In the Hjuksån
catchment, located below the FHC, which contains more fine deltaic
sediment in addition to coarse glacial sediment, there are slightly
stronger downstream hydraulic geometry relationships for all reach
types, indicating potential for self-adjustment in response to the
current flow regime as seen in alluvial channels (Singh et al., 2003;
Wohl, 2004). The fact that rapids and the catchment above the FHC show
poorer DHG relationships, fits with Wohl's (2004) observations from
coarse mountain streams, where low ratios of the stream power to
D\textsubscript{84} lead to poor DHG fits. Exponent (\selectlanguage{greek}β-\selectlanguage{english}) values, which
describes the spatial rate at which width increases with increased
drainage area, typically range 0.2-0.4 (Faustini et al., 2009). Combined
reaches and slow-flowing reaches in Bjurb\selectlanguage{ngerman}äcken fall within that range
(0.34 and 0.26, respectively) in addition to rapids in Hjuksån (0.39);
however, the remaining reach types have fairly large \selectlanguage{greek}β-\selectlanguage{english}values (ranging
0.56- 0.75) (Figure 3), indicating a fairly rapid downstream increase in
channel width, potentially caused by a y-value \textgreater{}1 (Equation
(2)), due to the more dendritic drainage basin in Hjuks\selectlanguage{ngerman}ån compared to a
more linear drainage basin in Bjurbäcken (Figure 2) and greater
connections to groundwater (Burgers et al., 2014).

The presence of lakes in the Hjuksån catchment, containing finer
sediment and thus having more alluvial characteristics, create wider
channels directly downstream of the lake than if the reach was further
downstream of a lake (Table 1). Lakes are serving to reset the
longitudinal sediment conveyor belt by trapping fine sediment,
increasing width: depth ratios directly downstream of lakes (Arp et al.,
2007). In the Sawtooth Mountains region of Idaho, US, channel shape
recovered by 50\% within 1.0-1.8 km downstream of lakes and required up
to 10-20 km to recover by 90\%. Given the high spatial density of lakes
in catchments in northern Sweden, channels may never recover and thus
never reach a non-lake influenced equilibrium form. In addition to the
significant effect of lakes, several surficial geology types, reflecting
erosivity of streambanks affect the drainage area- channel width
relationship, where the coarse till has a narrowing effect and fine
deltaic, and subglacial sediment has a widening effect (Table 1). Peat
has a widening effect on rapids but a narrowing effect on slow-flowing
reaches, likely because the intrinsic cohesivity of clay in peat will
decrease lateral erosion but compared to coarse till found in rapids the
presence of peat will allow greater erosion. Likewise, bedrock has a
narrowing effect in rapids and the slow-flowing reaches in Hjuksån but a
widening effect in slow-flowing reaches in Bjurbäcken; bedrock outcrops
found in slow-flowing reaches are smoothly rounded features composing
the bed or small parts of the banks, whereas bedrock in rapids will lead
to high slopes that naturally form narrower channels or make up
streambanks that will hinder any lateral erosion. In general, the low
R\textsuperscript{2} values and generally low \selectlanguage{greek}β-\selectlanguage{english}values reflect the low
ability for semi-alluvial channels to adjust their channels to the
contemporary flow regime (Polvi, 2021).

The positive relationships between increased distance between reaches
and reach similarity indicates low connectivity between reaches in terms
of hydrochoric seed or propagule dispersal. However, models like linear
regressions are sensitive to outliers and therefore these models are
significant but with a very weak R\textsuperscript{2}. We therefore
interpret these results a lack of connectivity since reaches closer to
each other are less similar than reaches that are further apart. The
geomorphic trend of weak longitudinal relationships with lakes is also
mirrored in the ecological data by a slight trend in decrease in
longitudinal species density of riparian vegetation in Hjuks\selectlanguage{ngerman}ån, and no
significant relationships in Bjurbäcken.

Poorly developed downstream hydraulic geometry relationships with
regards to channel width, combined with low support for connectivity
between riparian vegetation communities in semi-alluvial stream-lake
systems, indicate that these are highly fragmented catchments where
local factors steer geomorphic form and biotic communities. All rivers
are part of a landscape context with varying degrees of connectivity
between segments and reaches. Previous work has shown that dispersal is
strong in well-connected areas compared to isolated headwaters, and
patterns of connectivity among sites in a network can affect population
dynamics (Swan \& Brown, 2017). Hence, biodiversity has often been shown
to increase towards the middle of the catchment (Nilsson et al., 1989;
Kuglerová et al., 2015). However, stream networks in northern
Fennoscandia are commonly naturally fragmented and consist of three
types of process domains (rapids, slow-flowing reaches and lakes), which
all differ in morphology and hydraulics that influence their capacity to
facilitate the plant dispersal (Su et al., 2019a, b). In a connected
stream network, one would expect a downstream increase in species
richness density (Andersson et al., 2000; Kuglerová et al., 2015).
However, in our naturally fragmented river system we found the opposite
pattern, with a reduction in species density with increasing distance
downstream. These differences in patterns can partly be explained by the
high spatial resolution and that our study was conducted continuously
along two streams, in comparison to previous studies with lower spatial
resolution and discontinuity in sampling (e.g. Nilsson et al., 1994;
Andersson et al., 2000; Kuglerová et al., 2015). The increased spatial
resolution and sampling continuity allowed us to find an overall
reduction in species density, as a function of the lack of hydrochory
due to the presence of numerous lakes (Su et al., 2019a, b). Lakes trap
\textasciitilde{}80\% of seeds during the spring flood and only allow
downstream transport if the lake outlet is aligned with the wind
direction (Sarneel et al., 2014; Su et al., 2019a). In a connected
stream network, we would also predict higher similarity between reaches
close to each other; however, in our disconnected systems we did not
find such a relationship. Su et al. (2019b) showed that these three
process domains have differing plant species communities, and thus seed
banks may therefore provide a local source for metacommunity control, or
perhaps diversity depends mostly on local site conditions (Green et al.,
n.d.), and not connectivity.

Rather than longitudinal controls of increasing discharge (as a function
of drainage area) and inter-reach connectivity on channel width and
riparian vegetation communities, our results indicate that our study
catchments are driven by local-scale geomorphic and ecological controls.
These local-scale controls, such as surficial geology (presence of
coarse glacial sediment) and local seed banks and source populations,
are therefore more important in recovery of stream processes and
communities than connectivity of flows, sediment, and propagules between
reaches in responding to disturbances, which include habitat
restoration. Therefore, passive ecological recovery, with recolonization
by hydrochory, is not as likely in disconnected stream networks, and
thus manual planting of riparian vegetation may be necessary. Similarly,
geomorphic recovery through channel adjustment based on the current flow
regime is unlikely in disconnected networks with semi-alluvial process
domain segments; thus, physical channel manipulation should play a
larger role in stream restoration. In addition, interactions between
channel width and riparian vegetation communities throughout the
catchment may serve to further shape reach morphology and riparian zones
(Anderson et al., 2004).

With weak downstream hydraulic geometry relationships, traditional
stream ecology concepts, which assume increasing width as drainage area
increases, may not apply. Geomorphic relationships with channel size
have also been used to model nutrient uptake in river networks (Ensign
\& Doyle, 2006). Thus, given the abundance of lakes in northern
latitudes (Messager et al., 2016), this study can have widespread
implications on the understanding of fluvial processes and stream
ecosystems in boreal, and (sub)arctic regions. For example, we may not
be able to rely on past cornerstones of river science, such as
downstream hydraulic geometry and the river continuum concept, in
certain catchments in understanding river dynamics, designing stream
restoration projects, and predicting responses of communities after
restoration or other natural disturbances. Furthermore, disconnected
fluvial systems with abundant lakes may also be analogous to
pre-anthropogenic stream networks that contained abundant log jams and
beaver dams, which create various degrees of natural disconnectivity
(Wohl \& Beckman, 2014; Green et al., n.d.). These naturally occurring
discontinuities should be distinguished from anthropogenic dams that are
nearly complete barriers to propagule, sediment and water fluxes.
Natural fluvial disconnectivity features buffer fluxes and allow
transport in temporal pulses and through leaky barriers; thus, lakes can
provide a model for how beaver dams and log jams, which are temporally
and spatially heterogeneous, affect functional connectivity of processes
affecting geomorphic form and ecological communities.

\textbf{ACKNOWLEDGMENTS}

Funding for this study came from the Swedish Environmental Protection
Agency and the Swedish Research Council Formas to LEP. Thanks to
Christer Nilsson, Anna Henriksson, Wiebke Schultz, Xiaolei Su, and Joe
Sundin for assistance with project development, field work and data
analyses.

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\textbf{TABLES \& FIGURES}

Table 1. Multiple linear regression models (selected based on lowest AIC
with backward-step selection) to predict channel width based on drainage
area, distance downstream from lake and type of surficial geology.
Surficial geology variables are categorical (1 or 0). All models: p
\textless{} 0.0001 and all parameters have p-values \textless{} 0.05.

\textbf{Hosted file}

\verb`image1.emf`  available at \url{https://authorea.com/users/474987/articles/564575-disrupted-connectivity-in-biotic-and-geomorphic-patterns-in-stream-lake-systems}

Table 2. Relationship between downstream position (order of reach) and
species richness and density for each process domain type and all
reaches combined (catchment); relationships for similarity are presented
between all sites and the geographical distance (in meters) between
them. P-values \textless{} 0.05 are shown in bold with their
corresponding R\textsuperscript{2} values.\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
& Similarity & & Richness & & Species density & Species density
&\tabularnewline
\midrule
\endhead
& p & R\textsuperscript{2} & p & R\textsuperscript{2} & p &
R\textsuperscript{2} & R\textsuperscript{2}\tabularnewline
Bjurb\selectlanguage{ngerman}äcken & & & & & & &\tabularnewline
Slow-flowing & 0.132 & 0.039 & 0.063 & 0.59 & 0.894 & 0.004 &
0.004\tabularnewline
Rapid & \textbf{\textless{}0.001} & \textbf{0.226} & 0.211 & 0.290 &
0.183 & 0.392 & 0.392\tabularnewline
Lake & 0.686 & 0.007 & 0.146 & 0.739 & 0.638 & 0.131 &
0.131\tabularnewline
Catchment & \textbf{\textless{}0.001} & \textbf{0.092} & \textbf{0.003}
& \textbf{0.429} & 0.694 & 0.099 & 0.099\tabularnewline
Hjuks\selectlanguage{ngerman}ån & & & & & & &\tabularnewline
Slow-flowing & 0.059 & 0.044 & 0.774 & 0.013 & 0.673 & 0.027 &
0.027\tabularnewline
Rapid & 0.794 & 0.002 & 0.508 & 0.158 & 0.149 & 0.555 &
0.555\tabularnewline
Lake & \textbf{0.002} & \textbf{0.176} & 0.284 & 0.361 & 0.430 & 0.216 &
0.216\tabularnewline
Catchment & \textbf{0.003} & \textbf{0.052} & 0.532 & 0.023 &
\textbf{0.047} & \textbf{0.212} & \textbf{0.212}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 1. (a) Conceptual diagram of disrupted connectivity of flow (Q),
sediment (Q\textsubscript{s}) \& propagules (seeds and other
revegetative plant parts). Solid arrows indicate high connectivity \&
dashed arrows indicate higher potential for disconnectivity. (b)
Conceptual diagram of stream networks with three distinct process
domains: rapids, slow-flowing reaches \& lakes.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 2. (a) Location of Bjurb\selectlanguage{ngerman}äcken and Hjuksån catchments (drainage
areas \textasciitilde{}350 km\textsuperscript{2}) along the Vindel River
(Bjurbäcken in light grey and Hjuksån in dark grey) in the Ume River
catchment. The location of Ume River catchment shown in grey within map
of Sweden (bottom left). Maps of sub-catchments (b) Bjurbäcken and (c)
Hjuksån show process domain reaches demarcated along the mainstem. All
lakes within catchments (on both mainstem and tributaries) shown as
light blue. The mouth of both rivers (Bjurbäcken and Hjuksån) are at the
Vindel River. Scale bar applies to sub-catchment maps.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 3. Relationship between channel width and drainage area for
rapids (red) and slow-flowing reaches (blue) with corresponding power
regressions (black line shows trend for combined reach types) for (a)
Hjuks\selectlanguage{ngerman}ån and (b) Bjurbäcken.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Figure 4. Relationships between species density (richness/area) and
distance downstream (blue points \& line) and cumulative richness (black
line) for (a) Hjuks\selectlanguage{ngerman}ån and (b) Bjurbäcken. Species density regressions:
Hjuksån (p = 0.0471, R\textsuperscript{2} = 0.21), Bjurbäcken (p =
0.694, R\textsuperscript{2} = 0.009). Relationships between similarity
between vegetation communities and distance between all reaches for (c)
Hjuksån and (d) Bjurbäcken. Linear regression: Hjuksån
(R\textsuperscript{2} = 0.05, p = 0.003), Bjurbäcken
(R\textsuperscript{2} = 0.092, p \textless{} 0.001).

\selectlanguage{english}
\FloatBarrier
\end{document}

