Open Access

Seed production, seed dispersal and seedling establishment of two afromontane tree species in and around a church forest: implications for forest restoration

Forest Ecosystems20163:16

https://doi.org/10.1186/s40663-016-0076-5

Received: 30 September 2015

Accepted: 7 July 2016

Published: 26 July 2016

Abstract

Background

Seed production, seed dispersal and seedling establishment are relevant life phases of plants. Understanding these processes and their patterns is essential to recognize vegetation dynamics and to apply it to forest restoration.

Methods

For Olea europaea and Schefflera abyssinica, fecundity was estimated using randomized branch sampling. Seed dispersal and seedling establishment were monitored using spatially explicit seed traps and plots. Dispersal functions were calibrated applying inverse modeling.

Results

O. europaea produced more seeds and had longer dispersal distances compared to S. abyssinica. Correlations between observed and predicted number of recruits were statistically significant. Seedlings of the two species showed different niche requirements.

Conclusions

The studied species were recruitment-limited due to low dispersal activity or lack of suitable microsites. Restoration relying on natural regeneration should overcome these limitations by increasing disperser visitation and reducing biotic and abiotic stresses.

Keywords

Fecundity Olea europaea Schefflera abyssinica Recruitment limitation Restoration

Background

Deforestation is almost a synonym for Ethiopian forest history. Small patches of forests that surround churches, hence called church forests, are the only remnants after past deforestation in the northern part of the highlands (Nyssen et al. 2004, 2009). Church forests are located as islands in a matrix of a highly degraded agricultural landscape (Wassie et al. 2005). They represent hotspots of biodiversity and are critical conservation areas in the Afromontane region (Aerts et al. 2016). Ecosystem restoration with the objective of watershed and riparian repair functions as well as livelihood and landscape diversification is a national priority in current land management in these degraded highlands (Nyssen et al. 2004).

The most appropriate strategy to restore degraded agricultural landscapes involves the reconstruction of native plant communities through re-colonization of native flora, reforestation or afforestation (Stanturf et al. 2014). Restoration can be achieved using tree species (active restoration), relying on natural re-colonization, or through assisted natural regeneration (passive restoration). Both approaches have been discussed as restoration options to re-vegetate the highlands of Ethiopia (Abiyu et al. 2011). In the past, reforestation programs with plantation species were successful due to the fast growth of such species and their well-known management practices (Zanne and Chapman 2001; Lemenih and Teketay 2006). While these plantations improve soil fertility (Lemma et al. 2006; Abiyu et al. 2011), they do not have any positive effect on biodiversity (Chazdon 2008) and therefore represent an incomplete first step of a restoration process (Stanturf et al. 2001). Assisted natural regeneration and natural regeneration rank highest on the restoration ladder (sensu Chazdon 2008) with the highest ranks in biodiversity and ecosystem services at the lowest associated cost. These approaches, however, have the highest requirements in terms of spatial distribution of residual vegetation or biological legacies (Bannister et al. 2014). In order to achieve cost-efficient and timely restoration, a combination of mixed passive and active restoration strategies are favored in certain situations (Bannister et al. 2014). Thus, strategies and methods of forest restoration may follow different paradigms depending on stakeholder objectives, regional climate and degree of degradation (Jacobs et al. 2015).

Fruit production, seed dispersal, germination and seedling establishment are critical life phases in plants (Harper 1997). A clear understanding of these issues are crucial to recognize patterns of colonization and extinction, directional changes in species composition or succession over time, which have strong relevance for ecosystem restoration (Hobbs et al. 2007). Information on relevant life phases of Afromontane plant species is scarce. In the absence of this information there are no means to identify the risks of failure of management measures and the means to overcome them. This information helps to understand filters of succession that determine the floristic composition of the secondary forest resulting from a passive restoration treatment. An understanding of these key processes allows the prediction of the likely outcome of any silvicultural measure in terms of vitality, density, survival, growth and quality of regeneration at an appropriate time (Wagner et al. 2010).

Studies on the regeneration ecology of trees in the Afromontane forest regions in Ethiopia have characterized propagule pools, particularly soil seed banks and seedling banks, thus focusing on storage effects of reproductive potentials (Teketay and Granström 1995, 1997). Soil seed banks have little potential as a source of tree regeneration in the Afromontane region given the lack of available seeds due to soil erosion or the failure to form persistent soil seed banks owing to the physiological requirements of seeds (Teketay and Granström 1995, 1997). Apart from a study carried out for Leptonychia usambarensis in Tanzania (Cordeiro et al. 2009), no studies have been conducted to characterize seed dispersal of tree species in Afromontane forests. Some studies conducted so far acknowledge the importance of this information for East African Afromontane forests (Aerts et al. 2006). In principle, recruitment limitation can be caused by limited seed availability or by constraints on seedling establishment (Clark et al. 1999, 2007; Nathan et al. 2000; Muller-Landau et al. 2002). Dispersal mediated recruitment limitation is especially severe with fleshy fruited trees (Rey and Alcántara 2000; Zywiec et al. 2013). While these limitations may promote coexistence in plant communities at stand levels (Herrera and Jordano 1981; Herrera et al. 1998; Abrams 2003), they severely inhibit ecosystem restoration (Holl 1998, 1999, 2008).

Ecosystem restoration in general requires knowledge on seed dispersal characteristics of targeted tree species and an understanding of constraints to seedling establishment and survival. The objective of this study was to compare the similarities and differences between the seed dispersal, seed rain and seedling establishment patterns of two selected native tree species in an Afromontane church-forest of the northern Ethiopian Highlands.

Methods

Study area

The research was conducted in and around Tara-Gedam church forest in northwestern Ethiopia (12°08′35′′N and 37°44′29′′E), situated in steep mountain terrain. The northern and northwestern boundaries of the forest are defined by steep hill slopes, the western boundary by a highway. The southern and the southeastern boundaries delimit it towards a matrix of farm and grazing land settled by subsistence farmers. Leaving a diversity of trees, which have positive interaction with crops and livestock scattered in the landscape (parkland agroforestry), is a typical land use system. The elevation ranges from 2175 to 2390 m. The mean annual minimum temperature is 13 °C and the maximum 27 °C. The mean annual rainfall is 1085 mm and occurs from June to September. The composition of the forest consists of the following native trees and shrubs: Olea europaea L. ssp. cuspidata (Wall. ex G. Don) Cif., Schefflera abyssinica (Hochst. ex A. Rich.) Harms, Albizia schimperiana Oliv., Ekebergia capensis Sparrm., Croton macrostachyus Hochst. ex Del., Acacia negrii Pic.-Serm., Apodytes dimidiata E. Mey. ex Arn., Nuxia congesta R. Br. ex Fresen., Schrebera alata (Hochst.) Welw., Grewia ferruginea Hochst. ex A. Rich., Vernonia amygdalina Del., Calpurnia aurea (Ait.) Benth., Carrisa spinarum L., Dovyalis abyssinica (A. Rich.) Warb., Bersama abyssinica Fresen., Rhus glutinosa A. Rich., Clausena anisata (Willd.) Benth., Osyris quadripartita Decn., Maesa lanceolata Forssk. and Myrsine africana L. Eucalyptus camaldulensis Dehnh. is the dominant non-native tree species in the matrix of degraded land beyond the church forest.

Two native tree species, i.e., Olea europaea L. ssp. cuspidata (Wall. ex G. Don) Cif. (from here on referred to as O. europaea) and Schefflera abyssinica (Hochst. ex A. Rich.) Harms (S. abyssinica) were selected for this study, considering their dominance as upper canopy trees in forest remnants and also for their timber and non-timber importance to local people. The study was carried out from February to November 2009 and from January to October 2010.

O. europaea is an evergreen tree or shrub, reaching a height of up to 18 m. The flowers and fruits are clustered on auxiliary panicles. Fruits are dark violet when ripe, one seeded and 0.5 to 1 cm in diameter. Flowering and fruiting time is between September and January. Dispersal is predominantly by frugivorous birds. S. abyssinica is a deciduous tree species reaching up to a height of 30 m. The flowers and fruits are clustered at the end of 30 to 40 cm racemes. The multi-seeded fruits are red and 0.26 to 0.31 cm long. Flowering and fruiting time is from March to May. Dispersal is mostly carried out by fruit eating birds (Bamps 1989). In our study area, it starts its life as an epiphyte and becomes an upper canopy tree when fully grown (Abiyu et al. 2013).

Seed trap placement for dispersal distance estimation

Seed traps were used to sample seed rain inside and outside the forest patch. The seed traps were circular baskets with a 60 cm radius, made from bamboo and lined with plastic sheets. Three 1.5-m high stakes were used to raise the seed traps above the ground to avoid predation by rodents (Additional file 1). However, not all traps were at similar height above the ground, given differences caused by pit preparation.

Traps were arranged inside the forest and in the matrix outside the forest. In the matrix outside the forest, traps were arranged along transects, under trees and along water bodies and drainage lines (Fig. 1). The total number of traps set inside and outside the forest was 388. The coordinates (x, y) of each trap and potential seed source tree were established. The traps were set up in November 2009 and were monitored during the fruit setting period up to July 2010. Seeds from traps were collected once a week, counted at the spot, bagged, labeled and transported to the laboratory. This routine was repeated until no more seeds were recovered from the traps.
Fig. 1

Map showing the study area, the location of transects and seed traps. Vertical lines indicate UTM northing and horizontal lines indicate UTM easting

Regeneration study

Next to each trap, 1 m2 (1 m × 1 m) plots were prepared, where seeds were marked with toothpicks and monitored for emerging seedlings. These plots were stratified into: (i) open habitats, (ii) stones/boulders, (iii) trees/shrubs and (iv) banks and the immediate neighborhood of water bodies (springs, ponds and creeks).

While established plants and germinants are rare in the studied habitats, tree establishment was observed in areas with freshly exposed soil by human activity. In addition and in order to validate seed dispersal kernels with plant distribution, we laid out a further set of 34 square plots (2 m × 2 m) along additional transects running from seed sources into the open habitats, perpendicular to the first set of transects. Habitats for these plots were classified into road side boulders (12 plots), stone bunds on farms (10 plots) and open spaces between these habitats (12 plots).

Modeling seed dispersal: fecundity and distance

The approach developed by Ribbens et al. (1994) is widely used in modeling seed dispersal (Loiselle et al. 1996; Wada and Ribbens 1997; LePage et al. 2000; Canham and Uriarte 2006). It models both components of dispersal functions, i.e., the amount of seeds produced and the dispersal distance. Poisson distribution functions are used to predict the seedling recruitment patterns using the following equation:
$$ R=\left[STR\times \left(\frac{dbh}{45}\right)\beta \right]\times \frac{1}{n}\times \left[e{-}^{D\times m\theta}\right] $$
(1)
where R is the predicted number of recruits (seeds and seedlings) and STR (standard total recruitment) denotes the number of fruits produced by a tree of standard dbh (diameter at breast height). The parameter β modifies STR as a power function of the actual dbh observed.
The second part of the equation represents the mean density of recruits in a trap located at distance m from the parent tree, where n is a normalizer ensuring that the area under the second portion of the equation is equal to 1, ɵ determines the shape of the distribution and D determines the steepness of decline in the number of recruits as the distance from the parent tree increases. Therefore, the number of recruits (R) predicted for trap i, given T trees, is:
$$ {R}_i={\displaystyle \sum_{j=1}^T\left[STR\times {\left(\frac{db{h}_j}{45}\right)}^{\beta}\right]\times \frac{1}{n}\times \left[e{-}^{D\times mi{j}^{\theta }}\right]} $$
(2)
where m ij is the distance from the i th sample trap to the j th tree.

Fecundity estimation

We used randomized branch sampling (RBS) for the initial estimation of fecundity or standard total recruitment (STR) (Gregoire et al. 1995). RBS is a multistage sampling procedure, which defines a unidirectional random walk along the natural branching pattern within the crown of a tree. In this procedure, the most important points are defining the nodes (points where branching begins), segments (inter-nodal points) and paths (series of successive segments). A path is selected starting from the first node. The following segment is chosen by randomized selection weighted by the relative cross sectional area (CSA) of the radiating segments on the node. The thicker the segment, the more likely its selection. Eight individual trees of both species were randomly selected, since the church limited destructive sampling. From each individual tree, a limb (segment) was chosen from a pair or couple of limbs (segments) according to the probability proportional to its CSA. The number of seeds on the chosen limb (segment) was counted. This process continued until a terminal limb (segment), with a predetermined specific size was reached. The terminal limb circumference was between 4 and 6 cm. Fecundity then is defined as the total number of fruit counts at the final stage of the selected limb divided by the product of probabilities along the path (Jessen 1955; Cancino and Saborowski 2005, 2007; Peter et al. 2010). The total number of seeds per tree varied from 7,000 to 110,000 for both species.

Thus, the initial value of STR was set at 50,000 and the fixed dbh was set at 45 cm based on the average value of sampled trees. Initial values for the parameters were made to fluctuate and wander up to 40 % of their original values, without fixing them, as suggested by E. Ribbens (personal communications).

Data analysis

Model evaluation

Models were evaluated using maximum likelihood estimation, resulting in a likelihood function, which states the probability of obtaining a set of observations. In our case, maximum likelihood based dispersal functions determined the probability to observe a certain number of seeds, given a particular set of parameters. RECRUITS 3.1 (Ribbens 2002) was used to calibrate the dispersal function (equation 2), using the Metropolis algorithm to find a combination of parameter values that are likely to produce the observed values.

Mean dispersal distance (MDD), percentage of strange recruits or percentage strangers (PS), observed-predicted correlation and confidence intervals were calculated for the statistical evaluation of the model. RECRUITS calculates MDD by distributing the expected seeds on a circle around a parent tree and determining the average distance from the tree. The observed-predicted correlation is the measure of spatial association between observed and model predicted values; this method uses product—moment correlation coefficients between observed values and expected means for every species. Approximate bivariate 95 % confidence intervals were fitted for estimates of STR and MDD values using the inverse likelihood ratio test. The percentage strangers (PS) calculates the amount of seeds contributed by trees outside the observation distance or the amount of seeds contributed from unmapped trees in the vicinity of the traps inside the observation distance.

Model validation

The recruitment functions (equation 2) were cross-validated by omitting every third trap, computing a new model and using the new model to predict traps omitted from the new model (Ribbens et al. 1994).

Regeneration study

Descriptive statistics were used to visualize the number of seeds reaching different traps located in the various habitats. In the 2 m × 2 m plots along the transects, one way ANOVA with unequal sample sizes was used to test the hypothesis of differences between the various habitats (micro sites) in the emergence of seedlings.

Results and Discussion

The amounts of seeds produced per parent tree varied between the two species. The STR value denoting the seed production for the standardized parental size was higher for O. europaea (36,219) than for S. abyssinica (28,221) (Table 1).
Table 1

Maximum likelihood estimates of the parameters used in the dispersal function

Parameter

Olea europaea (median dispersal distance 200 m)

Schefflera abyssinica (median dipersal distance 100 m)

Mean

Confidence interval

Mean

Confidence interval

Lower

Upper

Lower

Upper

STRa

36, 219

35, 600

38, 500

28, 221

26, 900

28, 900

Beta

1.08

0.96

1.19

0.94

0.84

1.03

D b

2.43

2.39

2.46

12.06

11.74

12.37

MDDc

191

188.7

198.5

92

88.9

95.2

Theta

0.46

0.46

0.46

0.78

0.77

0.78

R d

0.38*

0.39*

Normalizer

5684

7328

Beta and Theta are parameters for the Poisson distribution function

*Significant at p = 0.05

aSTR is the standard total recruitment

b D the speed of the decline in the number of recruits

cMDD the mean dispersal distance

d R the observed-predicted correlation

The standard total recruitment (STR) values show seed production potential and hence fecundity. The total seed production values for both species studied are within the range of estimates of fruit production reported for tropical trees in Africa, e.g., 12,000–72,000 reported from Cameroon (Norghauer and Newbery 2015). Clark et al. (2005) estimated the fecundity of trees in the Dja Reserve, Cameroon between 25,000 to 65,000 for bird dispersed seeds and from 22,000 to 79,000 for mammal dispersed seeds.

Seed dispersal profiles of the two species showed that up to 55 m dispersal distance seed densities were higher for S. abyssinica than for O. europaea, while the latter species had higher seed densities compared to S. abyssinica at longer distances (Fig. 2).
Fig. 2

Seed dispersal profiles for Schefflera abyssinica and Olea europaea ssp. cuspidata

The difference in the dispersal profile of the two tree species may be a reflection of the reproductive ability of their mother trees, their seed disperser activity and differential requirements of the seeds and seedlings (Rey and Alcántara 2000). S. abyssinica is represented by few large and sparsely scattered trees in the forest (Abiyu et al. 2013). It produces lipid and protein rich fruits (Saracco et al. 2005) with attractive colors which can be tracked by specialist and generalist frugivorous birds, probably with short gut retention time, dropping the seeds close to the seed source. O. europaea trees are distributed abundantly in the study area. Their fruits are mostly tracked by specialized frugivorous birds, which may disperse the seeds over longer distances.

The median distance was 200 m for O. europaea and 100 m for S. abyssinica. The mean dispersal distance (MDD) was 191 m for O. europaea and 92 m for S. abyssinica (Table 1). The percentage of strangers was higher for O. europaea (46 %) than for S. abyssinica (40 %).

Dispersal distances for both species can be included in the range of long distance dispersal (Norghauer and Newbery 2015), even though they are shorter than reported by other studies from the tropics. Clark et al. (2005) found up to 473 m dispersal distances for animal-dispersed species. Farther distances (316 m) were also reported (Godoy and Jordano 2001). In general, animal dispersed tree species seeds have longer dispersal distances than wind dispersed ones (Ribbens et al. 1994).

The number of predicted and observed recruits are shown for both species (Fig. 3). The correlation coefficient, indicating intensity of association or spatial congruence between observed and predicted data sets, was 0.38 for O. europaea and 0.39 for S. abyssinica (Table 1). These values were also statistically significant when cross-validated, i.e., 0.55 for O. europaea and 0.35 for S. abyssinica. The highest number of dispersed seeds was located near their source trees (Fig. 4).
Fig. 3

Predicted (continuous lines) and observed (dotted lines) seed density of a Olea europaea ssp. cuspidata and b Schefflera abyssinica

Fig. 4

Seed density of Olea europaea seedlings on artificially created structures as a function of distance from the seed source

Despite the arrival of seeds, there was no seedling recruitment on the 1 m2 plots located near to the seed traps. Seeds of S. abyssinica were found in traps placed under fruiting trees of its own species, while no seeds were found in traps placed in other habitats. The highest average number of seeds of O. europaea per trap was recorded in traps placed close to springs (681) followed by traps adjacent to bigger stones (183), under trees/shrubs (22) and on open sites (<1) (Table 2).
Table 2

Mean number of seeds recorded in seed traps placed in different habitats for Olea europaea ssp. cuspidata and Schefflera abyssinica (the numbers in brackets indicate the standard deviation of the mean)

Habitat for trap location

Number of traps with seeds

Mean number of seeds per trap

Olea europaea

Schefflera abyssinica

Open

158

0.18 (0.89)

-

Stone/boulders

32

183 (755)

-

Trees/shrubs

230

22 (53)

43 (48)

Springs

11

681 (1580)

-

No seedling recruitment from the ground was recorded for S. abyssinica in the 2 m × 2 m plots. There were no statistically significant (F = 2.29, p = 0.12) differences in the number of seedlings of O. europaea among the various habitats. However, a large number of O. europaea seedlings were found on human-made structures such as between boulders excavated during road construction and on stone bunds constructed for soil and water conservation (Fig. 4). On these selected habitats, seedling density diminished with increasing distance from the seed source.

Except on certain human-made structures, seed dispersal was not accompanied by successful germination. Two conditions, non-random arrival and survival in predictable locations, should be met for directed seed dispersal to occur. Therefore, its contribution is minimal for vegetation dynamics in the study area. This may arise mainly from the uncoupling of different selective forces acting on seeds and seedlings (Rey and Alcántara 2000) or from onthogenic shifts in stress and resource requirement in various microhabitats (Jordano and Herrera 1995; Schupp 1995).

O. europaea and S. abyssinica are recruitment-limited in our studied landscape. Although there are several mother trees at the population level for the production of recruits for O. europaea, this species is recruitment-limited due to low dispersal activity as well as its failure to germinate and establish after dispersal. Dispersers birds do not take seeds of O. europaea to microsites. On the other hand, S. abyssinica is recruitment-limited because there are few mother trees at the population level and too few available microsites such as branch forks and stem wounds. These available microsites can be saturated easily (Abiyu et al. 2013).

The location of restoration sites in relation to the seed source critically affects restoration success (Holl 1998, 1999, 2008). Our study corroborates the need to maintain patches of forests as islands and stepping stones for biodiversity conservation and restoration. Church forests in northern Ethiopia are remnants of the original tree population (Aerts et al. 2016). Currently, these forests are facing strong anthropogenic pressure and dispersal of propagules from these remnants is crucial to form viable populations at the patch level. As well, restoration of those areas, devoid of their natural vegetation in the landscape, need seed input from the remnant forests. Seed dispersal is a filter for succession and affects the quality of regeneration in the context of passive restoration. This raises the importance of other landscape elements and biological legacies, such as trees on hedges and homesteads to support restoration as seed sources. In the absence of these supplementary seed sources, deliberate introduction of these two species may be needed in highly degraded areas.

Conclusions

The median dispersal distance for both species is less than 200 m. For successful dispersal and recruitment of O. europaea and S. abyssinica in degraded ecosystems in the Ethiopian highlands, the potential mother trees should be located not farther than the median dispersal distance. In the absence of seed sources within the indicated distance, reliance on natural regeneration may not be a suitable restoration strategy.

Declarations

Acknowledgements

The authors thank the Commission for Development Studies (KEF), ÖAD and the International Foundation for Science (IFS) for financial support to A.A. Molla Addisu and Fikirte Shewatatek assisted in data collection and the late Sinatyehu Bayeh provided valuable comments on the arrangement of the seed traps. Eric Ribbens provided support with the RECRUITS software, Menale Wondie provided GIS support and Andras Darabant provided English language editing and correction support. We thank the reviewers who helped us to improve an earlier version of the manuscript.

Authors’ Contribution

All authors conceived the study. All authors helped to draft the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Amhara Agricultural Research Institute
(2)
Department of Crop Science and Production, Botswana University of Agriculture and Natural Resources
(3)
Institute of Forest Ecology, University of Natural Resources and Life Sciences

References

  1. Abiyu A, Gratzer G, Teketay D, Glatzel G, Aerts R (2013) Epiphytic recruitment of Schefflera abyssinica (A. Rich) Harms. and the rle of microsites in affecting tree community structure in remnant forests in northwest Ethiopia. SINET: Ethiopian J Sci 36(1):41–44Google Scholar
  2. Abiyu A, Lemenih M, Gratzer G, Aerts R, Teketay D, Glatzel G (2011) Status of native woody species diversity and soil characteristics in an exclosure and in plantations of Eucalyptus globulus and Cupressus lusitanica in Northern Ethiopia. Mt Res Dev 31(2):144–152View ArticleGoogle Scholar
  3. Abrams MD (2003) Where has all the white oak gone? Bioscience 53(10):927–939View ArticleGoogle Scholar
  4. Aerts R, van Overtveld K, November E, Wassie A, Abiyu A, Demissew S, Daye DD, Giday K, Haile M, TewoldeBerhan S, Teketay D, Teklehaimanot Z, Binggeli P, Deckers J, Friis I, Gratzer G, Hermy M, Heyn M, Honnay O, Paris M, Frank JS, Muys B, Bongers F, Healey JR (2016) Conservation of the Ethiopian church forests: Threats, opportunities and implications for their management. Sci Total Enviro 551:404–414View ArticleGoogle Scholar
  5. Aerts R, Maes W, November E, Negussie A, Hermy M, Muys B (2006) Restoring dry Afromontane forest using bird and nurse plant effects: Direct sowing of Olea europaea ssp. cuspidata seeds. Forest Ecol Manage 230(1–3):23–31View ArticleGoogle Scholar
  6. Bamps R (1989) Araliaceae. In: Hedberg I, Edwards S (eds) Flora of Ethiopia, vol 3, Addis Abeba University. Addis Abeba & Uppsala University, Uppsala, Addis Abeba, pp 537–543Google Scholar
  7. Bannister JR, Wagner S, Donoso PJ, Bauhus J (2014) The importance of seed trees in the dioecious conifer Pilgerodendron uviferum for passive restoration of fire disturbed southern bog forests. Aust Ecol 39(2):204–213View ArticleGoogle Scholar
  8. Cancino J, Saborowski J (2005) Comparison of randomized branch sampling with and without replacement at the first stage. Silva Fennica 39(2):201–216View ArticleGoogle Scholar
  9. Cancino J, Saborowski J (2007) Improving RBS estimates–effects of the auxiliary variable, stratification of the crown, and deletion of segments on the precision of estimates. J For Sci 53(7):320–333Google Scholar
  10. Canham CD, Uriarte M (2006) Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling. Ecol Appl 16(1):62–73PubMedView ArticleGoogle Scholar
  11. Chazdon RL (2008) Beyond deforestation: restoring forests and ecosystem services on degraded lands. Science 320(5882):1458–1460PubMedView ArticleGoogle Scholar
  12. Clark C, Poulsen J, Bolker B, Connor E, Parker V (2005) Comparative seed shadows of bird-, monkey-, and wind-dispersed trees. Ecology 86(10):2684–2694View ArticleGoogle Scholar
  13. Clark C, Poulsen J, Levey D, Osenberg C (2007) Are plant populations seed limited? A critique and meta-analysis of seed addition experiments. Am Nat 170(1):128–142PubMedView ArticleGoogle Scholar
  14. Clark J, Beckage B, Camill P, Cleveland B, HilleRisLambers J, Lichter J, McLachlan J, Mohan J, Wyckoff P (1999) Interpreting recruitment limitation in forests. Am J Bot 86(1):1–16PubMedView ArticleGoogle Scholar
  15. Cordeiro NJ, Ndangalasi HJ, McEntee JP, Howe HF (2009) Disperser limitation and recruitment of an endemic African tree in a fragmented landscape. Ecology 90(4):1030–1041PubMedView ArticleGoogle Scholar
  16. Godoy JA, Jordano P (2001) Seed dispersal by animals: exact identification of source trees with endocarp DNA microsatellites. Mol Ecol 10(9):2275–2283PubMedView ArticleGoogle Scholar
  17. Gregoire TG, Valentine HT, Furnival GM (1995) Sampling methods to estimate foliage and other characteristics of individual trees. Ecology 76(4):1181–1194View ArticleGoogle Scholar
  18. Harper JL (1997) Population biology of plants. Academic, LondonGoogle Scholar
  19. Herrera CM, Jordano P (1981) Prunus mahaleb and birds: the high-efficiency seed dispersal system of a temperate fruiting tree. Ecol Monogr 51(2):203–218View ArticleGoogle Scholar
  20. Herrera CM, Jordano P, Guitián J, Traveset A (1998) Annual variability in seed production by woody plants and the masting concept: reassessment of principles and relationship to pollination and seed dispersal. Am Nat 152(4):576–594PubMedView ArticleGoogle Scholar
  21. Hobbs RJ, Jentsch A, Temperton VM (2007) Restoration as a process of assembly and succession mediated by disturbance. In: Walker LR, Walker J, Hobbs RJ (eds) Linking restoration and ecological succession. Springer, New York, pp 150–167View ArticleGoogle Scholar
  22. Holl KD (1998) Do bird perching structures elevate seed rain and seedling establishment in abandoned tropical pasture? Restor Ecol 6(3):253–261View ArticleGoogle Scholar
  23. Holl KD (1999) Factors limiting tropical rain forest regeneration in abandoned pasture: seed rain, seed germination, microclimate, and soil. Biotropica 31(2):229–242View ArticleGoogle Scholar
  24. Holl KD (2008) Are there benefits of bat roosts for tropical forest restoration? Conserv Biol 22(5):1090PubMedView ArticleGoogle Scholar
  25. Jacobs DF, Oliet JA, Aronson J, Bolte A, Bullock JM, Donoso PJ, Landhäusser SM, Madsen P, Peng S, Rey-Benayas JM (2015) Restoring forests: What constitutes success in the twenty-first century? New Forests 46(5–6):601–614View ArticleGoogle Scholar
  26. Jessen RJ (1955) Determining the fruit count on a tree by randomized branch sampling. Biometrics 11(1):99–109View ArticleGoogle Scholar
  27. Jordano P, Herrera CM (1995) Shuffling the offspring: uncoupling and spatial discordance of multiple stages in vertebrate seed dispersal. Écoscience 2:230–237Google Scholar
  28. Lemenih M, Teketay D (2006) Changes in soil seed bank composition and density following deforestation and subsequent cultivation of a tropical dry Afromontane forest in Ethiopia. Trop Ecol 47(1):1–12Google Scholar
  29. Lemma B, Kleja DB, Nilsson I, Olsson M (2006) Soil carbon sequestration under different exotic tree species in the southwestern highlands of Ethiopia. Geoderma 136(3–4):886–898View ArticleGoogle Scholar
  30. LePage PT, Canham CD, Coates KD, Bartemucci P (2000) Seed abundance versus substrate limitation of seedling recruitment in northern temperate forests of British Columbia. Can J For Res 30(3):415–427View ArticleGoogle Scholar
  31. Loiselle BA, Ribbens E, Vargas O (1996) Spatial and temporal variation of seed rain in a tropical lowland wet forest. Biotropica 28(1):82–95View ArticleGoogle Scholar
  32. Muller-Landau HC, Wright SJ, Calderón O, Hubbell SP, Foster RB (2002) Assessing recruitment limitation: concepts, methods and case-studies from a tropical forest. In: Levey DJ, Silva WR, Galetti M (eds) Seed dispersal and frugivory: ecology, evolution and conservation. CABI Publishing, Wallingford, pp 35–53Google Scholar
  33. Nathan R, Safriel UN, Noy-Meir I, Schiller G (2000) Spatiotemporal variation in seed dispersal and recruitment near and far from Pinus halepensis trees. Ecology 81(8):2156–2169View ArticleGoogle Scholar
  34. Norghauer JM, Newbery DM (2015) Tree size and fecundity influence ballistic seed dispersal of two dominant mast-fruiting species in a tropical rain forest. For Ecol Manage 338:100–113View ArticleGoogle Scholar
  35. Nyssen J, Haile M, Naudts J, Munro N, Poesen J, Moeyersons J, Frankl A, Deckers J, Pankhurst R (2009) Desertification? Northern Ethiopia re-photographed after 140 years. Sci Total Environ 407(8):2749–2755PubMedView ArticleGoogle Scholar
  36. Nyssen J, Poesen J, Moeyersons J, Deckers J, Haile M, Lang A (2004) Human impact on the environment in the Ethiopian and Eritrean highlands—a state of the art. Earth Sci Rev 64(3–4):273–320View ArticleGoogle Scholar
  37. Peter H, Otto E, Hubert S (2010) Leaf area of beech (Fagus sylvatica L.) from different stands in eastern Austria studied by randomized branch sampling. Eur J For Res 129(3):401–408. doi:10.1007/s10342-009-0345-8 View ArticleGoogle Scholar
  38. Rey PJ, Alcántara JM (2000) Recruitment dynamics of a fleshy fruited plant (Olea europaea): connecting patterns of seed dispersal to seedling establishment. J Ecol 88(4):622–633View ArticleGoogle Scholar
  39. Ribbens E (2002) RECRUITS 3.1 Operating manual. Department of Biology. Western Illinois University, MacombGoogle Scholar
  40. Ribbens E, Silander JA, Pacala SW (1994) Seedling recruitment in forests: calibrating models to predict patterns of tree seedling dispersion. Ecology 75(6):1794–1806. doi:10.2307/1939638 View ArticleGoogle Scholar
  41. Saracco JF, Collazo JA, Groom MJ, Carlo TA (2005) Crop size and fruit neighborhood effects on bird visitation to fruiting Schefflera morototoni trees in Puerto Rico. Biotropica 37(1):81–87View ArticleGoogle Scholar
  42. Schupp EW (1995) Seed-seedling conflicts, habitat choice, and patterns of plant recruitment. Am J Bot 82:399–409View ArticleGoogle Scholar
  43. Stanturf JA, Palik BJ, Dumroese RK (2014) Contemporary forest restoration: A review emphasizing function. For Ecol Manage 331:292–323View ArticleGoogle Scholar
  44. Stanturf JA, Schoenholtz SH, Schweitzer CJ, Shepard JP (2001) Achieving restoration success: myths in bottomland hardwood forests. Restor Ecol 9(2):189–200View ArticleGoogle Scholar
  45. Teketay D, Granström A (1995) Soil seed banks in dry Afromontane forests of Ethiopia. J Veg Sci 6(6):777–786View ArticleGoogle Scholar
  46. Teketay D, Granström A (1997) Germination ecology of forest species from the highlands of Ethiopia. J Trop Ecol 13(6):805–831View ArticleGoogle Scholar
  47. Wada N, Ribbens E (1997) Japanese maple (Acer palmatum var. matsumurae, Aceraceae) recruitment patterns: seeds, seedlings, and saplings in relation to conspecific adult neighbors. Am J Bot 84(9):1294–1300PubMedView ArticleGoogle Scholar
  48. Wagner S, Collet C, Madsen P, Nakashizuka T, Nyland RD, Sagheb-Talebi K (2010) Beech regeneration research: from ecological to silvicultural aspects. For Ecol Manage 259(11):2172–2182View ArticleGoogle Scholar
  49. Wassie A, Teketay D, Powell N (2005) Church forests provide clues to restoring ecosystems in the degraded highlands of Northern Ethiopia. J Ecol Rest 23(2):131–132Google Scholar
  50. Zanne AE, Chapman CA (2001) Expediting reforestation in tropical grasslands: distance and isolation from seed sources in plantations. Ecol Appl 11:1610–1621View ArticleGoogle Scholar
  51. Zywiec M, Holeksa J, Wesolowska M, Szewczyk J, Zwijacz-Kozica T, Kapusta P (2013) Sorbus aucuparia regeneration in a coarse-grained spruce forest–a landscape scale. J Veg Sci 24(4):735–743View ArticleGoogle Scholar

Copyright

© The Author(s). 2016