Predicting germination capacity of Pinus sylvestris ...

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Predicting germination capacity of Pinus sylvestris and Picea abies seeds using temperature data from weather stations

Can. J. For. Res. Downloaded from www.nrcresearchpress.com by SKOGFORSK LIBRARY on 06/01/14 For personal use only.

Curt Almqvist, Urban Bergsten, Lennart Bondesson, and Urban Eriksson

Abstract: In Fennoscandia, both Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.) often fail to produce mature seed, especially in the northern parts of their range. Therefore, cone and seed crop predictions are of major strategic importance for maintaining sustainable multipurpose forestry. We present functions for predicting germination capacity of Pinus sylvestris and Picea abies seed over a wide geographic area. The functions are based on germination analyses for 1297 Pinus sylvestris and 597 Picea abies natural stands in Sweden during 1971–1994. Meteorological data from 71 weather stations were used to calculate heat sums with threshold values from 4 to 10°C and two durations of growing season (ending August 31 or September 30). Logistic regression was utilised for parameter estimates. Accumulated heat sum (threshold 5°C) from start of growing season until August 31 in combination with number of days from estimated time of fertilisation until approximate time for embryo growth cessation gave the best function. The function shows that Picea abies has lower temperature requirements for producing mature seed than Pinus sylvestris. A germination capacity of 95% is reached at a heat sum of 875 degree-days for Picea abies and at 975 degree-days for Pinus sylvestris. Résumé : En Fennoscandie, le pin sylvestre (Pinus sylvestris L.) et l’épinette de Norvège (Picea abies (L.) Karst.) ne réussissent pas souvent à produire des graines matures, surtout dans la zone septentrionale de leur aire de distribution. Par conséquent, la capacité de prévoir la production de cônes et de graines est d’une importance stratégique majeure pour maintenir l’ensemble des ressources forestières de façon durable. Nous présentons des fonctions qui permettent de prédire la faculté germinative des graines de Pinus sylvestris et de Picea abies partout dans une vaste zone géographique. Ces fonctions sont basées sur des analyses de germination effectuées dans 1297 peuplements naturels de Pinus sylvestris et de 597 peuplements naturels de Picea abies, en Suède, entre 1971 et 1994. Les données de 71 stations météorologiques ont été utilisées pour calculer l’accumulation de chaleur à des seuils de 4 à 10°C et pour deux longueurs de saison de croissance (jusqu’au 31 août ou jusqu’au 30 septembre). L’analyse de régression logistique a été utilisée pour estimer les paramètres. La quantité de chaleur accumulée (seuil de 5°C) du début de la saison de croissance jusqu’au 31 août, combinée au nombre de jours entre le moment estimé de la fertilisation jusqu’au moment approximatif où l’embryon cesse de croître, donnait la meilleure fonction. Cette fonction montre que le Picea abies requiert une température plus basse pour la production de graines matures que le Pinus sylvestris. Une faculté germinative de 95% est atteinte avec une accumulation de chaleur de 875 degrés-jours dans le cas du Picea abies et de 975 degrés-jours dans le cas du Pinus sylvestris. [Traduit par la Rédaction]

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To determine if a tree seed crop is sufficiently viable to warrant cone collection or to attempt stand reestablishment through natural regeneration, there is a need for early, largescale predictions of germination capacity. Identification of larger areas or regions experiencing favourable or adverse conditions for seed maturation is important for effective Received January 23, 1998. Accepted July 30, 1998. C. Almqvist1 and U. Eriksson. Forestry Research Institute of Sweden, Uppsala Science Park, S-751 83 Uppsala, Sweden. U. Bergsten. SLU, Department of Silviculture, S-901 83 Umeå, Sweden. L. Bondesson. Uppsala University, Box 480, S-751 06 Uppsala, Sweden. 1

Author to whom all correspondence should be addressed. e-mail: [email protected]

Can. J. For. Res. 28: 1530–1535 (1998)

planning of both cone collection and soil treatment for natural regeneration. Additionally, predictions of a desirable seed crop will determine where to concentrate stand-level sampling. In Sweden the present method of predicting seed germination capacity of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst.), over a large geographic area, is based on the temperature from June until August in the year of seed maturation (Alfjorden and Remröd 1975). The method is widely used for both species despite being based solely on data from Scots pine. Predictive functions exclusively for Norway spruce must be developed, since Norway spruce may have lower temperature requirements for producing mature seed than Scots pine (Wennström and Almqvist 1995). Additionally, the Scots pine functions need improvement, since the predictions may be inaccurate, especially in years with high temperature during early spring (Wennström 1991). © 1998 NRC Canada

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Fig. 1. Location of the stands and weather stations.

Temperature affects both start and rate of pollen tube growth (Owens 1973; Sarvas 1962, 1968; Nygren and Pulkkinen 1994) and, consequently, time of fertilisation. In locally adapted populations of both Scots pine and Norway spruce, fertilisation is calculated to occur when the accumulated heat sum has reached about 30% of the long-term average heat sum (threshold 5°C) for the locality (Sarvas 1967, 1968). Temperature during spring and a factor for embryo growth should thus be included in any model predicting seed germination capacity. For large-scale predictions, Henttonen et al. (1986) presented a model, for Scots pine, which shows a strong relationship between seed maturation and accumulated heat sum (threshold 5°C). In this paper, we tested a similar approach to create new functions for predicting germination capacity of Scots pine and Norway spruce on a large scale to be used to optimize cone collection strategies and to identify areas and years when attempts to naturally regenerate would probably fail. We used data from natural Scots pine and Norway spruce stands to evaluate the relationship between germination capacity and heat sums, with different threshold values. The influence of the estimated number of days from fertilisation until embryo growth cessation is also evaluated.

trees per stand. Data from 1297 Scots pine stands and 597 Norway spruce stands were used (Fig. 1). Altitude of the stands varied between 5 and 700 m above sea level and latitude varied from 55°25′N to 68°30′N for both species.

Germination capacity All analyses were done immediately after the cones were collected and extracted. The number of seeds analyzed for each stand varied from 250 to 400, with a majority of 300 seeds. Germination capacity was assessed using a standard germination test on a germination table or by measurement of the anatomical potential of the seeds (Simak 1980). Germination on top of paper for 21 days for Norway spruce and 14 and 21 days for Scots pine was used for evaluation with a temperature regime of 20°C for 16 h and 30°C for 8 h. Occasionally, for Scots pine, a constant 20°C temperature was also used (cf. ISTA 1996). The anatomical potential is the calculated percentage of seeds that have anatomical prerequisites (female gametophyte size and embryo length) necessary for germination when physiological maturity is attained. The anatomical potential was determined with X radiography (cf. Simak 1980). Data for both methods from 496 samples were used to relate anatomical potential and germination capacity by linear regression. Seed samples with more than 50% seeds damaged by insects were excluded from the study.

Temperature data

Seed collections Cone samples used for obtaining seed germination data for this investigation were collected from natural stands throughout Sweden from 1971 to 1994. The original purpose of the collections was to evaluate the current year’s seed quality of a certain stand prior to cone collection. Cone samples were collected between September and March, with most collections from October to December. Each sample was collected from the whole crown from at least 10

Daily mean temperature data from 71 stations of the Swedish Meteorological and Hydrological Institute (SMHI) were used (Fig. 1). A temperature regime from the closest SMHI station was assigned to each stand. Stand and station were matched according to the recommendations for seed and seedling transfer in Sweden (cf. Anonymous 1986). Maximum distance between a stand and a station was set to 100 km unless the station was coastal or close to a large lake. In these cases the maximum distances were set to 50 and 75 km, respectively (cf. Lindgren 1994). For each stand the daily mean temperature was adjusted 0.6°C/100 m (Ångström 1974) according to the difference in altitude between the stand and © 1998 NRC Canada

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Can. J. For. Res. Vol. 28, 1998 Table 1. Prediction variables tested. Abbreviation

Description

TS5 TS52 NumD

Heat sum/100, degree-days, threshold 5°C, until August 31 Square of TS5 Number of days between estimated time of fertilisation and August 31 (i.e., embryo growth cessation) Heat sum/100, degree-days, over a threshold, and to a certain end date Square of TS Dummy variable for species


TS TS2 SP

Table 2. Parameter estimates for the chosen model (eq. 2) (p value given in parentheses). Parameter estimates β0

Function No.

Species

1 2 3 4

Pinus Picea Pinus Picea

sylvestris abies sylvestris abies

–17.008 –15.912 –16.107 –15.134

β1 TS5 3.385 3.385 3.966 3.966

Table 3. Correlation coefficients for functions with heat sum threshold values other than 5°C and (or) other stop dates for heat sum accumulation.

β2 TS52 (0.016) (0.016) (0.002) (0.002)

SP, SP, SP, SP, SP,

TS, TS, TS, TS, TS,

2

TS TS2 TS2 TS2 TS2

Temperature threshold (°C)

End date

r

+4 +6 +8 +10 +5

August 31 August 31 August 31 August 31 September 30

0.81 0.81 0.80 0.78 0.82

Note: r is the correlation coefficient between observed and predicted germination capacity.

the station. Heat sums, using degree-day summation (Sarvas 1967), with threshold values of 4, 5, 6, 8, and 10°C were calculated from the start of the growing season (i.e., when the average daily temperature exceeds the threshold value) until August 31 or September 30. The heat sum equation with threshold 5°C is n

[1]

TS5 = ∑ (t m − 5) n =1

where TS5 is the accumulated heat sum, n is the total number of days with a mean temperature higher than the treshold, and tm is the mean temperature of the nth day. Heat sums needed for fertilisation to occur in each stand were estimated by first calculating the long-term average heat sum (threshold 5°C) for the stand (Morén and Perttu 1994). Then the heat sum needed for fertilisation was computed as a proportion of the long-term average heat sum. According to Sarvas (1967, 1968), this proportion is about 31% for Scots pine and 30% for Norway spruce. We tested values of 25, 30, and 35% for each species as the estimated date of fertilisation and calculated the number of days available for seed and embryo growth and maturation as the number of days between the estimated time of fertilisation and August 31, which was used as an estimate of embryo growth cessation.

(0.096) (0.096) (0.026) (0.026)

r

— — –0.052 (0.060) –0.052 (0.060)

0.82 0.82 0.83 0.83

Statistical methods We used the logistic regression model described by Collett (1991) to predict germination capacity as a function of the prediction variables shown in Table 1:

Heat sum accumulation Function variables

–0.138 –0.138 –0.167 –0.167

β3 NumD

 p   = β0 + β1χ1 + K + βmχ m ln   1 − p  where p is the proportion of seeds that germinate, χ1, ..., χm are covariates (i.e., predicting variables), β0 is an intercept parameter, and β1, ..., βm are slope parameters. Solving for p, we have

[2]

p=

1 1 + exp {−β0 − β1 ⋅ x1 − β2 ⋅ x 2 − K − βm ⋅ x m}

The maximum likelihood method of the LOGISTIC procedure (SAS Institute Inc. 1996) was used to estimate the parameters. In the calculations the seeds from each stand were seen as count data from a binomial experiment. The total number of seeds represents the number of trials, and the number of germinating seeds represents the events. In the calculations, all seed samples were adjusted to be of equal size (300 seeds). Correction for overdispersion was done with the Williams procedure (Collett 1991, pp. 195–199) using the option SCALE in the LOGISTIC procedure (SAS Institute Inc. 1996).

The parameter estimates for the relationships (eq. 2) between climatic variables and germination capacity of Scots pine and Norway spruce had lower p values if heat sum (threshold 5°C), the square of heat sum, and the number of days between estimated time of fertilisation and August 31 were used as prediction variables (Table 2). An example of the functions, including the number of days between estimated time of fertilisation and embryo growth cessation (August 31), is shown in Fig. 2 (function 3). Correlation coefficients for other threshold values of heat sum tested were the same or lower than for a threshold of © 1998 NRC Canada


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Fig. 2. Response curves of the Scots pine function including the variable NumD. For parameters, see Table 2, function 3. Solid line, NumD = 65; dashed line, NumD = 70; dotted line, NumD = 75.

Fig. 3. Relationship between germination capacity and heat sum for Scots pine and Norway spruce seed based on functions 1 and 2 in Table 2. Solid line and solid circles, Scots pine; dashed line and open circles, Norway spruce. A random sample of 200 Scots pine and 100 Norway spruce data points is included.

5°C (Table 3). An extension of the time for heat sum accumulation until September 30 did not improve the correlation coefficients. Other variables such as latitude, longitude, and altitude did not have any significant effect when heat sum was included in the model (not presented). According to functions 1 and 2 the heat sum requirements for producing mature seed of Scots pine were higher than for Norway spruce. The maximum difference in germination capacity between the species was about 27% at 670 degreedays. A germination capacity of 95% was attained at 875 degree-days for Norway spruce and 975 degree-days for Scots pine (Fig. 3). A difference of 10 days in the number of days between fertilisation and the end of embryo growth (Num.) had a maximum effect of about 14% on germination capacity at 700 degree-days for Scots pine (Fig. 2). Using long-term series of weather data makes it possible to identify areas experiencing favourable or adverse conditions for seed maturation. An example of such use is shown in Table 4 where the proportion of years with germination capacity less than 75% is presented for six weather stations.

the time variable would probably improve the prediction of seed germination capacity. Anatomical ripening for Scots pine in northern Fennoscandia ceases in the middle of September, and physiological ripening ceases 2–4 weeks later (Sahlén 1992). For forestry applications, it is desirable that the forecast of the seed quality become available as early as possible. Extending the heat sum accumulation time did not improve our model. This suggests that temperature conditions in September have limited influence on the final germination capacity of the seed, which also agrees with Opsahl (1952). In our material for Norway spruce, most samples had high germination capacity. Only 79 of 597 observations had a germination capacity less than 80%. Since there were no significant differences in the slope parameter estimates between Norway spruce and Scots pine, their functions were estimated jointly with a dummy variable for species in the final model. This decision is also supported by the fact that fertilisation in Scots pine and Norway spruce takes place almost simultaneously and embryo development is parallel in the two species (Håkansson 1956; Sarvas 1967, 1968). However, the prediction functions in this paper show that Norway spruce has lower temperature requirements for producing mature seeds than does Scots pine. Although there have been indications of this fact earlier (Hagem 1917; Kujala 1927; Opsahl 1952; Hagner 1958; Lestander and Wennström 1989; Wennström and Almqvist 1995), no functions for prediction of germination capacity of Norway spruce have been available. The prediction function for seed maturation of Scots pine presented by Henttonen et al. (1986) and our function have a similar curve shape. However, the heat sum necessary to reach a certain level of germination capacity using their function is greater. To reach 50% anatomically mature seed, 890 degree-days are necessary, while with our Scots pine function (function 1), 50% germination capacity is attained at 725 degree-days. Their function uses heat sum (threshold 5°C) for the whole growing season (until no more heat sum is accumulated in autumn) as predictor variable whereas we used heat sum with the same threshold but only until August 31, which could partly explain the difference. The heat sum for the whole growing season corresponding to 725 degreedays on August 31 is about 800 degree-days (Lindgren 1994). Harju et al. (1996) presented data showing that 50%

Of the heat sums with different threshold temperatures that we tested, 4, 5, and 6°C were almost equally good. The most common threshold value for biological functions used in Swedish forestry is 5°C (Morén and Perttu 1994), and the estimations of fertilisation time by Sarvas (1967, 1968) are based on heat sums with a threshold of 5°C. Thus, it seems most appropriate to choose 5°C as a threshold for the predictive functions. The time of fertilisation and consequently the time for the seed and embryo to grow and mature vary between years at the same locality. Early fertilisation allows the seeds more time for both anatomical and physiological ripening before growth cessation. Which environmental factors that induce cessation of the anatomical ripening of the seed are not yet fully known, although it is probably regulated by photoperiod (Sahlén and Bergsten 1993). At present, there is no information available about the clinal (e.g., latitudinal) variation in this regulation. Thus, in the model the time variable for embryo growth, Num., was calculated with a fixed stop date, August 31, for all stands. A more precise calculation of

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Table 4. Proportion of years with germination capacity lower than 75% according to the presented functions. Example from six weather stations.


% years with germination capacity