Download Time series analyses reveal possible responses by the lichen

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Local responses of lichen vegetation to regional climate change: evaluation of two
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scenarios based on time series analysis
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Anna V Jonsson Cabrajic1, Kristin Palmqvist1, Uno Wennergren2
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Sweden.
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Department of Ecology and Environmental Science, Umeå University, SE-901 87 Umeå,
Department of Physics, Chemistry and Biology, Linköping University, SE-581 83
Linköping, Sweden.
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Corresponding author
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Anna Jonsson Cabrajic
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Department of Ecology and Environmental Science
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Umeå University
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SE-901 87 Umeå, Sweden.
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Phone: + 46 90 786 5191
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Fax: +46 90 786 6705
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E-mail: [email protected]
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Running head: Potential responses of lichen vegetation to climate change
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Abstract
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Introduction
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As an effect of climate change, global temperature rise is suggested to be greater over
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land and at higher northern latitudes (IPCC 2007). In northern Europe, projections
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indicate annual warming and increased precipitation, with larger increases during winter
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(Räisänen et al. 2004). Understanding and predicting the response of species to climate
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change is essential to the functioning of ecosystems and long-term conservation
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strategies. The climate change debate has largely focused on the impacts on vascular
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plants (Cornelissen 2007). However, cryptogamic organisms such as lichens and
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bryophytes are functionally important in these northern ecosystems, e.g. for biomass
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production, nitrogen fixation (Kurina & Vitousek 2001), CO2 cycling (Botting & Fredeen
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2006), and forage for herbivores (Gaare & Danell 1999; van der Wal 2006; Austrheim et
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al 2007). Responses to climate change by these organisms would thus potentially have an
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impact on the whole ecosystem.
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Lichens and many bryophytes may decline in response to vascular plant
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expansion as induced by climate warming (Van Wijk et al 2004, Cornelissen et al 2001;
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Hobbie et al 1999), and may be more severe for higher temperature elevations
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(Cornelissen 2001). However, that may not be the case for epiphytic lichens that
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experience weak competition from vascular plants, so their large-scale responses to
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climate change will rather be more affected by their physiological growth responses
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(Brooker 2006). Lichens, and particularly epiphytic species, are closely coupled to the
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atmospheric conditions due to their poikilohydric nature (Jonsson et al 2008); where
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green-algal lichens can be hydrated and activated almost instantaneously by rain, or
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gradually by humid air at water potentials (ψair) close to zero (Rundel 1988, Jonsson et al.
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2008, Pintado & Sancho 2002). Hence, it would be intuitive that poikilohydric organisms
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with such a coupling to environmental conditions would be one of the first to be affected
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by climate change. Growth model variables sensitive to climate change for these
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organisms would further rather be related to atmospheric humidity and precipitation
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patterns than to soil moisture (Berry et al 2002, Pearson et al 2004, 2006, Sancho et al.
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2007), or length of the thaw-free growing season for vascular plants in the boreal region
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(Jarvis & Linder 2000). The prolongation of the latter is suggested to be the major factor
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increasing net primary production as a response to climate warming in northern
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ecosystems (Cao & Woodward 1998; Jarvis & Linder 2000). However, epiphytic lichens
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can stay active even throughout the dark winter period when occasionally mild
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temperatures and increased humidity activate respiration. The response to climate change
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may therefore be quite different for lichens compared to vascular plants.
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Within a forest, micro-climate can vary on a small spatial scale and generate
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largely contrasting habitats with respect to light, humidity and temperature conditions
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(Renhorn et al. 1997). As a result lichen growth can vary substantially depending on the
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particular combination of the climatic conditions (Sundberg et al 1997, Palmqvist and
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Sundberg 2000, Gaio-Oliveira et al 2006, Caldiz…, Gauslaa, Sancho). In Scandinavia,
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the projected warmer and wetter weather with concomitant decreased irradiance, due to
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more overcast skies, will be altered in absolute terms on a regional scale (REFERENS
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IPCC; SMHI). Lichen growth will subsequently be affected by the perturbed climate on
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this regional scale. However, the site-specific growth of epiphytic lichens within the
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forest will potentially also be altered depending on how the regional climate change will
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affect the relative strength of the different micro-climate variables on the more local
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scale.
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The expected climate change scenarios (IPCC; SMHI) result from modeling and
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adjustment of its parameters by empirical data. Yet, if we would like to find out how the
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lichens may respond to such conditions we need to add a lichen growth model to the
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scenarios. Such a lichen growth model may then use the result of the climate model as
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inputs and then calculate the growth. The parameters that control their growth should
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then be based on empirical studies and adjusted according to projected change.
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The aim of this study was to assess potential climate change responses of
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epiphytic lichens in northern ecosystems simulating their responses from a net carbon
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gain model (NCG) to two predicted scenarios. Local responses to the two predicted
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regional changes were then evaluated by comparing two contrasting habitats. Both
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climate change scenarios, one moderate (b2) and a more intense (a2) adopted from IPCC
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(2007), involved the combination of projected changes in temperature, humidity and
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irradiance towards the end of the 21st century. To model the lichen responses, data on
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several aspects were required: (1) responses of a model species to controlled micro-
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climate; (2) field micro-climate of contrasting habitats for a reference period; (3)
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accompanying growth measurements during the reference period. These requirements
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were fulfilled for the foliose and epiphytic lichen Platismatia glauca using literature data
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(Renhorn et al. 1997; Sundberg et al. 1997). In addition, the continuously changing lichen
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water content was simulated using relative humidity and air temperature data by a
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biophysical model developed before for this species (Jonsson et al. 2008). We
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hypothesized that the predicted warmer and relatively drier summer period would
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decrease their wet and active growth period. During winter, we hypothesized that
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respiration would be increased as a result of prolonged activity periods in darkness due to
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wetter and warmer conditions.
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Material and methods
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Growth model description and parameterization
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A Net Carbon Gain (NCG) model was developed to simulate lichen growth responses to
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varying micro-climate conditions. The model was developed from laboratory CO2 gas
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exchange data, field micro-climate data, and growth of field transplants for the lichen
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Platismatia glauca (Renhorn et al. 1997, Sundberg et al. 1997). The model species P.
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glauca is a foliose epiphytic lichen, with green algal Trebouxia sp. photobionts, growing
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mainly on Norway spruce (Picea abies) in boreal forests. The thallus is loosely attached
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to the substrate with a high exposure to the surrounding atmosphere. The lichen had been
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collected in two sheltered and relatively dark Norway spruce forests in northern Sweden
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and transplanted in three 100 m long and parallel transects from the exposed edge to
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closed canopy interior conditions of a mature (110 year) boreal Norway spruce forest
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within
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(64°14´N,19°46´E; 230 m above sea level). Growth of the lichen was measured after 16
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months (9 July 1993 to 27 October 1994). Micro-climate was measured every minute and
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recorded with 10 min intervals at one of the exposed and one of the interior sites from 16
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August 1993 until harvest (Oct 27, 1994); monitoring irradiance (I), air relative humidity
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(RH) and air temperature (T) (raw-data kindly obtained from the authors). Water content
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(WC) of the lichen was simulated from RH and T, as described in growth simulations. No
Svartberget
Experimental
Forest,
in
Västerbotten,
northeast
Sweden
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micro-climate data had been obtained from 10 to 18 March 1994. Therefore, the model
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simulated lower accumulated light, WC and temperature for this month than would
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otherwise be.
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Net photosynthesis (NP) and respiration (R) had been measured in a flow through
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CO2 gas exchange system keeping [CO2] at ~ 35 Pa in response to controlled conditions of
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I, thallus WC and T, using thalli collected at the same time and from the same site as for the
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transplantation, see Sundberg et al. (1997) for details. The lichen responses were recorded
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for a wide and field realistic range for I, WC and T, by consecutively increasing or
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decreasing the studied variable and at the same time keeping the other variables constant.
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The functions of the below NCG model equations (Eqns. 1-5) were chosen to fit this
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original data (Sundberg et al 1997: Fig 1 and 2). The level of complexity of the functions
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was furthermore chosen to ensure significant parameters during regression. More
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specifically; (i) the photosynthetic light response curve for NP is best described by a non-
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rectangular hyperbola (Lambers et al. 1998), (ii) maximal gross photosynthesis (GPmax) at
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light saturation was assumed to be temperature (T) dependent (Reiter et al. 2008, Flora ref),
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(iii) R was assumed to be temperature dependent (Kershaw, Kappen, Sundberg et al. 1999),
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(iv) R and GP was further assumed to be linearly (R) or non-linearly (GP) dependent on
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WC at the interval between maximum and minimum WC
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Net photosynthesis (NP) was calculated as
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NP = GP-R.
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The light response curve of GP was then calculated as
Eqn 1
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(( I +Pmax - (( I + Pmax )2 - 4 IPmax )0.5 )
2
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GP 
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Furhermore, GPmax was calculated as Eqn 3.
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G Pmax  aT  bT 2
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The water response of GP was corrected by Eqn 4.
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GPkorr  c(1  e  d WC )
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Dark respiration was calculated as Eqn 5.
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R= fT
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The water response of respiration was then calculated as Eqn 6
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Rkorr= gWC
Eqn
2
Eqn
3
Eqn 4
Eqn 5
Eqn 6
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The NCG model was parameterized by linear and non-linear least-squares
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regression of the above equations using the complete data-set for I and T responses
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(Sundberg et al. 1997: Fig 1) and the software Statistica 8.0 (StatSoft, Inc. Tulsa,
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Oklahoma, USA) (Table 1). The correction factor for GP (NP+R) in response to suboptimal
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water contents was parameterized by non-linear least-squares regression (SigmaPlot 8.0;
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Systat Software Inc, Richmond, California, USA) using data in Sundberg et al. (1997: Fig.
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2) that was rescaled between 0 and 1 (where 0 represent no response in relation to a dry
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thalli and 1 the maximum response in relation to optimum WC). The equation’s parameters,
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units, and values are presented in Table 1. The convexity (θ) was initially set to 0.9 in the
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light response curve (Eqn 2), which is realistic for green-algal lichens (Palmqvist &
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Sundberg 2000). The approximated values for Ф and θ (Table parameters) were further
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adjusted to optimize the NCG model in relation to observed growth at the interior location
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(Sundberg et al. 1997), since the lichen had been collected from a shaded forest interior site
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(Renhorn et al. 1997). Values for Ф and θ were optimized by an iteration process so that
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simulated growth corresponded to the observed growth, using the approximated values as
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start values (Table 1).
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Growth simulations and validation
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Growth of the lichen was simulated from Eqns. 1-5 combined with reference micro-
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climate data from one forest interior site and one exposed site (Sundberg et al. 1997),
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either from the actual measurements of I, RH and T (Sundberg et al.1997) to validate the
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model in relation to the obtained growth at all forest interior sites and exposed edge sites
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in Renhorn et al. (1997), or the climate change scenarios (see below) to derive predicted
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growth. The Lichen WC was simulated using a biophysical model, developed before,
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using RH and T to derive ψair and species-specific rates for water uptake and loss
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(Jonsson et al. (2008). All simulations were made by the Matlab software package
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(R2006a; The MathWorks, Natick, Mass., USA), and were based on measured or
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simulated 10-min averages of I, RH, T and WC. The NCG-model yielded instantaneous
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gas exchange data on NP, GP and R, which can be summed monthly to get a net carbon
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gain (NCG). To derive the dry weight (DW) change, the specific thallus weight (g m -2) of
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P. glauca was set to 94.7 (Sundberg et al. 1997, Palmqvist and Sundberg 2000) it was
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assumed that the dry weight constituted mainly of sugar equivalents so that 6 mole
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assimilated CO2 was required for each mole of reduced sugar.
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Climate change scenarios
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The lichen responses to climate change were calculated for two climate change scenarios.
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These scenarios involved seasonal patterns of elevated T and RH, and concomitant
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decreased I due to a higher frequency of overcast skies. One of the scenarios was based
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on a moderate climate change (b2) while the other was more intense (a2). These scenarios
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are based on two levels of possible, still realistic human population growth and CO2
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emissions per capita (IPCC 2007). SWECLIM (Swedish Regional Climate Modelling
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Program) have previously applied these scenarios for Scandinavia and hence generated I,
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RH and T time series on a regional level (ref). We used the SWECLIM time series to
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transform the measured local climate time series from September 1993 to August 1994
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(Sundberg et al. 1997). The overall aim of the transformation of the local climate time
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series was to keep the variation in I, RH and T due to local effects, yet to enforce the
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scenarios of climate change. This transformation was made in two steps; (i) the regional
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climate change was calculated, and (ii) the measured local climates at the two sites
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(Sundberg et al 1997) were changed by adjusting their monthly mean and variance in I,
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RH and T according to projected climate change.
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The region that covered the sites was set and denoted the Västerbotten region (a
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rectangular area with the northwest corner: 64°93'N, 16°88'E, and the south east corner:
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63°60'N, 19°82'E). The climate change on the regional level was then calculated as the
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difference in monthly means and variances of I, RH and T between a reference period
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(1971-2000; provided from SWECLIM) and each of the two scenarios for the period
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2070-2100. These differences were further used to adjust the local climate time series.
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We adjusted the monthly means and variances either in absolute or relative terms. It can
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be assumed that for some climate parameters an absolute change is poorly applicable to
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local forest stands and instead a relative change is more functional and reasonable. For
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instance, light conditions would likely not change on an absolute level given local
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variation in forest canopy cover. Light would thus rather change on a relative basis, both
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in mean and variance. Hence, we assumed that humidity and light conditions would
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change on a relative basis, for both means and variances. As for temperature we assumed
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that the means would change on an absolute level whereas the temperature variation
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would change relatively. The applied monthly changes are presented in Table 2.
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Results
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Observed and simulated growth in the reference climate
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The growth simulations for P. glauca with reference climate at the exposed site (13 %)
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showed some discrepancy to the observed (4.5 %) for the complete transplantation period
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of 16 months (Sundberg et al. 1997). The observed growth at the reference climate was
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actually lower than at the interior reference climate (6.5%) probably due to the excessive
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light conditions experienced by the dark-adapted lichens, which would explain the
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discrepancy with the simulated growth. The simulated growth was more similar to the
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average growth of all three exposed sites with a total of 48 transplants in the full study
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(8.7 %) (Renhorn et al. 1997), and other studies have also reported similar ranges in
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growth responses between exposed and interior sites (Gauslaa et al. 2007, Jansson et al.
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2009). This implies that the parameterized model works well for interior conditions and
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for lichens that are adapted to exposed sites.
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Simulated CO2 exchange and growth at the interior location
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At the interior site, the simulated cumulative, annual growth was lower for the scenarios
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(4.5 and 4.2 for b2 and a2, respectively) than the reference climate (4.9 %) (Fig. 1a).
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Three time-periods emerged to cause the largest deviations in acquired net photosynthesis
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between scenarios and reference climate; November-December, March-April and June-
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August, where the first and the latter period contributed to the decreased growth response
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(Fig. 1 and 2b).
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For instance, in November there was a decreased growth response in relation to
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reference climate, with a decrease of 0.3 and 0.5% per g DW for scenario b2 and a2,
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respectively (Fig 1a). In November, the scenarios provided longer and wetter wet periods
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than the reference, with proportionately longer wet periods in dark (Table 3, Fig 3a). In
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light, the average irradiance when wet was furthermore very low on an annual basis
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(Table 3). Hence, respiration increased more than the gross photosynthesis which resulted
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in a net CO2 loss for the scenarios in contrast to reference climate (Fig 2a-b), with a
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higher loss for scenarios a2.
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The time-period March-April resulted in a substantially increased growth for each
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scenarios relative to the reference climate. In April the growth was 2.2 % and 2.0 % per g
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DW for scenario b2 and a2, respectively, compared to 0.9 % per g DW for the reference
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climate (Fig. 1a). The higher growth was the effect of a relatively higher gross
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photosynthesis compared to respiration (Fig 2 a-b, 3b). The wet periods were longer and
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wetter for the scenarios compared to the reference (Fig 3b, Table 3), in both light and
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dark. Despite a more than three-fold increase in wet time in dark compared to 50 %
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longer wet time in light the average light in the latter periods were among the highest on
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an annual basis resulting in a slightly higher Iwet.
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The period June- August was most disfavored by the projected climate scenarios
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and was the period that contributed most to the lower annual growth by the scenarios
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relative to the reference climate (Fig 1). For instance, in June, the growth was merely 1.4
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% and 1.8 % per g DW for scenario b2 and a2, respectively, relative to the reference
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climate (2.5 % per g DW). Although the CO2 gain was lower for the scenarios the climate
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conditions leading to this result were divergent. For scenario b2, the total wet periods
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were substantially shorter than reference, specifically in light, resulting in a lower gross
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photosynthesis and CO2 gain relative to reference (Fig 2a-b, Table 3). For scenario a2, on
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the other hand, the total wet periods were longer, specifically in dark, than reference
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resulting in a relatively higher increase in respiration than GP and thus a smaller net CO2
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gain relative to the reference climate.
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In general, the wet periods were shorter in summer (June to Aug for b2) for the
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scenarios relative to reference conditions, and longer or unchanged in the autumn, winter
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and spring. The temperature was increased during the wet periods for the scenarios
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during all months, both in light and in darkness (Table 3).
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Simulated CO2 exchange and growth at the exposed location
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The simulated cumulative, annual growth at the exposed site was nearly equal for
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scenario b2 (8.2 %) but higher for a2 (9.7 %) than the reference climate (8.4 %) (Fig. 1b).
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In general, the same changes in wet time were apparent at the exposed site as for the
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interior site. However, the average irradiance during the wet periods in light was much
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higher at the exposed site compared to the interior site, for both scenarios and reference
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climate.
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The higher growth for the scenarios at the exposed site was mainly attributed to
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the relatively higher gain in April which outweighed the reduced gains in June to August
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(Fig 2 b,d), except for growth in scenario b2. For scenario b2, the gain in June was
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substantially smaller than reference which coincided with a considerably shorter wet,
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active time in light, a lower average WC level when wet (not shown), and a lower Iwet. In
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contrast to the interior location, the growth response was not negative in November to
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December at the exposed site. But as for the interior location, the wet periods were
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shorter during summer (June-Sep for b2) and longer or unchanged for the remaining
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months.
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Growth in relation to prevailing wet time and climate conditions
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There was a strong positive relationship between growth and Iwet, both at the interior and
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the exposed location (Fig 4). However, the slope of the regression, or the growth
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efficiency with increased Iwet, was steeper for the interior location. At the exposed
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location, there was also a strong relationship between wet time in light and growth but
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was not as evident at the interior location (not shown).
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Discussion
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The responses of the epiphytic lichen to regional climate change scenarios were not
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uniform on the local scale, but rather diverging in relation to the specific site within the
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forest. The cumulative growth was lower in response to the climate change scenarios than
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the reference climate at the interior site but was in contrast equal or higher at the exposed
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site. These results are intriguing, implying that responses to general regional climate
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change are complex and can not easily be applied to the local scale.
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Local variation caused by the poikilohydric and symbiotic life-style
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Lichen growth is limited by the irradiance during wet time (Palmqvist & Sundberg 2000;
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Gaio-Oliveria et al. 2004). Growth was indeed two times larger at the exposed site (8.2 -
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9.7 %) than at the interior site (4.2-4.9 %) (Fig. 1). These trends have also been reported
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for epiphytic lichens before. For example, the growth of Usnea longissima and P. glauca
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varied two-fold with increasing exposure in the same continental region as this study was
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conducted (Renhorn et al. 1997; Jansson et al unpublished). Hence, the simulated results
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in this study were in line with those expected for this region. It would thus be expected
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that the projected reduced light conditions would generally impose a decreased growth.
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However, the growth increased five times in April at the exposed site (Fig 2d), implying
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that growth was not limited by light per se at this site.
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Instead, since lichens can not actively regulate their water content, any climate
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change affecting the wet periods might have as high effect on the responses for
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poikilohydric organisms as irradiance levels. During spring and late autumn, the
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projected temperature elevation extended the wet, active time for periods near melting
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point, since this species was projected to be active only for temperatures > 0 °C. In
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addition, the projected climate change increased humidity that in turn increased hydration
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level when wet. In April, it was thus the extended and wetter time periods in sufficient
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light that increased assimilation at the exposed site so much that it overbalanced the
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increased respiration with the resulting increased net carbon gain and simulated growth
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by five times (Table 3, Fig 2, 3d). The importance of more humid conditions was also
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reported for U. longissima, with a more than two time’s higher growth response in the
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wetter, sub-oceanic climate than in the drier, continental climate with identical light
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exposures (Gauslaa et al. 2007).
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Hence, the altered timing and level of irradiance and hydration is very important
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for the local responses to climate change. Increased hydration was positive at the exposed
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site in April but might also have negative effects. In dark periods such as in November,
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the combination of wetter, warmer and darker conditions at interior site resulted in an
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increased respiration and subsequent decreased growth response compared to reference
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(Fig 2, 3c). At the exposed site on the other hand, the somewhat lighter conditions in
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November offset the respiratory loss (Fig 2). Hence, a wetter climate might lead to
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contrasting responses locally due to the combined effect with concurrent light and
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temperature conditions, due to e.g. variations in forest exposure or topography. The
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negative responses by increased respiration in warm, dark conditions (Sundberg et al.
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1999) might also be further reinforced by a decreased capacity of the lichens to manage
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drought stress (Bewley and Krochko 1982; Farrar 1988).
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Climate change might also impose warmer and drier climates as exemplified in June-
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August. Then the carbon assimilation was reduced as a consequence of the decreased wet
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and active time (Fig 2, Table 3).
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Consequently, lichen growth increases with increased irradiance during the wet
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periods, as also observed in this study (Fig 4), and that can be obtained either by high
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irradiance when wet or by long wet periods in low light. In this study, the site exposure
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caused the large response differences between the interior and the exposed mainly due to
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the differences in light conditions. However, the responses to projected climate change
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were mainly affected by the altered hydration patterns, responses that in turn varied with
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forest site. At the exposed site increased hydration increased growth due to sufficicnet
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light conditions when wet, but increased hydration at the interior site occasionally had
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negative effect due to limited light conditions when wet.
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Although the poikilohydric life-style is characterized by clear temporal water
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availability, vascular plants with a more even water supply may also be affected
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differently on a local scale. The growth season will also for vascular plants be prolonged
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in a warmer climate in northern ecosystems. This extension has mainly been discussed in
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positive terms by potentially increased timber production (Jarvis & Linder 2000; Zheng
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et al. 2002). However, if the growth period is extended into the dark period, the effects
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may be more complex. For coniferous seedlings the cold tolerance was strongly
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correlated with their soluble sugar contents (Ögren et al. 1997). An extended growth
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season into dark conditions can therefore increase respiratory loss and deplete the sugar
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reserves which increase the sensitivity to cold temperatures in subsequent winter period.
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Also for ground vegetation below insulating snow cover, die-back was caused by
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respiring soluble sugars in the shoots during mild winters (Ögren 1996). Hence, more
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light exposed vegetation may still assimilate carbon during the extended growth period
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whereas the vegetation in the darker areas may suffer from respiratory loss and
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subsequent cold intolerance.
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Modeling climate change responses
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This study show that the local scale responses are not so easily predicted from regional
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scale climate changes. It was also clearly showed that the local scale responses are the
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combined effect of regional climate change and the transformation of these micro-
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climatic variables to local conditions, i.e. forest structure, topography, which is well
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illustrated by organisms such as lichens.
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Moreover, when predicting the biological effects of climate change, both abiotic
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and biotic aspects are important to consider. For example, the projection of merely
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temperature increase would not render the more complete picture presented here. The
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combination of various micro-climatic factors generates additive effects that are difficult
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to anticipate. In addition, the contrasting climatic change responses in June were mainly
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attributed to the diverging projections in humidity variation. Low humidity variation
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generated a more flat time-series with fewer or shorter peaks with sufficiently high
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relative humidity to activate the lichen (not shown). This showed that climatic variability
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can have just as high impact as projected change in averages, and emphasize that
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predicting future climate change responses demands well-founded assumptions regarding
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projected climate.
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The biotic responses in this study represent a lichen adapted to darker
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environments. However, intra-specific range in performance facilitates some adaptation
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to the current micro-climate. In more light adapted individuals the amount of algae would
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increase resulting in a higher GPmax and a decrease in the relative respiration (refs).
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Hence, at the exposes site the carbon gain would likely be even higher than the simulated
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responses in this study, and increasingly so for the scenarios. Consequently, the
19
411
divergence between interior and exposed site would if any be larger if the individual
412
responses would have been adjusted for.
413
The simulated responses are also affected by the parameterized and/or assumed
414
species specific responses to each variable. For instance, P. glauca was parameterized to
415
be active only for temperatures above freezing. This is realistic for this species (Sundberg
416
et al. 1997); just like for vascular plants. However, lichens can also be activated for
417
subzero temperatures from atmospheric humidity, although the gas exchange at these
418
temperature was low (e.g. Lange et al. 1977; Kappen et al. 1995; Hajek et al. 2001; Lange
419
2003; Bartak et al. 2007). The results are though still applicable…? In addition, the water
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response can for other species be more hampered at high water contents (Lange, Green &
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Heber 2001)). Therefore a projected wetter climate could for those species be further
422
hampered if the water contents reaches high levels.
423
Little is known about long-term acclimation of lichens to increased temperatures.
424
This will have effects during the extended active periods in dark with resulting increased
425
respiratory loss of carbon. Acclimation has been reported for vascular plants have (Atkin
426
et al 2005). Sundberg et al (1999) found a decreased respiration rate of lichens lasting up
427
to ten hours and potentially longer after a change in hydration or temperature, hence
428
lasting longer than the initial respiration burst of ca 10-20 minutes (Sundberg et al. 1997).
429
The NCG model was parameterized for NP data acquired after the initial burst, but the
430
respiration may hence decrease further during long hydration periods.
431
Moreover, photosynthetic organisms only respires soluble carbohydrates, so
432
during extended hydration periods in dark the thallus can not respire more carbon that
433
was built up in the carbon pool during previous storage periods (Dahlman, Lange?). If
20
434
this feature would be included in the model the negative growth response would be
435
reduced for the interior location in November.
436
The here developed model related photosynthesis and respiration merely to
437
temperature, but these factors and resultant growth have also shown to be positively
438
correlated to thallus Chl a – content (Palmqvist & Sundberg 2000; Palmqvist et al. 2002;
439
Palmqvist & Dahlman 2006). The Chl a-content varies inter-specifically (Palmqvist et al.
440
2002), and intra-specifically in response to nitrogen status (Palmqvist et al. 1998;
441
Palmqvist & Dahlman 2006) and light exposure (Jonsson, Moen, Palmqvist, unpublished;
442
Jansson, Esseen, unpublished). The inclusion of Chl a content in the model would
443
however not affect the outcome in this study since the thallus-specific variation in Chl a
444
was very low within the exposure gradient, both before and after the transplantation
445
experiment (Sundberg et al. 1997; Renhorn et al. 1997). However, for the purpose of a
446
multi-species comparison to climate change scenarios this factor would likely be
447
important and therefore included in the model.
448
The empirical responses to climate change will be greatly affected by the
449
reference climate at the local site. The results in this study rely on simulations during one
450
year which of course is a too short time span to interpret long-term climate change.
451
However, realistic seasonal changes were revealed in this study by the joint projections of
452
three important micro-climate variables. These results can thus be extrapolated to years or
453
seasons with different climate conditions.
454
455
456
Potential epiphytic community effects
The implications of these local scale responses are fascinating. Previous studies on
457
climate change responses have mainly emphasized the northward movement of lichen
21
458
populations (ref Holland , Håkan?). But these simulation results, however, stresses that
459
lichen populations would rather be redistributed on a local scale towards exposed habitats
460
by the favorable growth conditions at these sites, and thus reinforce the current pattern of
461
increased growth here. Moreover, a northward movement of populations is not obvious in
462
northern ecosystems since organisms may be more hampered by suboptimal light
463
conditions at these latitudes than suboptimal temperatures.
464
The redistribution will favor individuals and species that can survive the
465
potentially adverse effects of growing at these sites. Many species are sensitive to
466
increased wind exposure and the resultant thallus fragmentation, especially those that are
467
sensitive to forest fragmentation e.g. “old forest” lichens Alectoria sarmentosa or Usnea
468
longissima (Esseen & Renhorn 1998; Jansson et al. Unpublished data for U.longissima).
469
These species are suggested to harbor more interior sites, not because the growth
470
conditions are suboptimal at the most exposed sites, but due to their sensitivity to thallus
471
fragmentation. If the growth conditions will be increasingly favored at the exposed sites,
472
lichens must adapt by being less sensitive to wind exposure.
473
Drier conditions at more light exposed sites may also favor a poikilohydric life-
474
style (ref). Such conditions are projected for instance in the Mediterranean area (ICPP
475
2007), but may still occur at more northern altitudes at dry, exposed sites.
476
Projected warmer and wetter conditions during dark seasons may as discussed
477
affect lichens negatively. Lichens have a relatively high respiration load per DW due to
478
the large body of fungal tissue compared to algal cells (????). Warmer and wetter
479
conditions in dark, interior sites may thus affect lichens more severely than for instance
480
bryophytes that have low light compensation point (Proctor 1990). Bryophytes can also
22
481
cope with higher hydration levels than lichens, due to a water separating structure in
482
some bryophytes (Proctor 1990) whereas lichens can suffer from depressed
483
photosynthesis due to increased CO2 diffusion resistance at high WC levels (Lange et al.
484
2001). Hence, the symbiotic life-style may be too costly in dark, wet micro-climates and
485
is likely to be outcompeted by bryophytes that are more adapted to these conditions.
486
487
488
. However, lichens can potentially adapt to the prevailing micro-climatic conditions
489
(Hajek et al. 2001). The latter furthermore entails an increased dispersal limitation since
490
new habitats are more distant. The intra-specific response variation facilitates selection
491
for individuals with favorable responses in current micro-climate. These traits are on the
492
other hand unlikely to persist since lichen species also in the future must maintain some
493
plasticity to be able to disperse to new micro-climates and support a viable population.
494
Most likely, the realized niche will be reduced with a transition in optimum abundance
495
towards more semi-exposed habitats.
496
497
498
Conclusions
499
Regionally changed climate conditions generated diverging local responses. The local
500
responses are instead affected by how the regional climate change is reflected onto the
501
local scale.
502
Poikilohydric organisms can not regulate their wet active periods. In climate scenarios
503
projecting wetter conditions the responses are diverging on a local scale. Epiphytic
23
504
lichens will face a higher risk of negative responses in dark, wet ecosystems but a chance
505
to positive responses at wet, exposed sites.
506
507
Acknowledgements
508
We thank Per-Anders Esséen, Bodil Sundberg and Karl-Erik Renhorn for access to
509
micro-climatic data from their lichen transplantation study in Svartbergets Försökspark.
510
We also thank Rossby Center for providing us with data on climate scenarios.
511
512
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513
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