Online resource 1 belonging to:
Synthesis of ecosystem vulnerability to climate change in the Netherlands shows the
need to consider environmental fluctuations in adaptation measures
by
PM van Bodegom, J Verboom, JPM Witte, CC Vos, RP Bartholomeus, W Geertsema, A
Cormont, M van der Veen & R Aerts
Regional Environmental Change
Affiliation of corresponding author:
VU University Amsterdam, Department of Ecological Science, section of Systems Ecology,
de Boelelaan 1085, 1081 HV, Amsterdam, the Netherlands
e-mail: p.m.van.bodegom@vu.nl
Additional methodological details for impact study 1: Meta-analysis of retreating and
expanding species
A long tradition of vegetation records in the Netherlands allowed compiling decadal-long
records on the occurrence of plant species per 1 km2 grid cells. From this database, we
selected three periods, i.e. 1902-1949, 1975-1984 en 1985-1999, to determine local increases
and decreases of plant species indicative for ecosystem types prevailing in the Netherlands.
Note that most observations were from the latter two periods. Local changes in species
occurrence may be due to stochastic events, climate-related changes and land use related
impacts. To discriminate among effects by climate vs. other drivers, regression analysis was
used to determine for which species changes in local abundance were correlated to climate
variables (Tamis et al. 2005). Selected variables indicative of climate include the plot mean
Ellenberg indicator value of continentality, and the average temperature of the grid cell in
which the respective plant species occurs. Similarly, to evaluate the potential impacts of other
environmental changes, plot mean Ellenberg indicator values for nutrient availability,
moisture availability, salinity, and acidity were applied. In addition, the impact of 'Urbanity'
(as an ordinal factor) was analysed. Here we present the percentage of species for which the
local decrease or increase in occurrence was related to climate variables. No relationship
between the vulnerability and rareness of ecosystem types was found. Although this analysis
does not allow deciphering causality or individual drivers of species distribution, it is
indicative for the impacts of climate change.
Additional methodological details for impact study 2: Climate impacts sketch map
A national hydrology model (Vermulst and de Lange 1999) was run to identify general trends
in possible hydrological effects of climate change. The model had a spatial resolution of 250
m and a temporal resolution of 10 days. With the aid of a digital elevation model, simulated
groundwater levels and seepage intensities were downscaled to a spatial resolution of 25x25
m. To evaluate hydrological quantities for current climate conditions, we considered two
meteorological years (with accurate data quality) to represent climate variability in the
current climate: an average (1967) and a dry year (1949), with return periods of 2.5 and 11.7
yr, respectively. This selection was done to obtain feasible computation times. To initiate the
appropriate hydrological conditions, the calculation for these two characteristic years was
preceded by an additional year of simulations (1966, 1948).
For the future climate, we considered two scenarios; W and W+, according to the national
climate scenarios (Bakker and Bessembinder 2007). The W scenario assumes an increase in
temperature of 2 °C in 2050 without changes in air circulation. The W+ scenario additionally
assumes changes in air circulation, leading to wetter winters and drier summers. These
national climate scenarios are based on global climate projections based on international
consensus of expected change (Solomon et al. 2007), translated to detailed changes in
temperature, precipitation and evapotranspiration for the Netherlands. Temperature
modulates transpiration, and thus affects the water balance. Impacts of enhanced CO2 levels
on transpiration were not incorporated in the simulations. Projected climatic conditions were
obtained by transforming time series for temperature, precipitation and evapotranspiration of
1948, 1949, 1966 and 1967 to the 2050-climate of W and W+, using transformation software
supplied for these scenarios (Bakker and Bessembinder 2007).
General trends, but not the results in an absolute sense, were used to identify general trends in
possible hydrological effects of climate change. Hydrological quantities, relevant for
terrestrial ecosystems, considered were: moisture deficit (difference between potential and
actual transpiration), seepage intensity and saline load (all on an annual basis); lowest,
highest and spring groundwater depth (relative to soil surface); the average percentage
surface water imported from the rivers Rhine and Meuse in July.
Indicative trends per ecosystem type were assessed by overlaying the model estimates of
abovementioned hydrological quantities for the current climate and the two climate scenarios
with a current national vegetation map (which implicitly reflects current land use and water
management practices). In this way we obtained, per ecosystem type, current and future
frequent distributions of the hydrological quantities.
These trends were supplemented by a literature survey and expert knowledge to sketch the
consequences of climate change for a limited number of ecosystem types, such as bogs, fens,
wet heathlands, dry heathlands, woodlands and streams. The literature survey considered i)
environmental impacts on plant communities, including results obtained from ecological and
ecohydrological models, ii) the impact of deep groundwater levels on capillary flow to the
rooting zone, iii) groundwater recharge as affected by vegetation feedbacks, iv) increased
surface water flows to accommodate for agricultural demands and its impacts on water
quality, and v) increased dynamics in the hydrology through increased climatic variability in
a future climate (further details in Witte et al. 2012).
Expert knowledge came from the 9 authors (ecologists and hydrologists) of Witte et al.
(2012), as well as from two workshops for provinces, water boards and nature conservation
organisations, which led to minor adjustments.
Additional methodological details for the meta-analysis of relations between water-related
stresses and species occurrences
We selected 185 vegetation plots distributed across the Netherlands, that originate from a
wide range of terrestrial vegetation types differing in succession stages, soil type (sandy,
clayey, loamy), soil moisture regime, nutrient availability and soil pH. None of the
investigated plots had been under the influence of a structural change in water management
conditions in the last decades. All vegetation plots were representative of (semi) natural
habitats.
For groundwater-dependent sites, biweekly measurements of groundwater level data were
available in or immediately next to each vegetation plot, but only for specific periods and for
a limited number of years (min 3 years, max 8 years). The groundwater level series were
extended to the period 1971-2000, and interpolated to daily values with the Menyanthes
model (Von Asmuth et al. 2002).
Subsequently, for each plot, soil moisture and soil temperature profiles in the root zone
(consisting of 16 layers to allow for layer-specific soil physical properties) were simulated on
a daily basis for the period 1971-2000 with SWAP (Van Dam et al. 2008). Daily groundwater
levels served as the bottom boundary conditions. For groundwater independent sites, constant
deep groundwater levels were used as bottom boundary condition. The meteorological input
for the SWAP-simulations consisted of daily precipitation, evapotranspiration data and daily
temperature as available from neighboring weather stations of the Royal Netherlands
Meteorological Institute from 1970 onwards.
Potential daily transpiration reduction, i.e. the difference between the potential and the actual
transpiration for a reference grassland not adapted to drought, was output from the SWAPmodel. Likewise, potential daily respiration reduction (i.e. potential minus actual respiration
of a reference grassland not adapted to wet conditions) was calculated with a model for
oxygen transport and consumption, which uses generally applied physiological and physical
relationships to calculate both the oxygen demand of, and the oxygen supply to plant roots
(details in Bartholomeus et al. 2012). Daily soil temperature and daily gas-filled porosity in
each soil layer were input for this model and were derived in SWAP. The10-day period in a
year with the largest potential reduction in respiration and transpiration, respectively, was
selected. Such period has been shown to be sufficiently long for stress to strongly adversely
affect plant metabolism (e.g. Huang et al. 1998).
To determine potential reductions in respiration and transpiration for a future climate, time
series for temperature, precipitation and evapotranspiration of 1971-2000 were transformed
to the 2050-climate of W and W+, using transformation software (Bakker and Bessembinder,
2007). Complementary to these scenarios, and in contrast to the second impact study, we
corrected for a higher water use efficiency of plants at enhanced CO2 levels in 2050 by
decreasing reference evapotranspiration values by 2%, using the results and approach
described by Kruijt et al. (2008). Given that productivity or biomass was not used in the
calculations of transpiration (full vegetation cover was assumed), no corrections by enhanced
CO2 on productivity were applied.
The number of common and endangered species for the Netherlands within each vegetation
plot was determined according to van der Meijden et al. (2000). Endangered species were
representative for all natural ecosystem types throughout the Netherlands and had not been
selected because of known responses to oxygen and drought stress. For each plot, the number
of species was related to oxygen and drought stress in the current climate, using quantile
regression (Cade et al. 1999). Using the 95% quantile, this method enabled us to determine
the potential number of common and endangered species, respectively, that could potentially
occur under specific stress conditions.
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