The effect of temperature on growth and competition between Sphagnum species

Peat bogs play a large role in the global sequestration of C, and are often dominated by different Sphagnum species. Therefore, it is crucial to understand how Sphagnum vegetation in peat bogs will respond to global warming. We performed a greenhouse experiment to study the effect of four temperature treatments (11.2, 14.7, 18.0 and 21.4°C) on the growth of four Sphagnum species: S. fuscum and S. balticum from a site in northern Sweden and S. magellanicum and S. cuspidatum from a site in southern Sweden. In addition, three combinations of these species were made to study the effect of temperature on competition. We found that all species increased their height increment and biomass production with an increase in temperature, while bulk densities were lower at higher temperatures. The hollow species S. cuspidatum was the least responsive species, whereas the hummock species S. fuscum increased biomass production 13-fold from the lowest to the highest temperature treatment in monocultures. Nutrient concentrations were higher at higher temperatures, especially N concentrations of S. fuscum and S. balticum increased compared to field values. Competition between S. cuspidatum and S. magellanicum was not influenced by temperature. The mixtures of S. balticum with S. fuscum and S. balticum with S. magellanicum showed that S. balticum was the stronger competitor, but it lost competitive advantage in the highest temperature treatment. These findings suggest that species abundances will shift in response to global warming, particularly at northern sites where hollow species will lose competitive strength relative to hummock species and southern species.
Introduction
Peat bogs play a large role in the global sequestration of C. Although northern peatlands cover only 2% of the total land surface, they store about one-third of the world soil C in the form of peat (Gorham 1991). It is therefore important to know how ombrotrophic bog ecosystems, which form a large part of northern peatlands, will respond to predicted climate changes, especially since the rise in temperature is expected to be above the global average at high latitudes (Christensen et al. 2007) where the majority of peat bogs occur (Kivinen and Pakarinen 1980; Gunnarsson 2005).
Vegetation in ombrotrophic bogs is often dominated by different Sphagnum species. The Sphagnum species account for the bulk of the C sequestration in peat because of their recalcitrant litter (Coulson and Butterfield 1978; Clymo and Hayward 1982; Limpens et al. 2003). Therefore, it is crucial to understand how Sphagnum vegetation in bogs will respond to global warming in order to predict the role of bogs as C sinks in the future. Several studies have revealed differences in production (Lindholm and Vasander 1990; Gerdol 1995; Asada et al. 2003; Gunnarsson 2005) and in decomposition rate (Rochefort et al. 1990; Johnson and Damman 1993; Belyea 1996; Limpens and Berendse 2003) between different Sphagnum species. These differences between species are often related to differences in microhabitat preference (Gunnarsson 2005). Within a bog, different Sphagnum species occur at different heights above the water table and at different positions along pH and nutrient gradients (Andrus 1986; Sjörs and Gunnarsson 2002; Limpens et al. 2003). The most obvious division in microhabitat preference is between hollow species, which grow in pools and at shallow water levels, and hummock species, which grow at deeper water levels. Hummock species can also grow at higher water levels, but they are then usually outgrown by hollow species (Rydin 1986, 1993, 1997). However, the competitive ability of species may differ between years, seasons and locations, and as such, competitive replacement occurs very slowly, if at all. This results in a relatively stable competitive balance between species (Rydin 1997).
Several studies found a positive relation between Sphagnum productivity and temperature (Moore 1989; Sonesson et al. 2002; Gunnarsson 2005). The positive effect that increased temperature might have on C sequestration in bogs is, however, often diminished by the positive effect of temperature on decomposition rates (Hobbie 1996). Increased decomposition rates also lead to increased rates of nutrient release from the peat layer, enhancing production rates even further. A change in temperature influences not only the production and decomposition of individual Sphagnum species but also the competitive balance that exists between species. An important challenge facing ecologists is to predict how climate change will alter species distributions in ecosystems (Mooney 1991). Robroek et al. (2007b) already found different responses in biomass production among species when temperature was increased. It can be imagined that when a species with high production and/or a low decomposition rate increases its relative abundance in a bog, this will increase the C storage capacity of the system.
Not only are there different competing species within a bog, but there are also differences in dominant species between bogs when different climatic regions are compared. In this study, we used species from two different sites. At the site in northern Sweden, Sphagnum balticum and Sphagnum fuscum are the dominant species while at the site in southern Sweden these species also occur, but Sphagnum magellanicum and Sphagnum cuspidatum are the most abundant species. This corresponds with the general distribution of these species in Europe since both S. magellanicum and S. cuspidatum occur further south than S. fuscum and S. balticum (Daniels and Eddy 1985).
To examine the effect of temperature on the competition between species, we performed a greenhouse experiment in which we studied the effect of four temperature treatments on the growth of the four species: S. fuscum and S. balticum from a northern Swedish site and S. magellanicum and S. cuspidatum from a southern Swedish site. Three combinations of species were made to study the effects of temperature on interspecific competition. In our experiment we tried to answer the following questions:What is the effect of increased temperature on the growth of different Sphagnum species? We expect all species to show an increase in both height increment and biomass production as a direct result of increased temperature and indirectly through increased nutrient availability.What is the effect of temperature on competition between species? Since S. fuscum and S. magellanicum grow in drier and therefore also warmer microhabitats than S. balticum and S. cuspidatum respectively, we expect these species to be better adapted to higher temperatures. S. magellanicum grows at more southern sites than S. balticum, so we expect this species to be better adapted to higher temperatures. Consequently, we hypothesize that increased temperature will have a positive effect on competitive abilities of the hummock and southern species, leading to a relatively larger increase in height increment and biomass production with temperature than for hollow and northern species.
Materials and methods
Plant material
In August 2004, Sphagnum cores (diameter 16 cm, height 18–22 cm) were collected at two different sites in Sweden. From the northern site Lappmyran (64°09′N, 19°35′E), 30 Sphagnum fuscum (Schimp) H. Klinggr cores and 40 Sphagnum balticum (Russ.) C. Jens. cores were collected. This site is a string flark mire or mixed mire with ridges of hummocks and hollows where S. fuscum is dominant on the hummocks and S. balticum in the dryer parts of the hollows. When identifying the species from this site in the lab, we found specimens of both S. balticum and Sphagnum angustifolium (Russ.) C. Jens. These species are difficult to distinguish, which both Russow (Smith 1978) and Klinggraff (Daniels and Eddy 1985) recognized when they identified both species as varietas of Sphagnum recurvum. In our samples, we were unable to quantify the exact percentages of S. balticum and S. angustifolium. As result, whenever we mention S. balticum, we are referring to a mixture of S balticum and S. angustifolium.
From the southern site Saxnäs Mosse (56°51′N, 13°27′ E), 40 Sphagnum magellanicum (Brid.) cores and 30 Sphagnum cuspidatum (Hoffm.) cores were collected. At this site S. magellanicum occurs on the lawns and low hummocks and S. cuspidatum in the hollows and pools.
Cores were taken from monospecific stands of each Sphagnum species (>95%) with sparse vascular plant cover (<5%). The cores were placed in plastic containers (diameter 16 cm, height 22 cm). Vascular plants were clipped flush with the Sphagnum, and other Sphagnum species were removed with tweezers. The containers were brought to Wageningen and stored outside for 8 weeks before the greenhouse was available. As a result, containers from both sites could acclimate to the same climate to some extent.
Experimental design
At the start of the experiment, the containers were brought into the greenhouse and randomly divided over the treatments and five replicate blocks, with seven species combinations (four monocultures and three mixtures) and four temperature treatments per block. All four species were kept in monoculture and the following three species combinations were made to study interspecific competition: two northern species S. fuscum with S. balticum, two southern species S. magellanicum with S. cuspidatum and a northern with a southern species S. balticum with S. magellanicum. To study competition between a northern and a southern species we chose the combination of S. balticum and S. magellanicum because they occur at similar water levels. To make the combinations, the cores were cut into four equal quarters and two quarters of both species were placed alternately in an empty container. In potting the species combinations, we made certain that the surface of the mixture was uniform. We did not cut monocultures in four quarters, but another experiment showed no difference in water content between cut and uncut monocultures (Robroek et al. 2007a).
The experiment was conducted in four adjacent climate controlled greenhouse compartments from November 2004 till April 2005 for a total of 154 days. Each compartment was assigned one of four temperature treatments. Treatments and containers were switched between compartments every 2 weeks to minimize any effect of the different compartments. The position of the blocks and the position of containers within the blocks were also switched every 2 weeks. The average day temperatures in the four temperature treatments were 11.2, 14.7, 18.0 and 21.4°C, respectively (Table 1). During the dark period of 8 h, the day temperature was lowered by approximately 3–9.3, 11.6, 15.5 and 18.9°C, resulting in mean temperatures of 10.6, 13.7, 17.2 and 20.6°C in temperature treatments 1, 2, 3 and 4, respectively. In the region of the northern site, the mean temperature in July is 14.7°C (Alexandersson et al. 1991) and in the southern site the mean temperature in July is 17.0°C (Malmer et al. 2003). A light period of 16 h was applied. If light intensity was low during this period, SON-T AGRO 400 (Philips Powertone 400) lamps were used.
Table 1Day and night mean values of temperature (°C), relative humidity (%) and vapour pressure deficit (VPD) (kPa) of the four treatments, ±SE, n = 154TreatmentTemperatureRelative humidityVPDDayNightDayNightDayNightT111.2 ± 0.0493 ± 0.0581.9 ± 0.486.8 ± 0.40.24 ± 0.010.16 ± 0.01T214.7 ± 0.03116 ± 0.0576.9 ± 0.381.8 ± 0.50.39 ± 0.010.25 ± 0.01T318.0 ± 0.02155 ± 0.0375.2 ± 0.476.1 ± 0.40.51 ± 0.010.42 ± 0.01T421.4 ± 0.03189 ± 0.0472.7 ± 0.473.0 ± 0.50.70 ± 0.010.59 ± 0.01
Relative humidity during the day was set at 75%. In the greenhouse it was not possible to keep the relative humidity exactly the same with all temperatures. The rise in temperature between treatments corresponded with a decrease in relative humidity, which caused an additional increase in vapour pressure deficit (VPD) with temperature (Table 1). The difference in relative humidity only explained 33% of the increase in VPD with the highest temperature. If relative humidity would have been equal in all compartments, VPD would still have been twice as high at temperature 4 as at temperature 1. Our highest VPD of 0.7 kPa with a temperature of 21.4°C is actually still quite low compared to field conditions. Although not many data on VPD are published for similar ecosystems, Hobbie and Chapin (1998) did find the following values for VPD in Toolik Lake, Alaska, in June and July: in open field sites, 0.02–1.71 kPa with temperatures ranging from 5.9 to 22.5°C; and under small plastic greenhouses, 0.08–3.83 kPa with temperatures ranging from 6.4 to 31.1°C. Dorrepaal et al. (2003) measured a VPD of 1.54 under normal conditions and 1.41 in open-top chambers with an average temperature of 15°C in June and July in Abisko, Sweden.
The water level was set to 1 cm below capitula at the start of the experiment. All species were subjected to the same water level, so that temperature was the only changing environmental variable. This relatively high water level was used for all species because hollow species cannot grow at low water levels; while hummock species can survive the environmental conditions of hollows quite well; nonetheless, they are absent from these areas because of biotic factors (Rydin and McDonald 1985). Grosvernier et al. (1997) found that growth in height and dry weight is equal for S. fuscum grown at water levels of 1 cm and 40 cm below moss surface while, for S. magellanicum and especially for Sphagnum fallax, growth in height and dry weight is much greater with the high water level.
During the experiment an artificial rainwater solution, an 8,000-fold dilution of a sea water solution (Garrels and Christ 1965), was added twice a week to bring the water level back to 1 cm below capitula. The amount of water added was used as a measure of evaporation. The drop in the water table was highest in the highest temperature treatment, but water level never dropped more than 6 cm below moss surface between two water additions. In a number of containers, Sphagnum grew higher than 1 cm above the container. To keep the water level at 1 cm below the moss surface, a plastic ridge was glued onto the containers and the crack was filled with silicone kit. Water content was measured using a theta probe (Delta-T Devices, Cambridge, UK) before the final harvest of the experiment. This was done 3–4 days after watering the containers for the last time, so the water content would reflect possible differences between treatments.
Measurements
Height increment of the Sphagnum carpet was measured non-destructively every month using a variation of the cranked wire method (Clymo 1970). We used plastic rods that were inserted to a depth of approximately 8 cm and anchored by plastic broom bristles, this method kept the cranked wires firm at the same place so they did not move with Sphagnum growth. Two plastic rods were inserted in the monocultures and one plastic rod was inserted in each quarter of the mixtures. The rods had a diameter of 1.5 mm and did not seem to interfere with the growth of the surrounding Sphagna.
At the end of the experiment, columns with a diameter of 5 cm were cut around each cranked wire and cut off at 5 cm length. Each column was put in a plastic Ziplock bag and fresh weight was determined. All bags were stored at 1°C till further measurements could be taken. Capitula were defined as the top 1 cm of each individual plant and stem as the 1–4 cm part. Capitula and stems were separated per column and oven dried at 70°C for at least 48 h and then weighed. The weight of the total sample was used to calculate bulk density and the biomass production per squared centimetre to account for changes in capitulum density. For nutrient analyses, samples of capitula were pooled per species for each container. Total N, P and K concentrations were determined by digesting 300 mg of homogeneous, milled material with H2SO4, salicylic acid, Se and H2O2. All samples were analysed for total N and P spectrophotometrically using an auto-analyzer (Skalar). K concentrations were measured with an atomic absorption spectrophotometer (Varian AAS). To compare capitulum bulk density and nutrient concentrations with field values, we collected five samples (d = 5 cm) from monocultures of the four Sphagnum species in the two Swedish sites in August 2006. Measurements on capitulum bulk density and nutrient concentrations were executed as described above.
To measure the change in cover of the species in the mixtures, digital pictures were made at the start and at the end of the experiment. In these pictures we measured the total surface cover per species in each pot with Image J (Abramoff et al. 2004). The biomass production per unit area (g m−2) was calculated as follows:
Data analysis
Data were tested for normality and equality of variance. When necessary, data were square-root transformed to achieve homogeneous variances. Block effect was tested as random factor. When no block effect was detected, which was usually the case, block was omitted from the analysis to gain extra df. All analyses were conducted using the SPSS statistical package for Windows (12.0).
One container with a monoculture of S. balticum under temperature 4 was heavily affected by a fungal infection, probably Lyophyllum palustre. After 4 months, 90% of the plant material had died. This container was further omitted from the analyses.
Height increment in monocultures was tested per species with one-way ANOVA with temperature as independent factor. Height increment, biomass production, cover change, bulk density, water content and nutrient concentrations were tested per species. Two-way ANOVAs were performed with temperature and species combination as independent factors. The effect of temperature, species and competition on the concentrations of N, P and K was tested using a three-way ANOVA. Differences between the treatments were analysed using a Tukey post hoc test. To test how the environmental variables temperature, N concentration and water content influenced biomass production we performed a stepwise regression analysis per species.
Results
Height increment
In the monocultures, the height increment increased with temperature in each species (Fig. 1, Table 2). For S. cuspidatum this effect was least distinct with the lowest height growth at temperature 2 and no difference in growth between temperatures 1, 3 and 4.
Fig. 1Height increment of species in monocultures (cm). Data are mean values ± SE, n = 5 except for Sphagnum balticum at T4, n = 4. Different letters indicate significant differences (P < 0.05) between temperature treatments within each species. For temperature treatments, see Table 1Table 2F-values and P-values and direction of main effects influencing height increment and biomass production per speciesa, corrected for cover, using a two-way ANOVATemperatureCombinationT × combinationFPEffectFPEffectFPHeight incrementSphagnum fuscum (+Sphagnum balticum)49.31<0.001+1.170.288+0.920.445S. balticum (+S. fuscum)51.19<0.001+9.130.005−0.610.616S. balticum (+Sphagnum magellanicum)19.58<0.001+10.320.003−3.240.035S. magellanicum (+S. balticum)28.71<0.001+8.870.006−1.880.154S. magellanicum (+Sphagnum cuspidatum)18.53<0.001+4.860.035−1.140.350S. cuspidatum (+ S. magellanicum)10.80<0.001+18.83<0.001−0.860.470Biomass productionS. fuscum (+S. balticum)20.99<0.001+18.57<0.001−2.310.095S. balticum (+S. fuscum)19.41<0.001+5.480.026−2.040.128S. balticum (+S. magellanicum)9.68<0.001+12.380.001−3.470.028S. magellanicum (+S. balticum)17.50<0.001+44.99<0.001−1.670.193S. magellanicum (+S. cuspidatum)11.75<0.001+23.36<0.001−2.000.133S. cuspidatum (+ S. magellanicum)5.150.005+2.200.148−0.180.913aNumber of observations n = 40, except for S. balticumn = 39
Only S. fuscum showed no difference in height increment between monoculture and mixture. All other species showed a growth reduction in mixtures (Table 2). There were no significant interactions between the effect of temperature and competition on height increment, except for S. balticum in combination with S. magellanicum (Table 2). Temperature increased height increment of S. balticum in monoculture, while there was no effect of temperature in mixture with S. magellanicum (Figs. 1b, 2b). When we compared height increment between the two species in each mixture, the “wet” species S. balticum and S. cuspidatum had higher values than the “dry” species S. fuscum and S. magellanicum at temperature treatments 1 and 2 (Fig. 2). When temperature increased, the differences in height increment between the two species disappeared.
Fig. 2Height increment of the individual species at each temperature treatment (see Table 1) within the three mixtures of species: aSphagnum fuscum + S. balticum, bSphagnum magellanicum + S. balticum and cS. magellanicum + Sphagnum cuspidatum. Data are mean values ± SE, n = 5. Different letters indicate significant differences between treatments (P < 0.05)
Cover
The hollow species S. balticum and S. cuspidatum increased in area in 53 out of 60 containers when growing in the mixtures. In the other seven containers (three with S. magellanicum + S. balticum, two with S. fuscum + S. balticum, two with S. magellanicum + S. cuspidatum), cover changed less than 5%. For S. balticum there were significant effects of temperature (F = 3.67, P = 0.023) and neighbouring species (F = 4.95, P = 0.033) on expansion (Fig. 3a, b). Maximum change in cover was for S. balticum in combination with S. fuscum with temperature 2 and 3. There was no effect of temperature on expansion of S. cuspidatum (Fig. 3c, F = 0.88, P = 0.470).
Fig. 3Cover change for hollow species: aS. balticum in combination with S. fuscum, bS. balticum in combination with S. magellanicum and cS. cuspidatum in combination with S. magellanicum. Data are mean values ± SE, n = 5. There were no significant differences between treatments (P < 0.05). For temperature treatments, see Table 1
Biomass production
The response of biomass production to the temperature treatments was similar to the response of height increment (Table 2). In all species biomass production increased with increased temperature. S. fuscum showed the strongest response; this species increased its biomass production 13-fold from the lowest to the highest temperature treatment in monocultures (Fig. 4a). Only for S. balticum in combination with S. magellanicum was there a significant interaction between temperature and species combination in biomass production (Table 2). Temperature increased biomass production of S. balticum in monoculture and in mixture with S. fuscum, while there was no effect of temperature in mixture with S. magellanicum.
Fig. 4Biomass production corrected for change in cover for species in monocultures (mono) and in mixtures (mix) for each temperature treatment (see Table 1) and species combination: aS. fuscum (fus) + S. balticum (bal), bS. magellanicum (mag) + S. balticum and cS. magellanicum + S. cuspidatum (cus). Data are mean values ± SE, n = 4–5. Different letters indicate significant differences between treatments (P < 0.05)
When differences in biomass production between monocultures and mixtures are compared per temperature treatment, it shows that S. fuscum suffered from competition with S. balticum at temperature 3 because production was lower in mixture than in monoculture, but it no longer suffered at temperature 4 (Fig. 4a). At temperature 4 S. balticum does suffer from competition with S. fuscum, but not at lower temperatures. In the mixtures of S. magellanicum and S. balticum, S. magellanicum suffers from competition at temperature 1 and 2, whereas S. balticum suffers from competition at temperature 3 and 4 (Fig. 4b). Biomass production of S. cuspidatum did not show any effect of competition with S. magellanicum, while biomass production of S. magellanicum did suffer from competition at temperatures 1, 2 and 3 (Fig. 4c).
In the stepwise regression for biomass production of S. balticum, water content was selected as the most explanatory variable (R2 = 0.36, P < 0.001). For biomass production of S. fuscum (R2 = 0.52, P < 0.001), S. magellanicum (R2 = 0.36, P < 0.001) and S. cuspidatum (R2 = 0.12, P = 0.031), temperature was selected as the most explanatory variable.
Bulk density
Bulk densities were lower at higher temperatures for all species, except for bulk density of the capitula and stems of S. cuspidatum (Table 3). Compared to field values, capitulum bulk density of S. fuscum and S. balticum decreased with temperature, while capitulum bulk density of S. magellanicum and S. cuspidatum seemed to increase at low temperatures.
Table 3Bulk density of capitula section, stem section and total sample. Data are mean values ± SE, pooled within temperature treatment (see Table 1) and within competition treatment. Different letters indicate significant differences between treatments within a species (P < 0.05). There were no significant interactions between temperature and competition treatments. fus S. fuscum, bal S. balticum, mag S. magellanicum, cus S. cuspidatumField valueTemperatureCombinationT1T2T3T4Monofus–balmag–balmag–cusBulk density capitula (mg cm−3)S. fuscum38 ± 235 ± 2b37 ± 2b21 ± 1a17 ± 1a30 ± 2b25 ± 2a––S. balticum32 ± 126 ± 1b16 ± 1a14 ± 1a14 ± 1a20 ± 1b18 ± 2b15 ± 1a–S. magellanicum19 ± 121 ± 1b18 ± 1b13 ± 1a13 ± 1a17 ± 1–15 ± 117 ± 1S. cuspidatum19 ± 123 ± 122 ± 219 ± 119 ± 123 ± 1b––19 ± 1aBulk density stems (mg cm−3) S. fuscum18 ± 1b16 ± 1b15 ± 2ab11 ± 2a17 ± 1b14 ± 1a––S. balticum15 ± 1b11 ± 1a8 ± 1a9 ± 1a13 ± 1b9 ± 1a11 ± 1ab–S. magellanicum11 ± 1c9 ± 0bc8 ± 1ab7 ± 0a9 ± 1–9 ± 18 ± 0S. cuspidatum10 ± 110 ± 17 ± 17 ± 18 ± 1––9 ± 1Bulk density total sample (mg cm−3) S. fuscum22 ± 1c21 ± 1bc17 ± 1ab13 ± 1a20 ± 1b16 ± 1a––S. balticum17 ± 1b12 ± 1a10 ± 1a10 ± 1a14 ± 1b11 ± 1a12 ± 1ab–S. magellanicum13 ± 1c11 ± 0b9 ± 1a8 ± 0a11 ± 1–10 ± 110 ± 0S. cuspidatum12 ± 1c12 ± 0bc10 ± 1ab9 ± 0a11 ± 1––11 ± 0Values for material from the sites of origin (Field values, n = 5) are given for comparison. Number of observations for each species for each temperature treatment: S. fuscum and S. cuspidatum, n = 10; S. balticum, n = 14–15; S. magellanicum, n = 15. Number of observations for each species for each combination, n = 19–20
Bulk densities of both capitula and stems were lower in mixtures than in monocultures of S. fuscum and S. balticum. Similarly, in S. cuspidatum the bulk density of the capitula was lower in mixtures than in monocultures. There were no significant interactions between temperature and species combination.
Nutrient concentrations
The concentrations of all nutrients (N, P and K) differed between species and rose with increasing temperature. N concentration was also affected by the interactions of temperature by species (F = 2.66, P = 0.007) and species by combination (F = 3.73, P = 0.006). At temperatures 1 and 2, N concentrations were lower for S. fuscum and S. balticum than for S. magellanicum and S. cuspidatum, as was also the case in field values. At temperature 3, only the N concentration of S. balticum was lower than that of S. magellanicum. At temperature 4, N concentrations of S. balticum were lower than those of S. magellanicum and S. fuscum (Table 4). Compared to field values, all species showed an increased N concentration with temperature.
Table 4N, P and K concentration (mg g−1) of the capitula. Data are mean values ± SE, pooled within temperature treatment (see Table 1) and within competition treatment. Different letters indicate significant differences between treatments within a species (P < 0.05). There were no significant interactions between temperature and competition treatments. For abbreviations, see Table 3Field valueTemperatureCombinationT1T2T3T4Monofus–balmag–balmag–cusN (mg g−1)S. fuscum6.5 ± 0.28.4 ± 0.2a8.6 ± 0.4a11.3 ± 0.6b12.0 ± 0.7b9.8 ± 0.510.4 ± 0.5S. balticum5.3 ± 0.18.4 ± 0.38.7 ± 0.49.7 ± 0.59.6 ± 0.39.5 ± 0.48.7 ± 0.49.0 ± 0.3S. magellanicum11.1 ± 0.511.7 ± 0.512.6 ± 0.312.8 ± 0.312.9 ± 0.312.4 ± 0.312.3 ± 0.312.7 ± 0.3S. cuspidatum10.0 ± 0.39.8 ± 0.611.3 ± 0.610.5 ± 0.510.8 ± 0.811.5 ± 0.4b9.7 ± 0.4aP (mg g−1) S. fuscum0.39 ± 0.030.19 ± 0.07a0.30 ± 0.02ab0.40 ± 0.03b0.41 ± 0.04b0.31 ± 0.040.34 ± 0.04S. balticum0.36 ± 0.030.13 ± 0.090.26 ± 0.040.29 ± 0.030.29 ± 0.020.32 ± 0.040.22 ± 0.050.19 ± 0.05S. magellanicum0.29 ± 0.010.10 ± 0.06a0.18 ± 0.04ab0.27 ± 0.04ab0.37 ± 0.08b0.26 ± 0.070.21 ± 0.050.21 ± 0.03S. cuspidatum0.31 ± 0.030.10 ± 0.080.18 ± 0.040.23 ± 0.020.26 ± 0.040.24 ± 0.040.15 ± 0.04K (mg g−1)S. fuscum54 ± 0.24.9 ± 0.2a5.5 ± 0.3a7.1 ± 0.3b7.1 ± 0.2b6.4 ± 0.35.9 ± 0.3S. balticum4.7 ± 0.44.7 ± 0.3a5.2 ± 0.2a6.4 ± 0.3b6.5 ± 0.3b5.6 ± 0.35.9 ± 0.35.5 ± 0.3S. magellanicum2.2 ± 0.23.8 ± 0.1a4.7 ± 0.2b6.6 ± 0.2c6.9 ± 0.2c5.6 ± 0.35.3 ± 0.45.4 ± 0.3S. cuspidatum2.2 ± 0.34.5 ± 0.3a5.0 ± 0.2a6.6 ± 0.3b6.9 ± 0.4b6.1 ± 0.3b5.5 ± 0.3aField values (n = 5) are given for comparison. Number of observations for each species for each temperature treatment: S. fuscum and S. cuspidatum, n = 10; S. balticum: n = 14–15; S. magellanicum, n = 15. Number of observations for each species for each combination, n = 19–20
P and K concentrations were affected by temperature (P concentration, F = 9.32, P < 0.001; K concentration, F = 82.77, P < 0.001) and species (P concentration, F = 3.05, P = 0.031; K concentration, F = 3.86, P = 0.011). P and K concentrations were higher at high temperature for all species (Table 4). P-values decreased, compared to field values, while K concentration increased compared to field values.
Evaporation and water content
Water content decreased with temperature treatment (Table 5). Water content was lowest in S. balticum in mixture with S. fuscum. Evaporation increased with temperature and therefore with VPD for all species (Table 5). Evaporation in S. fuscum in both monoculture and mixture was lower than in other species.
Table 5Water content (% volume) at 5 cm depth and evaporation (mm day−1) per temperature treatmenta (see Table 1) and per species combinationb. Data are mean values ± SE. Different letters indicate significant differences between treatments (P < 0.05). There were no significant interactions between temperature and competition treatmentsWater contentEvaporationTemperature 188 ± 2c11.2 ± 0.02a 279 ± 3b21.5 ± 0.03b 360 ± 3a31.7 ± 0.04c 460 ± 3a42.0 ± 0.05dMonoculturesS. fuscum83 ± 5cS. fuscum1.3 ± 0.05aS. balticum66 ± 6bS. balticum1.7 ± 0.08bcS. magellanicum74 ± 4bcS. magellanicum1.8 ± 0.08cS. cuspidatum78 ± 4bcS. cuspidatum1.8 ± 0.08cMixturesS. fuscum74 ± 5bcS. fuscum + S. balticum1.5 ± 0.07aS. balticum49 ± 5aS. magellanicum69 ± 5bS. magellanicum + S. balticum1.6 ± 0.07bS. balticum68 ± 5bS. magellanicum82 ± 5cS. magellanicum + S. cuspidatum1.7 ± 0.08bcS. cuspidatum73 ± 5bcNumber of observations for each temperature treatment: for water content, n = 50; for evaporation, n = 35. Number of observations for each competition treatment: for water content and for evaporation, n = 20
Discussion
Effect of temperature on growth
As expected, all species in monoculture increased height increment with temperature (Fig. 1). All species also showed a looser growth form with higher temperatures, which resulted in lower densities (Table 3). Despite the lower bulk density at higher temperatures, biomass production still increased with temperature for all species (Table 2, Fig. 4). The response of height increment to temperature was about a factor 2 larger than the response of biomass production. Growth of Sphagnum was probably increased by a higher rate of photosynthesis and a higher N availability. Photosynthesis in Sphagnum has been shown to increase with temperature up to an optimum around 20–25°C (Skre and Oechel 1981; Harley et al. 1989). When temperature increased, the nutrient concentrations in Sphagnum were higher (Table 4). Moreover, N and K concentration increased compared to field values (Table 4). As biomass production also increased, N and K uptake must have increased considerably with increasing temperature. No nutrients were added with the rainwater solution, so the higher availability of nutrients must have come from Sphagnum itself and the peat below. Probably the lower Sphagnum parts in the containers decomposed faster when the temperature was higher, making more N and K available for growth. This temperature-induced stimulation of nutrient mineralization is probably larger than it would be in field conditions as the peat soil in the containers is surrounded by warm air on every side, resulting in relatively high soil temperatures in our experiment. However, it can be expected that increased temperature as a result of climate change will also enhance decomposition rates in field situations (Hobbie 1996), thereby increasing nutrient availability for both Sphagnum and vascular plants. The lower N concentrations of S. fuscum and S. balticum compared with S. magellanicum and S. cuspidatum at temperatures 1 and 2 are probably caused by the different sites of origin. In the northern site, the N deposition is much lower (approximately 0.2 g N m−2 year−1) than in the southern site (approximately 0.7 g N m−2 year−1) where S. magellanicum and S. cuspidatum were collected.
In this experiment we provided near optimal growing conditions for Sphagnum with high water level and high humidity, which explains why the Sphagnum plants could grow with a lower bulk density and still keep their capitula moist. However, Sphagnum water content still decreased with an increase in temperature. In field conditions it would probably not have been possible for the Sphagnum plants to change their density so much since it would have led to problems in maintaining the water content of the capitula. The effect of temperature on height increment might therefore also have been less. In a few field studies, no positive or even negative effects of temperature on production were found. However, in these experiments there were other factors besides temperature that could have had a negative effect on biomass production, like drought stress (Hobbie et al. 1999; Weltzin et al. 2001; Gunnarsson et al. 2004) and higher vascular plant cover, which could have resulted in etiolation of the Sphagnum plants and reduced biomass production because of increased shading (Gunnarsson et al. 2004).
In other studies also positive effects of temperature on height growth and production were found for different species, in both greenhouse (Robroek et al. 2007b) and field experiments (Moore 1989; Gerdol 1995; Sonesson et al. 2002; Dorrepaal et al. 2003). In accordance with our hypothesis, Asada et al. (2003) suggested that Sphagnum species respond positively to increased temperature and that hollow and lawn species are more sensitive to temperature than hummock species. This, however, does not correspond with the low response of S. cuspidatum to temperature in our experiment. Dorrepaal et al. (2003) also found a decrease in bulk density with increased temperature. Since the response of height increment and bulk density to temperature were in opposite directions, the dry matter production of S. fuscum did not show a significant increase with temperature. Our relatively high height increment and low density of S. fuscum compared to the values of Dorrepaal et al. (2003) can probably be explained by the much higher water levels in our experiment. Dorrepaal et al. (2003) used water levels of −20 to −40 cm below moss surface during their measurements. However, the Sphagnum densities we measured (Table 3) agreed quite well with densities from other studies (Lindholm and Vasander 1990; Moore et al. 1998; Asada et al. 2003).
From our results, we conclude that the height increment and biomass production of all Sphagnum species in bogs can increase with an increase in temperature. However, the literature shows us that, particularly under field conditions, this potential response may not be realized in instances of competition from vascular plants, drought stress or extreme temperature increases.
Effect of temperature on competition
We hypothesized that increased temperature will have a positive effect on competitive abilities of S. fuscum and S. magellanicum. This hypothesis was confirmed in the competition with S. balticum, since the height increment and biomass production of S. balticum at the highest temperature treatment were no longer larger than those of S. fuscum and S. magellanicum (Figs. 2, 4). However, S. balticum still increased its cover at the expense of S. fuscum and S. magellanicum in all mixtures (Fig. 3a, b). This could be expected as the water level we used was relatively high and in the range of the natural habitat of these species. These results correspond to the findings from a field experiment of Rydin (1986), who found an expansion of S. balticum at the expense of S. fuscum at a water level of −1 cm. At water levels of −5 and −10 cm, he found a small expansion of S. balticum, but at a water level of −15 cm S. fuscum showed large expansion.
In agreement with the hypothesis, the difference in height increment and biomass production between S. fuscum and S. balticum disappeared as temperature increased (Figs. 2a, 4a). S. fuscum kept increasing height increment with temperature, but S. balticum already reached maximum height growth at temperature 2, which is comparable to the summer temperature in the site of origin of these species. Also, the expansion in cover became lower for S. balticum at temperature 4 (Fig. 3a). As a result, the difference in biomass production between S. fuscum and S. balticum slowly decreased with an increase in temperature until there was no significant difference at the highest temperature. Apparently, the hummock species S. fuscum is better able to profit from a high increase in temperature than S. balticum, even at relatively high water levels. This is confirmed by the stepwise regression analysis which shows that biomass production of S. fuscum is correlated most to temperature, and biomass production of S. balticum to water content. As could be expected, S. fuscum as a hummock species has a higher water content than S. balticum, also at higher temperatures (Table 5), and therefore can profit more from increased temperature, because water does not become limiting for growth. S. fuscum also seems to be the better competitor for nutrients. The N and P concentrations in S. fuscum tended to be higher in the mixtures than in the monocultures, whereas in S. balticum the opposite was the case (Table 4). Indeed, S. fuscum is known for its high N uptake rate (Jauhiainen et al. 1998). Our results show that S. balticum loses competitive strength with increasing temperature. With a slight increase in temperature in northern bogs, S. balticum may remain the stronger competitor at high water levels, but at higher temperature increases, S. fuscum will gain a competitive advantage over S. balticum, also because increased temperature may lead to lower water tables in bogs. Recent climate change simulation models predict an increase of 2.5°C in summer temperature in northern Europe, with increasing precipitation in northern Scandinavia (Christensen et al. 2007). This limited rise in temperature, almost similar to the increase from temperature 2 to 3, would not affect competition between S. balticum and S. fuscum very strongly. However, the effect of a predicted increase in winter temperature of 5.0°C (Christensen et al. 2007) could shift the competitive balance between S. balticum and S. fuscum further, because increased snow cover and spring temperature have been shown to increase S. fuscum production (Dorrepaal et al. 2003).
For S. magellanicum and S. cuspidatum, temperature 3 is comparable to the summer temperature in their site of origin. There was no effect of a temperature increase from temperature 3 to 4 on biomass production and relative performance of the species. This implies that with the predicted increase in temperature of 2.5°C (Christensen et al. 2007), the competitive balance between S. magellanicum and S. cuspidatum will remain unchanged.
The mixtures of S. balticum and S. magellanicum show the largest difference in height increment and biomass production at temperature 2, which is comparable to the summer temperature in the site of origin of S. balticum. Also the expansion in cover of S. balticum was highest at this temperature. When temperature increases, the difference in height growth and biomass production became smaller and then disappeared in mixtures, whereas in monocultures the difference in biomass production between species remained. This implies that S. balticum as a northern species can enhance its production with an increase in temperature as long as it grows in monocultures. If S. magellanicum expanded its distribution further to the north as a result of global warming, it would be a strong competitor for S. balticum, thereby reducing S. balticum production. Gunnarsson et al. (2004) also showed that S. balticum performs less well under competition with increased temperatures. They performed a competition experiment in a poor fen, close to the site of origin of the S. balticum material. They found that when Sphagnum papillosum was transplanted to an area with S. balticum, S. papillosum decreased in area by 30%. However, when temperature was increased by 3.6°C, S. papillosum increased by 42%. This treatment is comparable to the increase from temperature 2 to temperature 3 in our experiment but with lower water tables, ranging from 5 to 17 cm under the moss surface.
Generally, we conclude from our experiment that an increase in temperature can favour hummock and lawn species compared to hollow species. This corresponds to the findings of Mauquoy et al. (2002), who showed from peat core analyses that in periods with lower temperature, due to decreased solar activity, there was a shift in representation from lawn and hummock species to hollow species in ombrotrophic mires in Denmark and the UK.
In conclusion, our findings suggest that production rates can increase and that Sphagnum species’ abundances can shift in response to global warming, particularly at northern sites. There, hollow species such as S. balticum will lose competitive strength relative to hummock species such as S. fuscum and southern species such as S. magellanicum. What the consequences for the C balance of bog ecosystems will be depends not only on the production rates, but also on decomposition. In general, decomposition rates also increase with temperature and increased N availability (Hobbie 1996; Limpens and Berendse 2003) and hummock species decompose slower than hollow species (Rochefort et al. 1990; Johnson and Damman 1993; Limpens and Berendse 2003), but virtually nothing is known about the temperature sensitivity of decomposition of bog plant species.

bog
global warming
greenhouse
cover change
species composition


Fractional anisotropy in white matter tracts of very-low-birth-weight infants

Background Advances in neonatal intensive care have not yet reduced the high incidence of neurodevelopmental disability among very-low-birth-weight (VLBW) infants. As neurological deficits are related to white-matter injury, early detection is important. Diffusion tensor imaging (DTI) could be an excellent tool for assessment of white-matter injury.
Introduction
The last decade has seen improved survival for very-low-birth-weight (VLBW) preterm infants [1, 2]. The survivors, however, still show a high incidence of neurodevelopmental disability, despite advances in fetal and neonatal intensive care [3–5]. These neurological deficits are usually related to white-matter injury [6, 7]. Thus early detection of abnormal white-matter maturation is important in the design of preventive, protective, and rehabilitative strategies for the management of the critically ill newborns [8, 9].
The clinical evaluation of these infants may not provide adequate diagnostic or prognostic information on white-matter injury. Various neuroimaging techniques have become available, however, that may be of help. Cranial US is such a technique used in premature infants, but it is not as sensitive as MR imaging, which shows better soft-tissue contrast [10]. Yet, conventional T1-weighted (T1-W) and T2-weighted (T2-W) MR imaging sequences also have limited value in the evaluation of the preterm brain, as they do not allow visualization of specific white-matter tracts before the onset of myelination. Most white-matter tracts of the premature cerebrum are unmyelinated except for a few pathways, e.g. the pyramidal tract that matures early as the infant approaches term-equivalent age [11, 12].
Diffusion tensor imaging (DTI) is unique in its ability to visualize and quantify white-matter tracts in the human brain. It is superior to T1-W and T2-W imaging in detecting unmyelinated or premyelinated fibre tracts [13] and, therefore, likewise in assessing the microstructural organization of the developing white matter. DTI anisotropy measurements offer great potential in the study of white-matter damage in VLBW infants. So far, however, the clinical use of this technique is restricted by the lack of normal reference values for VLBW infants. Although there are reports on fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in preterm infants, only four groups have reported values for infants of gestational age less than 32 weeks without brain injury (Table 1). Each of the populations studied included no more than four infants without white-matter damage on conventional imaging, scanned within days after birth and gestational age less than 32 weeks [14–17]. Because the sizes and shapes of the regions of interest (ROIs) in these studies differ, comparison between the studies is difficult. We therefore set up a retrospective study aimed at providing reference values for the clinical interpretation of DTI images in VLBW infants.
Table 1Overview of relevant literatureReferenceGestational age (weeks)Scan weekNo. of patientsNo. with gestational age <32 weeksMR field strength (T)ROI14<3728–4327<51.5FTa1524–3628–3917<51.5Manual1624–3628–3914<51.5Manual1726–3028–406<51.5ManualaROI placement with fibre tracking.
Materials and methods
Subjects
The Erasmus MC Ethical Review Board approved the study and written informed parental consent was obtained for each subject. The images used in this study had been obtained within the framework of a study in which premature infants of different gestational ages underwent serial conventional and DTI acquisitions to evaluate white-matter development. The inclusion criteria for our study were birth at gestational age 25–32 weeks, no evidence of white-matter injury on conventional MRI and scanned within 4 days of birth. Developmental outcome assessed at age 1–3 years needed to be normal. Gestational age was calculated from the mother’s last menstrual period or estimated from early US (<18 weeks of pregnancy). Exclusion criteria were intraventricular haemorrhage, ventriculomegaly, congenital infection, brain malformation or a multiple congenital anomaly syndrome. Furthermore, preterm infants whose images showed severe motion degradation were excluded since evaluation of these scans was not possible. During the 25 months of the study period (March 2004 to April 2006), 41 infants were scanned and 32 met our study criteria. Four MR examinations were excluded due to severe motion artefacts, so 28 patients were included.
Neurodevelopment monitoring
The infants’ hospital charts were reviewed for neurodevelopmental outcome. They had all been neurologically assessed at 3, 6, 12 and 24 months, and Denver scores were used to monitor neurodevelopment [18]. At 24 months the Bayley scales of infant development, second edition (BSID-II) had also been applied [19]. All patients had shown normal neurodevelopment according to the most recent examination.
Conventional MR imaging
Images were acquired using standard scanning protocols. All imaging was performed on a 1.5-T GE EchoSpeed scanner (GE Medical Systems, Milwaukee, Wis.). The imaging protocol included T1-W (spin echo, TR/TE 500/11 ms) and T2-W sequences (spin echo, TR/TE 3,000/120 ms) with a slice thickness of 4 mm and 0.4 mm gap. For DTI an echoplanar sequence with diffusion gradients (b = 1,000 s/mm2) applied in 25 non-collinear directions was used with a slice thickness of 3 mm and no gap. An average of 20 slices was recorded within 4 min using TR/TE 9,150/98–91 ms. The FOV was 20 cm, the scan matrix 128×128 and the reconstruction matrix 256×256.
All patients were scanned using an MR-compatible incubator with a specialized high-sensitivity neonatal head coil (Lammers Medical Technology, Lubeck, Germany) that allowed DTI imaging at high spatial resolution and high signal-to-noise ratio (SNR). The incubator provided controlled temperature and humidity as well as MR-compatible pulse oximetry and ventilation. This set-up allowed imaging in this most vulnerable patient population in a stable and safe microenvironment [20–22]. We used mouldable earplugs and neonatal earmuffs to reduce the noise. No sedation was given. Pads around the infant’s head kept movement to a minimum.
Diffusion tensor postprocessing
Diffusion tensor images were transferred to a GE Advantage Windows workstation (General Electric Medical Systems, Milwaukee, Wis.) for postprocessing using Functool 2000 software (General Electric). DTI measures the diffusion of water in each voxel and the extent to which water diffuses in particular directions as a result of the microstructural characteristics of the tissue imaged. High anisotropy indicates that the magnitude of diffusion is very unequal in different directions. The complex nature of anisotropic diffusion in the brain has been described by a diffusion tensor, which contains information about the magnitude of diffusion in different directions. Each tensor contains a set of three eigenvalues, which are related to the major, intermediate, and minor axes of a diffusion ellipsoid. The principal eigenvector (λ1) specifies the direction in which water diffusion is greatest. FA measures the fraction of the magnitude of the diffusion tensor that can be ascribed to anisotropic diffusion [23–25]. For isotropic diffusion (λ1 = λ2 = λ3), FA is zero, and in the case where there is a strongly preferred direction of diffusion (λ1>>λ2 = λ3), FA approaches a value of one. The colour maps were based on major eigenvector orientation with red representing right–left, green representing anteroposterior, and blue representing superoinferior anatomical directions.
The tracts selected for quantization in the study included commissural tracts (corpus callosum: splenium and genu), projection tracts including those of the posterior limb of the internal capsule (PLIC), the anterior limb of the internal capsule (ALIC) and the optic radiation (OR), and association tracts (external capsule, EC).
Regions of interest
DTI measurements were taken from multiple ROIs positioned bilaterally within individual white-matter tracts. For the placement we used standard-size, round-shaped 16-pixel ROIs. To optimize our ROI placement we first detected the patient scan slice that represented slice “O” of the atlas of Wakana et al. [26]. We then placed the ROI, combining the FA, ADC and colour map to verify the right location. When the two researchers both agreed on the position, the ROI was used as a seed point to perform fibre tracking (minimum length 10 mm, minimum anisotropy 0.10). We compared the fibres that were visualized with the fibre bundles described in the atlas of Wakana et al. for verification (Figs. 1, 2 and 3). We then looked for the maximum pixel value within the ROI (Figs. 4 and 5). Two researchers experienced in neonatal DTI achieved consensus on ROI placement and measurements.
Fig. 1Example of an FA map (gestational age 28 weeks) on which the ROIs are placedFig. 2Confirmation of ROI placement on the colour map (gestational age 28 weeks)Fig. 3Fibre tracking was performed in each of the ROIs to confirm the correct location. This is an example showing the corticospinal tracts (gestational age 28 weeks)Fig. 4Delineation of the corpus callosum using free-hand ROI placement on an FA map (gestational age 28 weeks)Fig. 5Automated calculation of the maximum FA pixel value within the ROI on an FA map (gestational age 28 weeks)
Statistical analysis
The relationship between FA of the white matter tracts and gestational age was analysed by correlation analysis (Pearson product moment correlation, SPSS 13.0.1). Tract comparison was done using one-way analysis of variance (ANOVA).
Results
Patient characteristics
Gestational ages at birth ranged from 26 to 32 weeks (mean 28 weeks 5 days). Mean weight at birth was 1,148 g and mean head circumference was 26.4 cm. All patients had shown normal neurodevelopment as defined by the Denver or Bayley scoring system according to the most recent examination.
FA and ADC of ROIs of standard pixel size
We plotted the average FA and ADC values of 16-pixel ROIs of the different white-matter tracts against gestational age. No statistically significant differences based on a two-tailed paired Student’s t-test (at a significance level of P<0.05) were found comparing FA and ADC values between the left and right hemispheres in each subject. Therefore, the values obtained from the left and right were averaged to obtain the mean FA and ADC of the different ROIs. We found a significant correlation between gestational age and FA of the PLIC (r = 0.495, P<0.01; Fig. 6). No significant correlations were found for the other tracts (Table 2). We found no correlation between average ADC values and gestational age in the studied tracts (Table 2).
Fig. 6Average FA values of 16-pixel ROIs of the PLICTable 2Tract statistics (FA and ADC mean values and standard deviations) and significant differences in FA and ADC between tractsStructureFAADCMean (SD)Tracts showing significant differences (P<0.05)Mean (SD)Tracts showing significant differences (P<0.05)Posterior limb of internal capsule0.349 (0.028)a, b, c1.09 (0.05)l, m, n, o, pAnterior limb of internal capsule0.242 (0.033)a, d, e, f1.27 (0.091)lExternal capsule0.175 (0.188)b, g, h, i1.29 (0.097)mOptic radiation0.270 (0.042)g, j, k1.30 (0.126)nCorpus callosum (genu)0.42 (0.048)d, e, h, j1.24 (0.111)oCorpus callosum (splenium)0.442 (0.056)c, f, i, k1.27 (0.131)p
Maximum FA values of the PLIC
The maximum FA values of the ROI were plotted against gestational age and also showed a significant correlation between gestational age and FA of the PLIC (r = 0.569, P<0.01; Fig. 7). We saw no other significant correlations between FA and gestational age. Compared with standard-size ROI mean FA values of the PLIC, the maximum values were a mean of 0.05 higher.
Fig. 7Maximum FA ROI values of the PLIC
Comparison between tracts
DTI values varied between white-matter structures (Table 2). FA was highest in the commissural tracts of the corpus callosum (splenium>genu) and deep projection tracts (internal capsule). FA was lowest in association tracts (external capsule).
Discussion
Our aim was to provide clinicians with reference values for the evaluation of diffusion tensor images of white-matter tracts in VLBW infants. A literature search identified four similar studies. Comparison with these studies seems irrelevant as each included no more than four infants evaluated below a gestational age of 32 weeks within the first days of life. We were able to study scans of 28 VLBW infants without white-matter damage within the first 4 days of life. We found a statistically significant correlation between gestational age and FA of the PLIC. Differences were observed between white-matter tracts: FA was highest in commissural, followed by deep projection and association tracts. Others have found the same hierarchy in the perinatal brain [16] and in fully myelinated adult tracts [27].
Different anisotropy indexes can be used to study the anisotropy of white-matter tracts: FA, relative anisotropy (RA), axial anisotropy etc. We focused on FA, the most frequently used anisotropy index. FA has a high sensitivity for studying anisotropy in white-matter tracts [16]; it has a higher SNR than RA for anisotropic regions [28, 29]. Previous studies have shown that FA is the most sensitive and significant discriminating DTI parameter in pair-wise comparisons between different tracts in premature infants [16]. In most tracts FA increases significantly by the week, whereas weekly decreases in ADC values are smaller and less discriminative in most regions [16]. There are a growing number of reports of FA values of injured tracts [30–32]. Nevertheless, we should realize that FA is only one of the functions that describe the diffusion tensor. Although aberrant FA values seem to be a sensitive detector of abnormal tissue one could also use the relative magnitudes of the three principal eigenvectors to describe diffusion.
What determines anisotropy in white-matter tracts? The value of the anisotropic index is determined by size, shape and composition of physical obstructions, as well as the space between them. Myelin, fast axonal transport, the axonal cytoskeleton (neurofilaments and microtubules), and local susceptibility gradients do not seem to have any major impact on anisotropic water diffusion [26, 33]. Indeed, intact membranes are thought to be the main contributing factor to anisotropy. The increasing anisotropy of white matter takes place before the histological appearance of myelin [15]. This increase has been attributed to the ‘premyelinating state’ [13, 34]. The corpus callosum, with a coherent parallel organization, has the highest FA values. Callosal fibre tracts, however, do not show a significant increase in FA with increasing gestational age, as the PLIC does. This might be due to the fact that myelination progresses more slowly in the callosal fibres than in the projection fibres at this age.
During development a decrease in ADC values of the white-matter tracts is expected. We found no correlation between average ADC values and gestational age in the studied tracts. When looking at the available data reported previously we only saw the ADC values decrease significantly with gestational age when the ADC values of the infants older then 35 weeks were included. The fact that we could not find any significant correlation could be due to the limited number of infants scanned. The alternative is that at an earlier gestational age there is no significant decrease in ADC in the studied tracts.
Studying DTI parameters of the white-matter tracts of VLBW infants is challenging for many reasons. One of these challenges is to determine a standard for the size and shape of the ROIs. A ROI is a controlled identification of a given area of an image for numerical analysis and the area of anatomy being scanned that is of particular importance in the image. Different authors have used different ways to set their ROIs. The reason we compared two techniques was to achieve better reproducibility. Maximum values (the maximum pixel value within a ROI) might be an alternative in which the value is given by the software. However, theoretically there is a bigger change of artefacts. Fibre tracking, colour maps and ADC maps are established but time-consuming techniques for the verification of tracts. We trust that automatic verification will become common practice in the future. A possible solution for ROI comparisons between researchers is the use of a neonatal brain atlas coordinate system. Individual brain images could then be transformed into a common coordinate space and the ROIs could be placed at specific topographic coordinates. Our research group is currently looking into this option.
Another serious challenge is the SNR and spatial resolution constraints due to the very low anisotropy of premyelinating white matter and the tiny size of white-matter tracts in premature newborns. Using a custom-made MR-compatible incubator with a high-sensitivity neonatal head coil that improved image quality, spatial resolution and patient comfort, we were able to overcome this challenge.
In this retrospective study a b value of 1,000 s/mm2 was used to allow comparisons between early and later scans at different ages. We realize a lower b value would be optimal because the ADC value in neonatal white matter is higher than that of more mature brains. The optimal b value can be calculated as indicated by Jones et al. [35].
Like all VLBW infants discharged from our NICU, our study patients were routinely seen by trained paediatricians and by paediatric physical therapists at the outpatient department for neurodevelopmental follow-up. Neurodevelopmental outcome was defined according to the most recent neurological examination and Denver and Bayley scores. The children’s ages at the most recent assessments varied, making the results difficult to compare; also Denver and Bayley scores are limited in their prognostic value below the age of 2 years.
Better understanding of normal preterm white matter development is essential to encourage the use of DTI for evaluation and treatment of white-matter injury. Early diagnosis of white-matter abnormalities means that early intervention might be possible. We are exploring the feasibility of perinatal brain repair, and new MR imaging techniques such as DTI will enable us to improve our understanding of how the developing brain responds to our interventions.
Conclusion
Our study gives anisotropy values for VLBW infants with normal outcome that can be used as reference values. This work adds to our understanding of normal preterm white-matter development.

fractional anisotropy
diffusion tensor imaging
prematurity
mri


Iron and thrombosis

Although essential for cell physiology, an increase or depletion of body iron has harmful effects on health. Apart from iron deficiency anemia and iron overload-related organ tissue damage, there are increasing evidences that body iron status is implicated in atherosclerotic cardiovascular diseases. The hypothesis formulated in 1981 that iron depletion may protect against cardiovascular events is intriguing and has generated a significant debate in the last two decades. Indeed, to study this phenomenon, several investigators have tried to design appropriate experimental and clinical studies and to identify useful biochemical and genetic markers of iron status. The results of the literature on the effect of iron deficiency and overload on vascular health are critically reviewed in this study from a pathogenic and clinical point of view.
Introduction
Iron is an essential nutrient for living cells because of its role as a cofactor for enzymes in the mitochondrial respiration chain, in the DNA synthesis, and being the central molecule for binding and transport of oxygen by hemoglobin and myoglobin.
While the lack of iron leads to growth arrest and anemia, an increased accumulation of this metal is associated with toxic radical formation and progressive tissue damage. It is interesting to note that both iron deficiency and excess have been associated with an increased risk of developing thromboembolic events [1–7].
This review will analyze, from a clinical and pathogenic point of view, the existing literature data on the relationship between iron and arterial and venous thrombosis.
Iron deficiency and thrombosis
There are several reports in the literature on thrombotic complications in iron-deficient children and adults [8–26]. Secondary thrombocytosis has been implicated in many cases. Indeed, iron deficiency is a cause of reactive thrombocytosis, usually mild [27]. For instance, within a study group of children with iron deficiency, reactive thrombocytosis was found in up to one-third of them [28].
Nagai et al. [29] reported a case of severe iron deficiency with marked thrombocytosis (1,020 × 109/l) that was complicated by central retinal vein occlusion. By contrast, Kinoshita et al. [26] described two cases of cerebral venous sinus thrombosis associated with iron deficiency and normal platelet count. Hartfield et al. [13] reported six children with iron deficiency who developed an ischemic stroke or venous thrombosis. Four of them had a concomitant thrombocytosis. In a prospective case–control study, Stolz et al. [30] found that severe anemia, along with thrombophilia and hypercholesterolemia, were independent risk factors for cerebral venous thrombosis.
The mechanisms causing reactive thrombocytosis in iron deficiency anemia are not completely understood. Iron is an important regulator of thrombopoiesis [31, 32]. Whereas normal iron levels are required to prevent thrombocytosis by inhibiting thrombopoiesis, a minimum amount of iron is required to maintain platelet production. Thus, while thrombocytosis is usually associated with a mild iron deficiency and is the result of a lack of inhibition of thrombopoiesis, a severe defect of this metal may be accompanied by thrombocytopenia. However, studies on thrombopoietic cytokines failed to show any effect on reactive thrombocytosis in iron deficiency [27]. For instance, Akan et al. [33] assayed the serum levels of thrombopoietin, erythropoietin, leukemia inhibitor factor, IL-6, and IL-11 in patients with iron-deficient anemia with or without elevated platelet count. Only erythropoietin level was elevated, correlated with thrombocytosis, and decreased with iron replacement. The other cytokines remained unchanged after therapy, suggesting that they probably do not play any significant role in iron deficiency-associated reactive thrombocytosis. Recently, Bilic and Bilic reported that the amino acid sequence homology of thrombopoietin and erythropoietin may explain the thrombocytosis in children with iron deficiency anemia [34]. By contrast, two other reports suggested that the relationship between iron deficiency and reactive thrombocytosis is more complex than a mere consequence of a crossreactivity between erythropoietin and thrombopoietin [35, 36]. In addition to the increased thrombotic risk associated with high platelet count, other authors have suggested that the decrease in antioxidant defense in iron deficiency anemia may cause increased oxidant stress, which in turn may result in a tendency toward platelet aggregation [37]. Thus, the abnormal platelet count and function observed in iron deficiency anemia could act synergistically to promote thrombus formation, especially in the setting of an underlying atherosclerotic disease [23].
However, as not all cases of iron-related thrombotic events occur in patients with concomitant high platelet count [13, 26], other pathogenic mechanisms have been proposed in these last years. Thus, iron deficiency may contribute to a hypercoagulable state by affecting blood flow patterns within the vessels because of reduced deformability and increased viscosity of microcytic red blood cells [13]. Furthermore, anemic hypoxia secondary to iron deficiency could precipitate situations of increased metabolic stress (i.e., infections) in particularly vulnerable areas of the brain supplied by end arteries, such as the basal ganglia, thalamus, and hypothalamus [38]. This phenomenon could explain the association between iron-deficient anemia and reversible focal deficits and stroke found by some authors [1, 13, 39, 40].
Iron overload and thrombosis
Accumulation of iron in excess of physiologic requirements has been implicated in the development of several chronic illnesses, including cardiovascular diseases [7]. As previously reported, iron is a prooxidant cofactor associated with an increased production of hydroxyl radical in cardiovascular tissues and increased progression of atherosclerosis in experimental models [41–44]. Indeed, in an experimental mouse thrombosis model, a moderate iron overload markedly accelerated thrombus formation, impaired vasoreactivity, and enhanced the production of reactive oxygen species and systemic markers of oxidative stress [41]. It is interesting to note that the administration of dl-cysteine, a reactive oxygen species scavenger, completely abrogated the iron load-induced thrombus formation thus corroborating the hypothesis that iron accelerates thrombosis through a prooxidant mechanism. Similarly, laboratory investigations have demonstrated iron-dependent generation of reactive oxygen species in endothelial cell cultures and increased aortic atherosclerosis in the apolipoprotein E-deficient mice and cholesterol-fed rabbits with increased iron intake [42–44].
The research in this field has focused on the evaluation of the impact of iron depletion and iron overload on cardiovascular outcomes. Sullivan first postulated in 1981 the “iron hypothesis” by which the chronic iron depletion has a protective effect against ischemic heart disease and may account for the reduced risk of cardiovascular events in menstruating women [45–47]. Basing on these observations, some investigators have studied the effect of serial blood donations on the coronary heart disease risk, but their results were inconsistent [48–53]. However, an important support to the hypothesis of a potential link between blood donation and reduced cardiovascular risk came from a recent study conducted by Zheng et al. [54] who found that high-frequency blood donors had decreased serum ferritin levels, a marker of body iron stores; decreased serum 3-nitrotyrosine levels, a marker of oxidative stress; and greater flow-mediated dilation in the brachial artery, a marker of vascular function. It is interesting to note that in a clinical study, the iron chelation with deferoxamine improved endothelial function in patients with coronary artery disease [55]. By contrast, in a multicenter, randomized controlled trial (the iron [Fe] and Atherosclerosis Study [FeAST]) on 1,277 patients with symptomatic peripheral arterial disease, the reduction of body iron stores by phlebotomy did not significantly decrease all-cause mortality or death plus nonfatal myocardial infarction and stroke [56]. Similarly, in a prospective analysis of the second National Health and Nutrition Examination Study (NHANES II), Sempos et al. [57] observed either no association (in Caucasian men) or a possible nonsignificant increased risk (in Caucasian women) of cardiovascular or coronary heart disease death among individuals with low ferritin concentrations.
On the other hand, the association between biochemical markers of body iron load and the risk of developing cardiovascular disease have been investigated by several studies [7, 58–72]. In the Kuopio Ischemic Heart Disease Risk Factor Study (KIHD), serum ferritin levels were found to be one of the strongest risk factors for acute myocardial infarction among Finnish men [61]. Similar findings were reported from a Canadian study [65] that observed an increased risk of myocardial infarction among subjects in the highest serum iron category and from the Bruneck study [64] in which a positive association between serum ferritin levels and ultrasound measures of progression of carotid atherosclerosis over a 5-year follow-up period was found. A relationship between serum ferritin levels and carotid atherosclerosis was also identified by a recent study conducted by Wolff et al. [71]. Haidari et al. [60] observed a significant correlation between serum ferritin levels and risk of coronary heart disease in male Iranian patients. However, a number of epidemiological studies did not find an association between iron status and coronary artery disease [61, 69, 70, 72]. For instance, Bozzini et al. [61] found that the mean serum ferritin concentrations were slightly higher in coronary heart disease patients than in controls, but this difference disappeared after adjusting for sex and C-reactive protein.
The 1996 discovery of HFE gene mutations responsible for most cases of hereditary hemochromatosis has led to the use of genetic markers of iron overload, which are not influenced by external factors such as inflammation, in epidemiologic studies. Thus, several authors have investigated in recent years the relationship between C282Y and H63D mutations in the HFE gene and the risk of cardiovascular diseases [73–88]. Three prospective population-based studies have reported an association between heterozygotes and vascular events [75–77].
The first study was from a subgroup of the original Finnish KIHD cohort [75]. Of 68 individuals, 8 (11.8%) were diagnosed with acute myocardial infarction, and of 1,150 noncoronary heart disease participants, 77 (6.7%) were carriers of C282Y. The crude relative risk of myocardial infarction was 2.0 (95%CI = 0.9–4.1) and the adjusted relative risk was 2.3 (95%CI = 1.1–4.8). In a cohort of 12,239 Dutch postmenopausal women, the C282Y carrier status was assessed among 531 women who died of cardiovascular disease and 555 randomly selected women who did not die of cardiovascular disease [76]. This study reported a relative risk of 1.6 (95%CI = 1.1–2.4) for total cardiovascular death. Finally, in the United States Atherosclerosis Risk in Communities (ARIC) study [77], a C282Y carrier frequency of 9.9% among 243 coronary heart disease cases and 6.1% among 535 controls was reported. The crude relative risk of coronary heart disease associated with C282Y carrier status was 1.6 (95%CI = 0.9–3.0) and was 2.7 (95%CI = 1.2–6.0) after being controlled for other risk factors. To support of these findings, Gaenzer et al. [78] found an association between increased iron stores and impaired endothelial function (measured as endothelium-dependent dilation and intima-media thickness) in patients homozygous for C282Y mutation. Iron-depletion therapy normalized the endothelial function in such patients thus reducing the increased risk of cardiovascular events.
However, the majority of the studies disagreed with these results [61, 79–89]. Indeed, Bozzini et al. [61] found a similar rate of carriers of C282Y mutation among patients with coronary atherosclerotic disease and controls. In a case–control study on 1,098 subjects, Rossi et al. [80] found that C282Y mutation was not a predictor of asymptomatic carotid atherosclerosis. Franco et al. [81] reported that the HFE genes were not associated with coronary or peripheral atherosclerosis in patients aged less than 50 years. Similarly, in the West of Scotland Coronary Prevention Study (WOSCOPS), Gunn et al. [86] found that the presence of a C282Y mutation in the HFE gene did not predict the occurrence of coronary events over a mean follow-up of 4.9 years. It is interesting to note that Yunker et al. [89] analyzed the relationship between biochemical and genetic markers of iron overload and carotid intima-media thickness and brachial flow-mediated vasodilation by high-resolution ultrasound in 907 males, but neither ferritin nor hemochromatosis genotype were related to brachial endothelial function and carotid atherosclerosis. In addition, a recent large study from Denmark found no increased risk of coronary heart disease among carriers of the C282Y mutation or individuals who had compound heterozygosity for the C282Y and H63D mutations [79].
Other investigation have focused on the association between genetic markers of iron overload and idiopathic dilated cardiomyopathy and stroke, but their results were conflicting [90–94].
Finally, some authors have suggested that HFE C282Y could interact with other predisposing factors for venous thromboembolism, such as factor V Leiden, thus exacerbating their prothrombotic effect [95].
Table 1 summarizes the most important studies on the association between genetic markers of iron overload and cardiovascular diseases.
Table 1Summary of the most important studies on the association between HFE gene mutations (C282Y and H63D) and the risk of cardiovascular diseasesAuthors [reference]Study designPopulationResultsTuomainen et al. [75]Prospective1,150 individualsC282Y heterozygosity is associated with a 2.3 RR for AMI compared with noncarriersRoest et al. [76]Prospective12,239 postmenopausal womenC282Y heterozygosity is associated with a 1.6 RR for TCD compared with noncarriersRasmussen et al. [77]Prospective243 CHD cases and 535 controlsC282Y heterozygosity is associated with a 2.7 RR for CHT compared with noncarriersGaenzer et al. [78]Case–control41 C282Y/C282Y cases and 51 controlsC282Y homozygosity is associated with impaired endothelial functionBozzini et al. [61]Case–control546 CHD cases and 303 controlsC282Y mutation is not associated with CHDRossi et al. [80]Case–control1,098 subjectsC282Y mutation is not a risk factor for asymptomatic carotid atherosclerosisFranco et al. [81]Case–control256 CHD cases and 272 controlsC282Y and H63D mutations are not associated with CHDEllervik et al. [79]Prospective9,178 individualsC282Y and H63D mutations are not associated with CHDCase–control2,441 CHD and 1,113 AMI cases vs 8,080 controlsC282Y and H63D mutations are not associated with CHDGunn et al. [86]Case–control482 CHD cases and 1,104 controlsC282Y mutation is not associated with CHDCampbell et al. [88]Case–control924 AMI cases and 1,029 controlsC282Y mutation is not associated with CHDYunker et al. [89]Case–control907 individualsHFE genotype is not related to brachial endothelial function and carotid atherosclerosisAMI: acute myocardial infarction, CHD: coronary heart disease, RR: relative risk, TCD: total cardiovascular death
Conclusions
It is interesting to note that although with different pathogenic mechanisms, both iron deficiency and overload have been associated with an increased thrombotic risk in experimental and clinical studies.
However, several aspects need to be still elucidated in this field. In particular, large prospective controlled trials are needed to elucidate the role of genetic markers of iron stores and the impact of long-term iron depletion on morbidity and mortality from cardiovascular events.