Global Ecology and Conservation 9 (2017) 148–170

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Global Ecology and Conservation

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Original Research Article Temporal pattern of tree community dynamics in a secondary forest in southwestern Nigeria, 29 years after a ground fire Fatimoh Ozavize Ademoh a, Joseph Ikechukwu Muoghalu b,*, Brian Onwumerec a Department of Biological Sciences, Kogi state University, Anyigba, Nigeria b Department of Botany, Obafemi Awolowo University, Ile-Ife, Nigeria c Department of Biological Sciences, Nigerian Defence Academy, Kaduna, Nigeria

article info a b s t r a c t

Article history: The study determined successional replacement model among the functional groups in a Received 12 September 2016 secondary rain forest that was ravaged by a ground fire, 29 years ago. This was with a view Received in revised form 21 November 2016 to determining the stand temporal pattern of tree community dynamics in a moist tropical Accepted 21 November 2016 forest regenerating after fire disturbance. Two plots, 0.25 ha each, established in burnt and Available online 20 January 2017 unburnt parts of the forest immediately after the fire to study community dynamics in the forest were used for the study. In each plot, woody plant species ≥1 cm in girth and 1 Keywords: Fire m and above in height were completely enumerated, identified to species level, and girth Forest regeneration size measured at breast height (gbh). The number of species, genera and families were Dynamics established for each plot. The data collected were used to calculate species diversity indices, Climate basal area, species evenness, density, similarity and dissimilarity indices for the plots. Tree mortality and recruitment rates were calculated using data from this study and previous studies in the burnt plot in 1983, 1984, 1997 and 2008. Correlation and regression analyses were used to assess whether decadal changes in rainfall and temperature were the major drivers of changes in the forest after calculating decadal temperature and rainfall data for 29 years. The results showed that a total of 380 trees were present in the 0.25 ha burnt plot, representing 63 species, 46 genera and 25 families. Tree stem density decreased from 4332 stem ha−1 to 1520 stem ha−1 29 years after the fire. The species diversity (H1) which decreased to 2.50 in 2008 increased to 3.50 in 2012. The species evenness which peaked (0.80) in 1997 decreased to 0.48 in 2012. The basal area which increased to 20.18 m2 ha−1 in 1997 and dropped to 14.62 m2 ha−1 in 2008 has increased to 21.34 m2 ha−1 in 2012. Tree annual mortality rates which continued to decrease one year after the fire (−2.02% y−1 in 1984–1997, −5.16% y−1 in 1997–2008) had increased to 25.7% y−1 in 2008–2012). The annual recruitment rates continued to decrease since the fire, decreasing to the lowest rate of −25.7% y−1 in 2008–2012. There was a non-significant positive correlation between decadal mean minimum temperature, decadal mean maximum temperature and decadal mean annual rainfall and tree density but a non-significant negative correlation between these climatic data and basal area, species richness and species diversity. The changes in community parameters in the forest as it recovers from the fire disturbance followed the tolerance model of succession. It was concluded that changes in the floristic, structural character, mortality and recruitment rates were still going on in the forest, 29 years after the fire disturbance. © 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

* Corresponding author. E-mail address: [email protected] (J.I. Muoghalu).

http://dx.doi.org/10.1016/j.gecco.2016.11.005 2351-9894/© 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc- nd/4.0/). F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 149

1. Introduction

Disturbance is defined as any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment (Pickett and White, 1985). Disturbances play important role in determining the structure and functioning of ecosystems (Oliver, 1981; Paine and Levin, 1981; Pickett and White, 1985). They directly affect community and population dynamics by altering resource availability (Denslow et al., 1998) causing mortality and providing opportunities for recruitment (Canhan and Marks, 1985) and by influencing the relative competitive status of individuals (Sousa, 1984). Disturbances may also be important in maintaining species diversity, particularly in species rich ecosystems such as tropical forests (Connell, 1978; Huston, 1979; Glitzenstein et al., 1986) by providing occasional periods favourable to recruitment for long-lived organisms such as certain tree species (Warner and Chesson, 1985). Disturbance may be large scale disturbance or small scale. Large scale disturbance is caused by landslides and erosion, small scale disturbance is caused by tree fall (Richards, 1996; Whitmore, 1989, 1991). A forest community may be disturbed by fire, disease, flood or human activities such as timber harvesting and farming. Stand evolution trajectories are often altered dramatically by disturbances (Johnstone et al., 2010) but natural distur- bances rarely eliminate all structural elements from the affected stand (Franklin et al., 2002). Disturbances can create vastly contrasting quantities and types of living and dead structures that contribute to the ecological legacies associated with structurally diverse starting points for stand structural development (Johnstone et al., 2010). Such disturbance effects can propagate through the forest for decades at least (Gough et al., 2007) creating lags in heterotrophic respiration caused by delayed mortality or delayed decomposition (Harmon et al., 2011). The world’s tropical forests are undergoing major transformations due to deforestation, fragmentation, land use change and climate change. Throughout wet and dry tropical regions, secondary-regrowth forests are increasing in extent, economic importance, and conservation value (Brown and Lugo, 1990; Corlett, 1995; De Jong et al., 2001). Due to the transition from dominance by light-demanding pioneer tree species toward dominance by shade-tolerant species (Finegan, 1996), secondary-regrowth forests are expected to exhibit more rapid changes in tree species composition than mature forests. These successional dynamics will be important in determining how tropical forests respond to global climate change and land use/land cover changes. Disturbances are part of the dynamic fabric of ecosystems with strong spatial and temporal variability, creating a spectrum of legacies in forest structure, successional stages, and carbon cycle trajectory environment. Disturbances affect tree species composition by changing the species of hardwood to species with softer wood when the forest is repeatedly disturbed (Ter Steege, 2003). Disturbance might kill trees, resulting in direct and immediate carbon transfer to the atmosphere (in the case of fire) and a shift in structural elements from live to dead pools (e.g., leaves to litter, trees to logs, live roots to coarse woody debris, etc.). Fire is one of the most important agents of ecosystem disturbance. Many existing forest communities are at developmen- tal stages of natural succession, which eventually result in the restoration of the forest that were destroyed by lightening or man-caused fire (Taylor, 1973). Fire is a pervasive natural disturbance that controls many structural and functional properties of plant communities and it is a major agent initiating and terminating succession (Foster, 1985). Fire has other instantaneous effects, in particular the combustion of biomass, the loss of carbon to the atmosphere which exerts a significant radiative force (Randerson et al., 2006). Dry forest fire combusts forest floors and litter often smoulders rather than burn openly. Small plants including juvenile trees suffer greatest mortality and large ones suffer bole damage and may die within 2–4 years after the fire (Isichei et al., 1995). In recent years, fire incidence has increased in the tropical rain forest zones of the world, especially in deciduous forest where the dry season exceeds 3–4 months (Isichei et al., 1986; Kinnard and O’Brien, 1998). The effect of fire on rain forest is devastating (Kio and Nnaobi, 1983) since fire resistance, as found in savanna tree species, is lacking (Keay, 1959). Macchi et al.(2008) reported that the main reasons for forest losses have been wildfires, which have been severe, especially in Angola, southern Democratic Republic of Congo and Central African Republic. Fire affects forest regeneration directly through burning of seed, seedlings and trees and indirectly through its action on the soil (UNESCO, 1978). Many seeds and most seedlings are killed and trees are damaged by fire, but organs located a few centimetres under the soil may not be affected. Fire could stimulate seed germination of certain herbaceous and perennial shrubs, especially plants in the family Zingeberaceae and the shrub Chromolaena odorata which is the best indicator of disturbed humid vegetation in West Africa. Another effect of fire is the transformation of dry forest into savanna, once established such savanna are maintained by fire (Swaine, 1992). A large and growing proportion of forests has been and is being affected by major disturbances. Globally, secondary forests recovering from anthropogenic disturbances such as agriculture and wood harvesting cover an estimated 27 million km2 (Hurtt et al., 2011) and an estimated 1.2 million km2 are in use as forestry plantation (Kirilenko and Sedjo, 2007). In addition natural disturbances such as fires, storms, droughts, and insect outbreaks affect a significant proportion of earth’s ecosystem. Climate change is generally increasing the incidence of natural disturbances (Dale et al., 2001) including fires (Westerling et al., 2006) and biotic disturbances such as insect outbreaks (Evangelista et al., 2011; Hicke et al., 2012). Theory and models predict that future climate change may cause even more drastic changes (Westerling et al., 2011) depending on the future greenhouse gas emissions and the resultant shift in climate change (IPCC, 2007). The dynamic process of forest regeneration following disturbance is of key importance with ramifications on several scales. On a local level, forest recovery involves wholesale rearrangement of vegetation structure, carbon and nutrient 150 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 cycling, ecosystem physiology and community structure (Anderson-Teixeira et al., 2013). On a landscape level disturbance– recovery dynamics play an important role in the maintenance of species diversity, as different species use forests of different ages as habitat patches (Anderson-Teixeira et al., 2013). On a regional to global level, secondary forests are consequential for their role in climate regulation. Forests recovering from disturbance (secondary forests) are strong carbon sinks and play important role in the global carbon cycle (Running, 2008; Pan et al., 2011), for instance, in recent years (2000–2007) regrowth tropical forests following agricultural abandonment took up estimated 1.7 P g C yr−1 (Pan et al., 2011) which is equivalent to about 20% of annual global fossil fuel emission. These secondary forests also influence climate through biophysical mechanisms (Liu et al., 2005; Maness et al., 2012; O’Halloran et al., 2012). In early 1983, there was fire incident that burnt a part of the secondary rain forest within the Biological Gardens of Obafemi Awolowo University, Ile-Ife, Nigeria. The fire occurred after species listing and girth measurements for woody species had been completed in a 50 m × 50 m area of the forest demarcated in January 1983 for a baseline study of tree girth increases and litter deposition patterns. The studies carried out after the fire incidence (Isichei et al., 1986; Odiwe and Muoghalu, 2001; Muoghalu, 2006; Nwosu, 2010) showed changes in tree species composition of the forest following the ground fire. With recent proliferation of forest fires and the widespread of the fires throughout the moist tropical forests zones of the world, it is necessary to understand the dynamics of tropical forest undergoing natural regeneration after it has been disturbed by fire. The present study, therefore, investigated stand temporal pattern of tree community dynamics in the secondary forest at Ile-Ife, Nigeria 29 years after a ground fire. The study also assessed the effect of decadal changes in rainfall and temperature on species composition and structure of the forest.

2. Materials and methods

2.1. Study area

The study was carried out in a secondary rain forest within the Biological Gardens of Obafemi Awolowo University, Ile-Ife, Nigeria. Ile-Ife lies within the latitudes 7◦ 30′ to 7◦ 35′ N and longitudes 4◦ 30′ and 4◦ 35′ E. Two sample plots, one in the burnt part of the forest and another in the unburnt part of the forest were used for this study. The burnt plot (7◦ 31′ N, 4◦ 31′ E, 306 metres above sea level (a.s.l)) is on the base of a Hill and the unburnt plot (7◦ 32′, 4◦ 31′ E, 326 m a.s.l.) is on the slope of the Hill. The original vegetation of the area is lowland rain forest as the climax vegetation (Keay, 1959). The forest subtype is dry deciduous forest (Onochie, 1979). White(1983) described the vegetation as Guinea Guineo-Congolian drier forest type. There are two prominent seasons in Ile-Ife area, the rainy season and the dry season. The dry season is short usually from November to March and the longer rainy season prevails during the remaining months. Recent rainfall and temperature data (2002–2012) of Ile-Ife showed the mean annual rainfall to be 1647 mm and mean annual temperature range from 20.3 to 28.6 ◦C (Meteorological Stations: Departments of Physics and Engineering Physics; Crop Production and Protection and Institute of Ecology and Environmental Studies, Obafemi Awolowo University, Ile-Ife). Rainfall shows two peaks, one in July and the other in September. The relative humidity in the early morning is generally high, usually over 90% throughout the year (Hall, 1969). At mid-day it is rather lower, around 80% in the wet season to as low as 50%–60% in the dry season (Hall, 1969). The area is underlain by rocks of the basement complex, which are of precambrian age (Wilson, 1922; De Swardt, 1953). The soil has been classified as Lixisols (FAO/UNESCO, 1974) and Ultisols (USDA, 1975). The soil has low cation exchange capacity and low water holding capacity (Ayodele, 1986).

2.2. Data collection

2.2.1. Sampling procedure Two sample plots, 50 × 50 m each, were used for this study, the one established in the burnt part of the forest by Isichei et al.(1986) in 1983 before the ground fire and the second plot in the unburnt part of the forest established after the fire. Woody species (shrubs and trees) 1 m and above in height, were completely enumerated, identified to species level and labelled with a numbered permanent plastic tag nailed against each identified species. Their girth sizes were measured at breast height (gbh 1.3 m or above all buttresses or stem deformities) for the trees that are 3 m and above in height and at midpoint for those less than 3 m in height. Climbers were removed before girth measurements were taken.

2.2.2. Data processing and statistical analyses Species identification and nomenclature followed the Flora of West Tropical Africa (Hutchinson and Dalziel, 1954–1972)) and Trees of Nigeria (Keay, 1989). For each plot, the number of tree species (species richness), genera and families were 1 ∑ established. Tree species diversity was calculated using Shannon and Weiner(1949) Formula: H = − ni/N In ni/N; where ni is the importance value for each species, N is total importance value. Species evenness was calculated as Pielou’s evenness index J1 = H1/In S; where S is the total number of species. J1 is constrained between 0 and 1. The less variation in communities between the species, the higher J1 is. Basal area (m2 ha−1) was calculated for each tree species in each plot. The girth measurement for each individual tree was used to calculate the basal area using the formula: Basal area (m2 ha−1) = C 2/4 ∏, where C = girth size (circumference) in F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 151 metres. The total basal area for each species was determined by adding the basal areas of individuals of the species and the total basal area for each plot was calculated by adding the basal areas of all the species in the plot. Mortality was considered as the number of dead trees. The data that were collected from this study and those of the previous studies in 1983 (before the fire), 1984 (1 year after the fire), 1977 (14 years after the fire) and 2008 (25 years after the fire) were used to estimate the mortality and recruitment rates of the trees. Estimated mean annual rate of mortality was calculated using the logarithmic model (Log model) (Lieberman and Lieberman, 1987; Swaine et al., 1987a, b) which assumes that mortality declines logarithmically with time. Log annual mortality rate was calculated as:

M = 100(logen0 − logent )/t; where n0 is the number of first tree enumeration; nt is the number of trees surviving at the next enumeration; t is the time interval (years later).

The mean annual recruitment was calculated using the formula: r = 100(logent − logeno)/t; where no is the number of first tree enumeration; nt is the number of trees surviving at the next enumeration; t is the time interval (years later). All individuals of each tree species 1 m and above in height at each enumeration year were used for these calculations. In order to determine ecological meaningful dynamics patterns, the tree species in the plot were classified into 5 regeneration guilds adapted by Lieberman and Lieberman(1987) as (1) understory, (2) subcanopy, (3) canopy shade-bearer, (4) canopy light-demander, and (5) pioneer. The tree species in the burnt plot for each year was also classified into successional guild categories as : Pioneer, Early succession species, Late succession species, and climax following Hawthorne(1995) to verify if there is a relationship between the succession guilds and the forest regeneration after the fire disturbance. The various dispersal modes of the seeds of the tree species: animal and abiotic factor (wind) was determined according to Hawthorne(1995). Leaf phenology was classified as deciduous and evergreen. The confidence limits of all data were set by student t-test at 95% confidence interval. The data collected from the present study were compared with the data obtained from previous studies (1983, 1984, 1991 and 2008) in the forest. The same method of complete enumeration of trees ≥1 m in height within the burnt plot, that was used for plant enumeration in previous studies was used for data collection in the present study in 2012. To estimate compositional turnover within communities (i.e., change in a plot over the 29 years period) the similarity of the burnt plot from 1983 to itself for the sampling periods (1983, 1984, 1997, 2008 and 2012) was calculated using Sorensen similarity index. The Sorensen coefficient based on presence–absence data was applied to measure the similarity or dissimilarity between the species recorded at different sampling periods. The Sorensen similarity index ISS = 2C/A + B; where A is the number of species recorded in a year, B is the number of species recorded in another year and C is the number of shared species. Values near 1 indicate nearly identical community composition between time periods and values near 0 indicates that communities have very little compositional overlap between the periods. Turnover was defined as the degree of compositional dissimilarity between sampling periods within an individual plot. Therefore, turnover was calculated as 1 –ISS. Climate data (rainfall and temperature) for 29 years collected from Meteorological Stations on the campus were used to assess whether changes in rainfall and temperature are the major drivers of the changes in the forest using correlation and regression analyses after calculating decadal rainfall and temperature.

3. Results

3.1. Changes in floristic composition, regeneration and successional guilds in the forest

A total of 380 plants per 0.25 ha were recorded in 2012, representing 63 species, 46 genera and 22 families while Apocynaceae, Euphorbiaceae, Meliaceae, Moraceae, Pandaceace, Sapindaceae, and Ulmaceae were the dominant families. They have been changes in the dominant plant families in the plot when compared with previous survey in 2008 which showed predominant families as Apocynaceae, Bignonaceae, Euphorbiaceae, Lecyhidaceae, Moraceae, Pandaceae, Papilonoidae and Sapindaceae (Table 1). There have been changes in the abundance of the tree species within the plot in the different survey periods (Table 3). The most abundant species in the plot in 1983 before the ground fire were Funtumia elastica (384), Manihot glaziovii (136) and Pycnanthus angolensis (120). In 2012, twenty-nine years after the ground the most abundant species in the plot were Funtumia elastica (136), Microdermis puberula (152) and Trilepisium madagascariense (116) (Table 1). The rare species of the plot which are species having only one individual each include Albizia species, Bighia species, Canthium vulgare, Celtis species, Chassalia kolly, Chrysophyllum albidum, Cola acuminata, Cola nitida, Deinbollia pinnata, Dialium guineense, Ficus species, Lonchocarpus erinaceous, Mallotus mildbraedii, Mellettia species, Myrianthus arboreus, Piptadeniastrum africanum, Pterocarpus species, Rauvolfia vomitera, Sterculia tragacantha, Tabernaemontana pachysiphon and Terminalia superba in 2012 (Table 1). The rare species make up 5.5% of the total number of the species 29 years after the ground fire. The changes in abundance and rarity of species in the plot have also been reflected in the percentage contributions of the most abundant and rare species to the total abundance of species in the plot over the years. The most abundant species made up 42.2% of stem density in 1983, 85.7% in 1984, 54.2% in 1997, 51% in 2008 and 32.9% in 2012; while the rare species made up 1.3% in 1983, 1.6% in 1984 (1 year after the ground fire), 2.8% in 1997 (14 years after the fire), 2.5% in 2008 and 5.5% in 2012 (29 years after the fire) of all woody species in the plot. 152 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 ) ) Continued on next page ( 1 − ) Recruitment rate (%yr 1 − 1983–’84 1984–1997 1997–2008 2008–2012 1983–1984 1984–1997 1997–’08 2008–’12 29 yrs AF (2012) ) Mortality rate (%yr 1 − 25 yrs AF (2008) 14 yrs AF (1997) ) and recruitment rates of tree species in a burnt plot in a lowland secondary forest in Ile-Ife, Nigeria. 1 − 1 yr AF (1984) BFF (1983) ), mortality rate (%yr 1 − CLSMIMMIM –MIM –MIM –EUP – –EUP 44 –SAP – –APO – 32PPL 8 – 4MOR 24 20 –ANN – – –EUP 20 – 4 76 40 28APO – – – 28 – 8PPL 288CSL 8 8 – – 12 –SAP 44 20 –SAP – – – –SAP 92 – 876 – 4BOM – – – – 20EUP 4 32 4 64 4 –EUP 16 48 16EUP 72 – – – 20 – – –POL 8 – 60 – 16 8 –EUP 170.5 – – 4CAR – 68 – 8 –ULM 12 – – – – – – – –ULM – – 12 108 –ULM 4 – – – – 26.7 –RUB – – 24 128 4 – 4SAP – 91.6 12 12.6 27.2 24 – 4.97 – –RUT 28 – – 32 – – – 6.5ANN – – – – 4 160.9 –STR 84 – – 4 10.7 – – – – 7.96STR – – – – – – 30.3STR – 16.0 299.6 – – 12 – 36 – – 4SAP – 51.99 – 12 80 – 8 –CSL – – 2.2 – – – – – – –DCP – 100.1 44 – – – – – – 4 –THY – – 207.9 5.6 – 8 8 8 –RUB 10.7 – – 34.7 16 44.8 – – 346.6RUB – – – 69.3 - 44 – – 8 –EBN – 17.3 – – 4 – 12.6 10.7 4 – 23.0EBN – 74.9 – – – – – 12 – – – 28 15.42 – 12 – – 5.3 138.6 68 – – – – – – – – 4 – – – 32 33.7 – 43.6 – – 4 – – – – – – 25.6 5.3 – – – – 20 – 4 4 – – – 18.9 – – – 4 – – – – 18.8 10.1 – 10.5 – 12 – 4 – 204 – 248.5 79.5 24.5 – – – – – – 12.6 4.64 10.7 34.7 – 12.6 – – – 12 – 24.4 4 – 34.7 – – 4 – 138.6 – – – 8 – – 4 4 387.1 4 – – – – – – 138.6 8 – – – 10.7 – – – – 20 27.23 248.5 – 4 2.8 – 20 – 13.7 – – – – 14.6 – – – – – – – 51.99 – 59.9 – 5.3 10.7 31.2 – – – – 207.9 – – – – 5.8 – – – – – 59.9 – 10.7 – – – – 16.2 8.9 – – – – – – – 138.6 – – – – – – – – – – 317.8 – – – 10.7 – – – – – – 27.5 – – – – – – – – – 12.8 – – 34.7 – – – – – 27.6 34.4 10.7 – – 33.7 – 34.4 – – 18.9 – – 27.5 133.0 – – – – – – – – – – – – – – 34.4 138.6 51.98 16.0 34.7 – – – – – 18.9 34.7 19.1 31.3 52.0 – 52.0 36.2 – – 74.9 74.9 3.7 138.6 – 4.6 – 26.7 – – – – – 12.6 138.6 – – 16.8 34.7 – – – 22.6 – – – – – 34.7 10.7 – – 12.6 6.3 16.0 27.2 12.6 – – 27.2 – – – – – – 1983, 1984, 1997 and 2008; (1983, 1984) Isichei et al. ( 1986 ); (1997) Odiwe and Muoghalu ( 2003 ) and (2008) Nwosu ( 2010 ). SpeciesAfzelia africana Family Density number of stem per hectare (ha Albizia adianthifolia Albizia ferruginea Albizia species Albizia zygia Alchornea cordifolia Alchornea laxiflora Allophylus africanus Alstonia boonei Angylocalyx oligophyllus Antiaris africana Annona tenuifolia Antidesma membranaceum Apocynaceae species Baphia nitida Berlinia grandiflora Blighia sapida Blighia species Blighia unijugata Bombax buonopozense Bridelia atroviridis Bridelia ferruginea Bridelia micrantha Carpolobia lutea Canthium vulgare Carica papaya Celtis mildbraedii Celtis zenkeri Celtis species Chassalia kolly Chrysophyllum albidum Citrus species Cleistopholis patens Cola acuminata Cola millenii Cola nitida Deinbollia pinnata Dialium guineense Dichapetalum species Dicranolepis grandiflora Dictyandra arborescens Dictyandra involucrata Diospyros monbuttensis Diospyros nigerica Table 1 Species composition, density (ha Source: F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 153 ) Continued on next page ( EUPAGV –AGVPLM –SAP – –SAP 32EUP – 16MOR – –MOR 8 – 4MOR – –MOR – 28 –MOR 64 – –MOR – – 4APO – 4 – – 20APO – 72 4TIL – 12 –TIL – 384 – 4 8ANN – 8 12 – 44APO 20 4 – 152 8IRV 32 – –Rub 4 48 – 20 16 28SAP 8 4 20 56 164 4 4 – – – – – –ANA – 28 – –ANA 8 4 – – – –SAP – 208 20 138.6 – –PPL – – – – 12 – – 4STR – – 36 4EUP 16.0 – – – – – 64SPO 136 – 8 – – – 116.3 –EUP 16 – 12 – – – – 8EUP 8 – 4 – – 32 – –EUP 3.93 – – 20 92.7 12 – –EUP – – – – – – – 124PAN – – 34.7 – 32.0 – –MOR – – – – 136 – – – – – – –MOR – – 12.6 – – 101.2 – –PPL 4 – – – 252 – – 2584 –ANN – – – 6.3 277.3 12 – –RUB 38.5 5.3 – 34.7 52 69.3 – – – – – –RUB 31.5 – 53.9 – – – 212 –MOR 76 – 4.3 – 4 – 34.7 83.3 – – 160.9MOR – – – – – 12 10.7 10.7 – –LCY 12.6 – – 15.0 4 – – – 104 10.6 –LCY 12 – 20 – – – 10.7 – – – 8.6 4LCY 81.1 28 – – – – – – – 138.6 –BIG – – – – – – – – 120 – – 41.9 –OLA – 476 – – – – 8 – – – –OCH 12 – – – 248.5 – 40 18.9 8 4 10.7 – –RUB – 96 – – – – – – – –RUB 120 – – – 34.7 – – 32 248.5 4 152 – 7.5 – 8 – – 28 – 16.0 16 14.0 – – 12.6 4 0.58 – – – 52.0 – 18.9 17.7 – 8 – 4 – – – – – – 74.9 60 27.2 12.6 – 52 – – 4 – — – 4 – – – – – – 4 – 2.2 220 – – 10.7 – 4 – – 19.2 30.0 – – – 8 – – – – 4 – – 34.7 – 8 27.5 395.1 – 138.6 152 4 – – – – 300 – – – – – 18.9 21.5 8 – – – 4 – – – – – – – – – 20 – – – – 28 – – – 20 – – 44 12.8 4 34.7 – – – 52.0 – – – – – – 8 – – – 248.5 34.7 – 15.8 18.9 86.6 – – 16.0 8 – – – – – 23.0 – 91.6 – 294.4 28.5 – – – – – – – – – – 64.5 – – – – 17.3 – – – – – – – 6.3 – – – – – 6.3 – – – – – – 6.3 – – – – 333.2 62.1 – – – – – 34.7 – 10.7 – – – – – – – 6.3 – – – – – 12.6 35.7 – 34.7 62.1 – – – – – – 36.8 – 12.6 – – 48.0 – 42.3 – – 13.8 – 34.7 12.6 – 30.3 – – – – – – – – – – 16.0 30.8 – – – – – 22.9 – 34.7 – – 16.0 – 86.6 34.7 16.0 – – 138.6 – 52.0 – 20.2 30.4 – – – 16.0 – – 12.6 – 34.7 – 2.8 9.8 17.3 12.6 – – – – 16.0 10.7 – – 17.3 – – 27.5 8.3 – – – – 12.6 – 18.9 – – ) continued Discoglypremna caloneura Dracaena arborea Dracaena mannii Elaeis guineensis Eriocoelum kerstingi Eriocoelum macrocarpum Erythrococca anomala Ficus capensis Ficus exasperata Ficus mucuso Ficus species Ficus sur Ficus vogeliana Funtumia africana Funtumia elastica Glyphaea brevis Grewia species Hexalobus crispiflorus Holarrhena floribunda Irvingia gabonensis Keetia vulgae Laccodiscus pseudostipularis Lannea species Lannea welwitschii Lecaniodiscus cupanioides Lonchocarpus sericeus Leptonychia pubescens Macaranga hurifolia Malacantha alnifolia Mallotus mildbraedii Mallotus oppositifolius Mallotus subulatus Manihot glaziovii Microdesmis puberula Milicia excels Millettia species Millettia thonningii Monodora tenuifolia Morinda lucida Morinda morindoides Morus mesozygia Myrianthus arboreus Napoleonaea imperialis Napoleonaea vogelii Napoleonaea species Newbouldia laevis Olax subscorpioidea Ouratea flava Oxyanthus species Pauridiantha floribunda Table 1 ( 154 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 25.7 − -2.17 5.17 − – 16.0 – – = 5.17 25.7 74.5 − 74.5 2.17 − EUPEUPMIM – –PPL –RUB –RUB 4 16PPL – –MYS –APO – 4 –RUB 120 – –RUB 32 8 –CEL – 28 –BIG – –ANN 4 – – – –STR – – –APO 4 12 8 4 – 20 –COM 12 – – – 8MIM 8 4 – 4STR 4 4 8 4 – 16ULM 20 8 – 100MEL 8 4 – –MEL – – – – – –MEL – 16 32 4 – 8 –MEL – – – 12 – 4MEL – – 4MOR – – – 138.6 – – 4 21.3 12 – – 36 – 4MEL – 20 – 145.5 – – 4 – – – – – – – 4 60 207.9 – 12.6 9.6 – 12 4 16 24 – 8 – 6.3 – 4 4 – – – 4 – – – – – 36 – 16 8 – 64 76 40.5 24 – – 4 34.7 – 16 – 91.6 3.7 – 4 10.7 – – 8 – 100 – – 16.0 56 17.3 304 – – 277.3 299.6 34.7 16.0 – – 5.3 138.6 8 – 17.3 34.7 – 44 – 41.9 17.3 – – – – 116 346.6 138.6 – – – – – 10.7 12 – – 16.0 69.3 – – – – – – – – – – 51.1 – – – 10.0 – – – – – – – – 219.7 – – – 8.5 – – – – – – – – – 138.6 – – – – – – – – – 6.3 – – 12.6 207.7 – – 10.7 – 12.6 – – 33.4 – – – – 18.9 35.4 – 18.9 – – – – 69.3 – – 12.6 – – – – – – – 17.3 24.1 – – – 20.5 19.1 – – – 12.6 – 19.1 18.9 – – – – 34.7 – – – 31.5 – – – 6.3 – – – 12.6 – 0.59 – – 16.0 14.2 27.6 5.3 – – – 25.2 9.9 6.3 12.6 9.3 – – – – – – – 62.1 – APORUTRUT 36 – – 12 – – 8 – 4 – 4 – – – – 109.9 – 3.1 – 18.9 – – – 12.6 34.7 – – – – – – – 10.7 – 12.6 – – – ) continued Phyllanthus odontadenius Phyllanthus species Piptadeniastrum africanum Pleiocarpa species Psychotria species Psydrax arnoldiana Pterocarpus species Pycnanthus angolensis Rauvolfia vomitoria Rothmannia longiflora Rubiaceae species Salacia pallescens Spathodea campanulata Spondias mombin Sterculia tragacantha Tabernaemontana pachysiphon Terminalia superba Tetrapleura tetraptera Theobroma cacao Trema orientalis Trichilia heudelotii Trichilia megalantha Trichilia monadelpha Trichilia prieuriana Trichilia species Trilepisium madagascariense Turraea vogelii Voacanga africana Xylopia species Zanthoxylum rubescens UnidentifiedTotal – – 1516 3192 – 2408 4252 – 1520 12 – – – – – – – 62.-1 Table 1 ( Note: Families are given as mnemonic three letter acronym following Weber ( 1982 ). F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 155

Table 2 Species composition, family, regenerational guild, successional status, mode of dispersal, distribution range and leaf phenology in a burnt lowland sec- ondary forest in Ile-Ife, Nigeria. s/n Plant species Family Regenerational Successional Mode of Leaf guild status dispersal phenology 1 Afzelia africana CLS Canopy Early Abiotic Deciduous 2 Albizia adianthifolia MIM Canopy Early Wind Deciduous 3 Albizia ferruginea MIM Canopy Early Wind Deciduous 4 Albizia species MIM Canopy Early Wind Deciduous 5 Albizia zygia MIM Canopy Early Wind Deciduous 6 Alchornea cordifolia EUP Subcanopy Early Animal Evergreen 7 Alchornea laxiflora EUP Subcanopy Pioneer Animal Evergreen 8 Allophylus africanus SAP Subcanopy Pioneer – Deciduous 9 Alstonia boonei APO Canopy Pioneer Wind Deciduous 10 Angylocalyx oligophyllus PPL Understorey – Evergreen 11 Antiaris africana MOR Canopy Early Birds/Bat/primate Deciduous 12 Annona tenuifolia ANN Subcanopy – – 13 Antidesma membranaceum EUP Understory Pioneer Birds – 14 Apocynaceae species APO – - Animal – 15 Baphia nitida PPL Understorey Late Other animals Evergreen 16 Berlinia grandiflora CSL Canopy – Primate Evergreen 17 Blighia sapida SAP Canopy Early Animal Evergreen 18 Blighia species SAP Canopy – Primate, Abiotic Evergreen 19 Blighia unijigata SAP Canopy Late Primate Evergreen 20 Bombax buonopozense BOM Canopy Pioneer Wind Deciduous 21 Bridelia atroviridis EUP Canopy Pioneer Bird Deciduous 22 Bridelia ferruginea EUP Canopy – – Deciduous 23 Bridelia micrantha EUP Canopy Pioneer Bird Deciduous 24 Carpolobia lutea POL Understory – Primate Evergreen 25 Canthium vulgare EUP Canopy Pioneer Other animals – 26 Carica papaya CAR Understorey – Animal Evergreen 27 Celtis mildbraedii ULM Canopy Late Bird/Primate Deciduous 28 Celtis zenkeri ULM Canopy Early Bird/Primate Deciduous 29 Celtis species ULM Canopy – Primate Deciduous 30 Chassalia kolly RUB - – – – 31 Chrysophyllum albidum SAP Canopy Late Primate Evergreen 32 Citrus species RUT Canopy – – Deciduous 33 Cleistopholis patens ANN Canopy Early Primate, Other Deciduous animals 34 Cola acuminate STR Canopy – Primate Evergreen 35 Cola millenii STR Canopy Early Primate Evergreen 36 Cola nitida STR Canopy Late Primate Evergreen 37 Deinbollia pinnata SAP Understorey Late – Deciduous 38 Dialium guineense CSL Canopy Savanna Animal – 39 Dichapetalum species DCP Understorey – – – 40 Dicranolepis grandiflora THY Canopy – – – 41 Dictyandra arborescens RUB Canopy Late – – 42 Dictyandra involucrate RUB Canopy – – Evergreen 43 Diospyros monbuttensis EBN Understorey Late Primate Deciduous 44 Diospyros nigerica EBN Understorey – Primate Deciduous 45 Discoglypremna caloneura EUP Canopy Pioneer Birds – 46 Dracaena arborea AGV Canopy Pioneer Other animals – 47 Elaeis guineensis PLM Canopy Pioneer Giant rat/animal Evergreen 48 Eriocoelum kerstingi SAP Canopy – - – 49 Eriocoelum microcarpum SAP Canopy – - – 50 Erythrococca anomala EUP Understorey – – – 51 Ficus capensis MOR Canopy Pioneer Bat – 52 Ficus exasperate MOR Canopy Pioneer Animal/Birds Deciduous 53 Ficus mucuso MOR Canopy Pioneer Animal/Birds – 54 Ficus species MOR Canopy Pioneer Bat/Primate – 55 Ficus sur MOR Canopy Pioneer Bat Evergreen 56 Ficus vogeliana MOR Canopy – Birds – 57 Funtumia africana APO Canopy Early Wind – 58 Funtumia elastic APO Canopy Early Wind Evergreen 59 Glyphaea brevis TIL Understorey Late – Evergreen 60 Grewia species TIL Understorey – – Evergreen 61 Hexalobus crispiflorus ANN Canopy Late – – 62 Holarrhena floribunda APO Canopy Pioneer Wind Deciduous 63 Irvingia gabonensis IRV Canopy Early Rodent, duiker Evergreen 64 Keetia vulgare Rub – – – (Continued on next page) 156 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Table 2 (continued) s/n Plant species Family Regenerational Successional Mode of Leaf guild status dispersal phenology 65 Laccodiscus pseudostipuaris SAP Canopy – – – 66 Lannea species ANA Canopy – Primate Deciduous 67 Lannea welwitschii ANA Canopy Pioneer Primate Deciduous 68 Lecaniodiscus cupanioides SAP Canopy Late Primate – 69 Lonchocarpus erinaceous PPL – – – 70 Leptonychia pubescens STR Understorey Late Birds – 71 Macaranga hurifolia EUP Subcanopy Pioneer Primate, Other – animals 72 Malacantha alnifolia SPO understorey Pioneer – – 73 Mallotus mildbraedii EUP – – – 74 Mallotus oppositifolius EUP Understorey Late Other animal – 75 Mallotus subulatus EUP – – – 76 Manihot glaziovii EUP Understorey Pioneer – Evergreen 77 Microdesmis puberula PAN Understorey Late Primate, Other – animals 78 Milicia excels MOR Canopy Pioneer – Deciduous 79 Millettia thonningii PPL Canopy – Regenerate by Deciduous root sucker 80 Monodora tenuifolia ANN Canopy Late Other animals – 81 Morinda lucida RUB Understorey Pioneer Birds Evergreen 82 Morinda morindioides RUB Understorey – Primate, Other – animals 83 Morus mesozygia MOR Canopy Pioneer Bird Deciduous 84 Myrianthus arboreus MOR Canopy Late Primate, Other Deciduous animals 85 Napoleona imperialis LCY Understorey – Abiotic Evergreen 86 Napoleona vogelii LCY Understorey Late Abiotic Evergreen 87 Napoleona species LCY Understorey – Abiotic Evergreen 88 Newbouldia laevis BIG Subcanopy Pioneer Abiotic Evergreen 89 Olax subscorpioidea OLA Understorey Late Primate, Other Evergreen animals 90 Ouratea flava OCH Understorey Swamp – Evergreen 91 Oxyanthus species RUB Understorey Late – – 92 Pauridiantha floribunda RUB Understorey – – – 93 Phyllanthus odontadenius EUP Understorey – Animal – 94 Phyllanthus species EUP Understorey – Animal – 95 Piptadeniastrum africanum MIM Canopy Early Wind Evergreen 96 Pleiocarpa species PPL Understorey – – Evergreen 97 Psychotria species RUB Understorey – – – 98 Psydrax arnoldiana RUB Canopy Pioneer – – 99 pterocarpus species PPL Canopy – Abiotic Deciduous 100 Pycnanthus angolensis MYS Canopy Early Primate, Other Evergreen animals 101 Rauvolfia vomitoria APO Understorey Pioneer Primate, Other Evergreen animals 102 Rothmannia longiflora RUB Subcanopy Late Other animals – 103 Rubiaceae species RUB – – – 104 Salacia pallescens CEL Subcanopy – – – 107 Spathodea campanulata BIG Canopy – Wind Deciduous 108 Spondias mombin ANN Canopy – Bat Deciduous 109 Sterculia tragacantha STR Canopy Pioneer Animal Deciduous 110 Tabernaemontana APO Canopy Late – Evergreen pachysiphon 111 Terminalia superba COM Canopy Pioneer Wind Deciduous 112 Tetraptera tetrapleura MIM Canopy – – – 113 Tetrapleura tetraptera MIM Canopy – Abiotic, Other Evergreen animals 114 Theobroma cacao STR Subcanopy – Big birds – 115 Trema orientalis ULM Subcanopy Pioneer Birds Semideciduous 116 Trichilia heudelotii MEL Canopy – Animal Evergreen 117 Trichilia megalantha MEL Canopy Early – Evergreen 118 Trichilia monadelpha MEL Understorey Early – Evergreen 119 Trichilia prieureana MEL Understorey Early – Evergreen 120 Trichilia species MEL Canopy Early Primate Evergreen 121 Trilepisium madagascariense MOR Canopy Early Bats and Birds Evergreen 122 Turraea vogelii MEL Understorey – – Evergreen 123 Voacanga africana APO Canopy Pioneer – – 124 Xylopia species RUT Canopy Late Primate – 125 Zanthoxylum rubescens RUT Understorey Pioneer – – Note: Families are given as mnemonic three letter acronym following Weber(1982). F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 157

Table 3 Changes in the number of species regeneration and successional guilds in the forest after 29 years. AF = after fire. Parameter Year 1983 Before fire 1984 1 yr AF 1997 14 yr AF 2008 24 yr AF 2012 29 yr AF Number of species 37 40 67 74 63 Successional guild Pioneer species (%) 34.3 40.0 23.9 32.6 28.6 Early successional species (%) 21.6 22.5 25.4 21.6 23.8 Late successional species (%) 10.8 10.0 23.4 24.4 16.4 Unknown (%) 35.1 27.5 26.9 21.6 30.2 Regenerational guild Canopy (%) 70.3 67.5 58.2 64.9 63.5 Subcanopy (%) 10.8 7.5 7.5 6.3 3.8 Understorey (%) 18.9 20.0 28.5 27.0 17.5 Unknown (%) – 5.0 6.0 2.7 5.9

Table 4 Changes in some structural and diversity parameters of the burnt plot of a secondary lowland rain forest in Ile-Ife, Nigeria in 1983 before the fire and in 1984, 1997, 2008 and 2012 after the ground fire. Source: 1983, 1984, 1997, 2008 data: (1983 and 1984) Isichei et al.(1986); (1997) Odiwe and Muoghalu(2003); (2008) Nwosu(2010). Parameters Enumeration year 1983 BFF 1984 1 yr AF 1997 14 yr AF 2008 25 yr AF 2012 29 yr AF Stem density (stem ha−1) 1516 3192 2456 4332 1520 Basal area (m2 ha−1) 21.92 13.35 20.18 14.62 21.34 Species richness (0.25 ha−1) 37 40 67 74 63 Number of genera 37 37 53 62 46 Number of families 22 22 23 29 22 Shannon–Weiner index (H−1) 2.98 1.07 3.37 2.50 3.50 Pielou’s index 0.83 0.20 0.80 0.58 0.48 BFF = before fire; AF = after fire.

Seven new species established in the plot in 2012. These were Bridelia ferruginea, Funtumia africana, Lannea welwitschii, Lonchocarpus erinaceous, Mallotus mildbraedii, Mallotus subulata and Millettia species. There were fluctuations in the species richness, regeneration and successional guilds as the forest regenerated from the fire disturbance. Before the fire, canopy species and pioneer species were dominant. One year after the fire canopy and pioneer species were still dominant. Fourteen years after the ground fire canopy and early successional tree species were dominant and twenty-five and twenty-nine years after the fire canopy and pioneer species were dominant tree species in the plot (Tables 2 and3). In 1983 (before the fire) the species richness was 37 (Tables 3 and4) of which 70.3% was canopy species, 10.8% was subcanopy species and 8.9% was understorey. In 1984 (one year after the fire) species richness was 40 (Tables 3 and4) of which 67.5% was canopy species, 7.5% subcanopy species, 20.0% understorey and 5.0% was unknown. In 1997 (14 years after the fire) species richness was 67 (Table 4) of which 58.2% was canopy species, 7.5% subcanopy species, 28.5% understory and 6.0% was unknown (Table 3). In 2008 (25 years after the fire) the species richness was 74 (Table 3) of which 64.9% was canopy species, 6.3% subcanopy species, 27.0% understorey and 2.7% unknown (Table 3). In the present study in 2012 (29 years after the fire), the species richness was 63 (Table 3) of which 63.5% was canopy species, 3.8% subcanopy species, 17.5% understorey and 5.9% was unknown (Table 3). Thus, the species richness, canopy species and understorey species were highest 25 years after the fire in 2008 and have started decreasing 29 years after (2012). The plant species recorded in these periods were also classified into three successional guilds with the following percentages as follows: In 1983, 34.3% was pioneer species, 21.6 early successional species, 10.8% late successional species and 35.1% was unknown (Tables 2 and3). In 1984, 40.0% was pioneer species, 22.5% early successional species, 10.0% late successional species and 26.9% was unknown (Tables 2 and3). In 1997, 23.9% was pioneer species, 25.4% early successional species, 23.4% late successional species and 26.9% was unknown (Tables 2 and3). In 2008, 32.4% was pioneer species, 21.6% early successional species, 24.3% late successional species and 21.6% was unknown. In 2012, 28.6% was pioneer species, 23.8% was early successional species, 16.4% was late successional species and 30.2% was unknown (Tables 2 and3). Thus, the pioneer species which reached a peak immediately after the fire generally started decreasing in percentage while early and late successional species continued to increase as the forest recovered from the fire disturbance. The species classified as unknown are species which are not classified into any categories in the schemes of classification used.

3.2. Mode of dispersal of the tree species in the forest

The tree species were grouped into two dispersal modes of their fruits and seeds, namely, animals (e.g., primate, rodent, birds, bat, and other animals) and abiotic vectors (wind, gravity, etc.). In 1983 survey, 45.0% of the tree species had their fruits and seeds dispersed by animals, 21.6% dispersed by abiotic vectors and the mode of dispersal of 34.3% was unknown. In 1984, 158 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

60.0% was dispersed by animals, 22.5% was dispersed by abiotic factor and the mode of dispersal of 18.0% was unknown. In 1997, 50.8% was dispersed by animals, 17.9% was dispersed by abiotic factors and the mode of dispersal of 31.35 of the species was unknown. In 2008, 60.8% of the species was dispersed by animals, 13.2% was dispersed by abiotic vector and the mode of dispersal of 25.7% unknown. In 2012, 57.1% of the species was dispersed by animals, 17.5% was dispersed by abiotic vectors and the mode of dispersal of 25.4% was unknown (Table 2). Generally, the seeds and fruits of the tree species in the forest were dispersed by animals and on average, increasing numbers of the tree species had their fruits and seeds dispersed by animals as the forest recovered from the fire disturbance.

3.3. Leaf phenology of tree species

The leaf phenology of the tree species, described as deciduous and evergreen, showed that in 1983, 37.8% of the species was deciduous, 35.3% was evergreen and the leaf phenology of 27.3% was unknown (Table 2). In 1984, 35.0% of the species was deciduous, 37.5% was evergreen and the leaf phenology 32.8% was unknown. In 2008, 32.4% of the species was deciduous, 39.2% was evergreen and the leaf phenology of 28.4% was unknown. In 2012, 30.1% of the species was deciduous, 44.4% was evergreen and the leaf phenology of 25.4% of the species was unknown (Table 2). Thus, there is increasing percentage of evergreen trees as the forest regenerates from the fire disturbance.

3.4. Changes in tree basal area and girth size distribution

Tree basal area has fluctuated over the years. The tree basal area of the plot decreased from 21.92 m2 ha−1 in 1983 before the fire to 13.3 m2 ha−1 in 1984 one year after the fire, then increased to 20.17 m2 ha−1 in 1997 (14 years after the ground fire) and decreased to 14 m2 ha−1 in 2008 (25 years after the fire) and increased to 21.34 m2 ha−1 in 2012 (29 years after the fire) (Tables 4 and5). The basal areas of Baphia nitida, Blighia sapida, Dracaena arborea and Manihot glaziovii decreased while the basal areas of Albizia zygia, Alstonia boonei, Trilepisium madagascariense and Trichilia prieureana increased in 2008 and 2012 (Table 5). The percentage contribution to the basal of the dominant tree species, namely, Albizia zygia, Alstonia boonei, Antiaris africana, Bighia sapida, Ficus mucuso, Funtumia elastica, Glyphaea brevis, Holarrhena floribunda, Lecanoidiscus cupanioides, Manihot glaziovii, Newbouldia laevis, Pycnanthus angolensis, Rauvolfia vomitoria, Sterculia tragacantha and Trilepisium madagascariense in the plot fluctuated over the years (Table 5). These dominant tree species contributed 47% of the total basal area in the plot in 2012 as against 61.4% in 1983 before the fire, 66.7% in 1984, 68.6 in 1997 and 57.5% in 2008 (Table 5). Thus, their contribution to the total basal area which continued to increase after the fire and reached a peak in 1997 (14 years after the fire) started decreasing in 2008 (25 years after the fire). The girth size class distribution of the stems of all the tree species (Fig. 1) showed that the smallest girth size, 0–20 cm make up the largest number of the stem population and 81–100 cm girth size the lowest over the years. The percentage contribution of each girth size class in 2012 (29 years after the fire) was 0–20 cm, 61.7%; 21–40 cm 16.6%; 41–60 cm 12.4%; 61–80 cm 3.4%; 81–100 cm 2.6% and >100 cm 2.9%. There was an increase in the density of trees in the higher girth size classes and a decrease in the lower girth size classes in 2012 compared to 1997 and 2008 (Fig. 1). The increases in the densities of trees in girth size classes 41–60 cm, 61–80 cm, 81–100 cm and >100 cm represent a shift from smaller girth sizes to larger girth sizes as the forest recovers from the fire disturbance.

3.5. Changes in mortality and recruitment rates of tree species

The annual mortality rates in the plot since the fire were 25.7% yr−1 in this study (2008–2012), −5.2% yr−1 in 1997–2008, 2.02% yr−1 in 1984–1997 and 74% yr−1 in 1983–1984 (Table 1). The annual mortality rate per girth size classes showed that in 1983–1984, one year after the fire, all the girth sizes with the exception of 0–20 cm girth size class experienced mortality with the highest mortality rate in the 21–40 cm girth size (Table 6). There were no mortalities in all the girth sizes in 1997–2008 (Table 6). However, in 2008–2012 girth size class 0–20 cm experienced the highest mortality (Table 6). Mortality rates of the tree species ranged from 40.6% yr−1 to 395% yr−1 in 1983–1984, 3.10–26.7% yr−1 in 1984–1997, 0.73–41.9% yr−1 1997–2008 and 3.9–134.7% yr−1 in 2008–2012 (Table 6). The pioneer (secondary) species Alchornea laxiflora had the highest mortality rate (137.7% yr−1)(Table 1). Other species with high mortality rates are Alstonia boonei (40.23% yr−1), Canthium vulgare (94.6% yr−1), Ficus capensis (83.3% yr−1), Manihot glaziovii (47.4% yr−1) and Newbouldia laevis (82.7% yr−1)(Table 1). The annual recruitment rates in the plots since the fire were 74.0% yr−1 in 1983–1984, 2.02% yr−1 in 1984–1997, 5.2% yr−1in 1997–2008, and in 2008–2012 there was no recruitment. The recruitment rates of the different species showed that many tree species recruited new individuals (Table 1). The species that recruited the highest number of individuals were Bridelia ferruginea (light demanding species) Carpolobia lutea (shade tolerant species), Celtis zenkeri (light demanding canopy species) and Ficus sur (light demanding canopy species) (Tables 1 and2). The recruitment rate per girth size in 2008–2012 showed that there was recruitment of trees in girth size classes 41–60 cm, 61–80 cm, 81–100 cm and >100 cm only compared to previous surveys that had recruitment in all the girth size classes in 1997–2008 and only in smaller girth sizes (0–20, 21–40 cm) in 1983–1984 and 1984–1997 (Table 6). F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 159

Table 5 Changes in tree basal area (m2 ha−1) in the burnt plot in a lowland rainforest in Ile-Ife, Nigeria over 29 years. Source: 1983, 1984, 1997 and 2008 data: 1983, 1984 Isichei et al.(1986); 1997 Odiwe and Muoghalu(2003) and 2008 Nwosu(2010). Species Family Basal area BFF(1983) 1 yr AF (1984) 14 yrs AF (1997) 25 yrs AF (2008) 29 yrs AF (2012) Afzelia africana CLS – – 0.009 – – Albizia adianthifola MIM – – 0.009 – – Albizia ferruginea MIM – – – 0.019 – Albizia species MIM – 0.98 – – 0.436 Albizia zygia MIM 1.2 0.09 1.72 0.14 0.418 Alchornea cordifolia EUP – – 0.007 – – Alchornea laxiflora EUP – – 0.091 0.013 0.046 Allophylus africanus SAP – 0.018 – 0.004 – Asltonia boonei APO 0.44 0.58 2.23 2.41 3.489 Angylocalyx oligophyllus PPL – – – 0.0024 – Antiaris africana MOR 0.15 0.06 0.15 0.058 0.017 Annona tenuifolia ANN 0.49 0.02 – – – Antidesma membranaceum EUP – – 0.08 – – Apocynaceae species APO – 0.004 – – – Baphia nitida PPL 0.058 – 0.81 0.16 0.079 Berlinia grandiflora CSL – – 0.016 0.04 – Blighia sapida SAP – 1.53 0.63 0.8 0.598 Blighia species SAP – – – – 0.027 Blighia unijigata SAP 0.95 0.5 0.003 0.01 0.127 Bombax buonopozense BOM 2.37 1 0.07 0.068 – Bridelia atroviridis EUP – 0.13 0.001 – – Bridelia ferruginea EUP – – – – 0.024 Bridelia micrantha EUP – – – 0.015 – Carpolobia lutea POL – – – 0.002 Canthium vulgare EUP – 0.18 – 0.104 0.005 Carica papaya CAR – 0.077 – – – Celtis mildbraedii ULM – – 0.3 0.03 0.131 Celtis zenkeri ULM – – 0.5 0.6 1.611 Celtis species ULM 0.085 – – – 0.023 Chassalia kolly RUB – – – – 0.00003 Chrysophyllum albidum SAP – – 0.052 0.009 0.014 Citrus species RUT 0.147 – – – – Cleistopholis patens ANN – – – 0.004 – Cola acuminate STR – 8 – – 0.001 Cola millenii STR 0.015 – 0.092 0.078 0.137 Cola nitida STR – – – 0.043 0.001 Cola species STR – – – – 0.003 Deinbolla pinnata SAP – – 0.007 0.018 0.0001 Dialium guineense CSL – 0.006 – – 0.005 Dichapetalum species DCP – – 0.0004 – – Dicranolepis grandiflora THY – – – 0.001 – Dictyandra arborescens RUB – – 0.002 0.012 – Dictyandra involucrate RUB – – – 0.0013 – Diospyros monbuttensis EBN – 0.007 – 0.0015 – Diospyros nigerica EBN – – 0.002 – – Discoglypremna caloneura EUP – – 0.014 0.0094 – Dracaena arborea AGV – 0.064 0.94 0.18 0.073 Elaeis guineensis PLM 4.93 0.95 – 0.7 0.796 Eriocoelum kerstingi SAP – – – 0.00032 – Eriocoelum macrocarpum SAP – – 0.002 – – Erythrococca anomala EUP – – – 0.0008 – Ficus capensis MOR – 0.054 0.08 0.17 – Ficus exasperata MOR – – 0.067 0.0056 0.179 Ficus mucuso MOR 0.67 0.14 0.1 0.72 0.352 Ficus species MOR – 0.005 0.37 – 0.023 Ficus sur MOR – – – – 0.089 Ficus vogeliana MOR – – 0.001 – – Funtumia africana APO – – – – 0.332 Funtumia elastica APO 2.69 1.97 1.64 1.2 1.545 Glyphaea brevis TIL 0.04 0.05 0.02 0.02 0.009 Grewia species TIL 0.006 0.044 – – – Hexalobus crispiflorus ANN – – – 0.0001 – Holarrhena floribunda APO 1.6 – – 0.5 – Irvingia gabonensis IRV 0.16 0.076 – – – (Continued on next page) 160 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Table 5 (continued) Species Family Basal area BFF(1983) 1 yr AF (1984) 14 yrs AF (1997) 25 yrs AF (2008) 29 yrs AF (2012) Keetia vulgare Rub – – – – 0.043 Laccodiscus SAP – – – 0.04 – pseudostipuaris Lannea species ANA – – – 0.004 – Lannea welwitschii ANA – – – – 0.732 Lecaniodiscus cupanioides SAP 0.056 0.035 0.185 0.34 1.002 Lonchocarpus erinaceous PPL – – – – 0.001 Leptonychia pubescens STR – – – 0.00015 – Macaranga hurifolia EUP 0.65 – – – – Malacantha alnifolia SPO – – – 0.0026 – Mallotus mildbraedii EUP – – – – 0.007 Mallotus oppositifolius EUP – – – 0.013 0.115 Mallotus subulatus EUP – – – – 0.024 Manihot glaziovii EUP 1.32 2.01 4.8 0.33 0.222 Microdesmis puberula PAN – – 0.14 0.096 0.29 Milicia excelsa MOR 0.014 – – – – Millettia species MOR – – – – 0.099 Millettia thonningii PPL 0.42 – 0.17 0.23 0.161 Monodora tenuifolia ANN – – 0.13 0.0045 – Morinda lucida RUB – – 0.018 0.0085 0.025 Morinda morindoides RUB – – – 0.003 – Morus mesozygia MOR – – – 0.0005 0.209 Myrianthus arboreus MOR – – – 0.00046 0.003 Napoleona imperialis LCY – – 0.017 0.0005 0.035 Napoleona vogelii LCY – – 0.056 0.008 0.039 Napoleona species LCY – 0.03 – – – Newbouldia laevis BIG 0.51 0.26 0.26 0.84 0.054 Olax subcorpioides OLA – – 0.03 0.06 0.004 Ouratea flava OCH – – – 0.0015 – Oxyanthus species RUB 0.28 – 0.001 – – Pauridiantha floribunda RUB – – – 0.00073 – Phyllanthus odontadennius EUP – – 0.005 – – Phyllanthus species EUP – 0.022 – – – Piptadeniastrum africanum MIM – – 1.09 0.5 0.113 Pleiocarpa species PPL 0.004 – – – – Psychotria species RUB – – – 0.00064 – Psydrax arnoldiana RUB – – – 0.004 – pterocarpus species PPL – – – 0.0051 0.006 Pycnanthus angolensis MYS 0.63 0.28 0.77 0.85 1.233 Rauvolfia vomitoria APO 0.081 0.023 0.018 0.0015 0.002 Rothmannia longiflora RUB – – – 0.027 – Rubiaceae species RUB – 0.002 – – – Salacia pallescens CEL – – 0.023 – – Spathodea campanulata BIG – 0.084 – – – Spondias mombin ANN 0.38 – – 0.4 1.003 Sterculia tragacantha STR 0.097 0.2 0.005 0.00037 0.004 Tabernaemontana APO – – 0.026 0.00064 0.001 pachysiphon Terminalia superba COM 0.89 – – 0.41 0.56 Tetraptera tetrapleura MIM 0.28 – 0.18 0.8 – Tetrapleura tetraptera MIM – – – – 1.512 Theobroma cacao STR – 0.004 – – – Trema orientalis ULM – – – – 0.0018

Trichilia heudelotii MEL 0.134 – 0.225 0.48 0.874 Trichilia megalantha MEL – – 0.018 – 0.159 Trichilia monadelpha MEL – – 0.005 0.000026 – Trichilia prieureana MEL – – 0.18 0.2 0.475 Trichilia species MEL 0.76 0.012 0.042 – 0.064 Trilepisium MOR 0.67 0.31 0.99 0.9 1.535 madagascariense Turraea vogelii MEL – – – – – Voacanga africana APO 0.34 0.066 0.002 – – Xylopia species RUT – – – – – Zanthoxylum rubescens RUT – 0.092 – – Unidentified – – – 0.143 Total 23.517 19.873 19.4934 14.710136 21.34293 Note: Families are given as mnemonic three letter acronym following Weber(1982). BFF = before fire; AF = after fire. F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 161

Fig. 1. Changes in the distribution of stem density of woody plants per girth size class for fiv.

Table 6 Mortality and recruitment rates per girth size class in Nigeria secondary rainforest 29 years after a ground fire. Mortality and Recruitment rates are given for 1983, 1984, 1997, 2008, 2012 periods. Dash (-) represent zero values. BFF = Before fire, AFT = After the fire. Source: 1983, 1984, 1997 and 2008 data: (1983, 1984) Isichei et al.(1986); (1997) Odiwe and Muoghalu(2003); (2008) Nwosu(2010). Density per hectare Mortality rates (% yr−1) Recruitment rates (% yr−1) Girth size BFF 1 yr 14 yrs 25 yrs 29 yrs 1983–’84 1984–’97 1997–’08 2008–’12 1983–’84 1984–’97 1997–’08 2008–’12 classes (1983) AFT AFT AFT AFT (cm) (1984) (1997) (2008) (2012) 0–20 728 2724 2036 3704 936 – 2.24 – 34.39 131.96 – 5.44 – 21–40 444 216 272 372 252 72.06 – – 9.74 – 1.77 2.84 – 41–60 200 148 92 156 188 30.11 3.66 – – – – 4.8 4.67 61–80 44 40 20 40 52 9.53 5.33 – – – – 6.3 6.56 81–100 40 24 – 20 40 51.08 24.45 – – – – 27.23 17.33 >100 60 40 36 40 44 40.55 0.81 – – – – 0.95 2.38 Total 1516 3192 2408 4332 1520 −74 2.02 −5.16 25.7 74 −2.02 5.16 −25.7

3.6. Species compositional turnover within the plot

The Sorenson’s index of similarity of the species composition in the burnt plot between 1983 and 1984 was 59.7%, it decreased to 42.9% between 1984 and 1997, increased to 63.8% between 1997 and 2008 and 68.6% between 2008 and 2012 (Table 7). This indicates that similarity in species composition in the plot between years increased with increasing recovery from the disturbance. Dissimilarity in species composition in the plot between 1983 and 1984 was 40.4%, 57.1% between 1984 and 1997, 36.2% between 1997 and 2008 and 31.4% between 2008 and 2012 (Table 7). These results show that the highest turnover rate of the species was between 1984 and 1997 (57.1%) (Table 7). 162 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Table 7 Summary of similarity and dissimilarity indices in the burnt plot. Year 1983 1984 1997 2008 2012 1983 – 59.7 48.1 37.8 46.0 1984 40.3 – 42.9 40.4 46.6 1997 51.9 57.1 – 63.8 44.6 2008 62.2 59.6 36.2 – 68.6 2012 54.0 53.4 55.4 31.4 – Upper right represent Similarity index between period and lower left repre- sent dissimilarity index in burnt plot.

Table 8 Mean Decadal Climatic data of Ile-Ife, Nigeria from 1983–2012. Year Maximum temperature (◦C) Minimum temperature (◦C) Rainfall (mm) 1983–1992 31.0 22.0 1472 1993–2002 30.4 21.8 1553.9 2003–2012 29.9 22.6 1857.3

Table 9 Summary of correlation coefficients between vegetation parameters and mean decadal minimum temperature, Mean decadal maximum temperature and Mean decadal annual rainfall. Mean decadal minimum temperature Mean decadal maximum temperature Mean decadal annual rainfall Density 0.155 0.149 0.189 Basal area −0.143 −0.138 −0.174 Species richness −0.970 −0.970 −0.967 Diversity −0.608 −0.603 −0.636

3.7. Variation in temperature and rainfall in Ile-Ife, Nigeria, from 1983–2012

The maximum temperature ranged from 25.9 ◦C to 32.1 ◦C, minimum temperature from 18.7 ◦C to 23.8 ◦C and annual rainfall ranged from 775 mm to 3327 mm from 1983–2012 (Table 8). The mean decadal minimum temperature decreased by 0.6 ◦C per decade, mean decadal maximum temperature decreased by 0.2 ◦C per decade, and mean decadal annual rainfall increased by 210.9 mm (12.1% increase) through the 29 years.

3.8. Relationship between climate change (mean decadal minimum and maximum temperatures, mean decadal annual rainfall) and species basal area, species diversity and richness

There was a positive correlation between decadal minimum temperature and density though not statistical significant (r2 = 0.155, p > 0.05), mean decadal maximum temperature and density (r2 = 0.149, p > 0.05) and mean decadal annual rainfall (r2 = 0.189, p > 0.05) (Table 9). There was a negative correlation between basal area and mean decadal minimum temperature, though not significant (r2 = −0.143, p > 0.05), mean decadal maximum temperature (r2 = 0.138, p > 0.05), and mean decadal rainfall (r2 = −0.174, p > 0.05). There was also a significant negative correlation between species richness and mean decadal minimum temperature (r2 = −0.970, p < 0.05), mean decadal maximum temperature and species richness (r2 = −0.970, p < 0.05) and mean decadal rainfall and species richness (r2 = −967, p < 0.05) (Table 9). Furthermore, there was also a negative correlation between species diversity and decadal maximum temperature, though not significant (r2 = −0.608, p > 0.05), mean decadal minimum temperature and species diversity (r2 = −0.603, p > 0.05) and mean decadal annual rainfall and species diversity (r2 = −0.636, p.0.05) (Table 9).

3.9. Comparison of vegetation characteristics of burnt and unburnt plots in 2012: floristic composition

The total number of taxa per 0.25 ha in the unburnt plot of 55 species, 44 genera and 26 families and 2 species remained unidentified was lower than 63 species, 46 genera and 22 families while 3 species remained unidentified in the burnt plot (Tables 10 and 11). The dominant tree species in burnt plot were Funtumia elastica (136), Microdesmis puberula (152) and Trilepisium madagascariense (116) (Table 1), while those in the unburnt plot were Funtumia elastica (124) and Dracaena mannii (116) (Table 10) in 2012, twenty-nine years after the fire. The Sorenson’s index of Similarity showed that there was a 55.9% similarity in species composition between the burnt and unburnt plot.

3.10. Structural characteristics, mortality and recruitment rates between the plots

The Shannon–Weiner index of diversity of all tree species greater than 1 cm gbh was higher in burnt plot than in unburnt plot (Table 11). When trees ≥10 cm dbh were considered the species diversity is higher in unburnt plot than on burnt (Table 11). F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 163

Table 10 Species composition, density, (ha−1), basal area (m2 ha−1), mortality and recruitment rates of tree species in unburnt lowland secondary forest at Ile-Ife, Nigeria. Source: 1983, 1984, 1997 and 2008; (1983, 1984) Isichei et al.(1986); (1997) Odiwe and Muoghalu(2003) and (2008) Nwosu(2010). Species Family Basal area Density Mortality rate Recruitment rate (m2 ha−1) (ha−1) 2008–2012 (% yr−1) 2008–2012 (% yr−1) 2008 2012 2008 2012 Afzelia africana CEL 0.00003208 – 4 – 34.65735903 – Albizia lebbeck MIM 0.00644 – 12 – 62.12266624 – Albizia zygia MIM 0.384 0.356 28 16 13.9903947 – Alchornea cordiflora EUP 0.0092 – 4 34.65735903 – Alstonia boonei APO 0.00104 0.575 8 20 – 22.9072683 Amphimas pterocarpoides CEL – 0.089 – 8 – 51.98603854 Anthocleista nobilis LOG – 1.569 – 4 – 34.65735903 Anthocleista vogelii LOG 0.0001376 – 4 34.65735903 – Anthonotha macrophylla CEL – 0.009 – 4 – 34.65735903 Antiaris africana MOR 0.168 0.038 104 16 46.79505442 – Antiaris welwitschii MOR 0.436 – 4 – 34.65735903 – Balanites wilsoniana BAL 1.344 – 4 – 34.65735903 – Baphia nitida PPL 0.00136 0.01 56 16 31.31907421 – Blighia sapida SAP 0.072 0.001 4 4 0 – Blighia unijigata SAP 0.00784 – 12 – 62.12266624 – Bombax buonopozense BOM – 0.417 – 12 – 62.12266624 Bridelia ferruginea EUP 0.32 – 12 – 62.12266624 – Carica papaya CAR 0.0148 – 4 – 34.65735903 – Carpolobia lutea POL 0.0312 – 76 – 108.2683335 – Ceiba pentandra BOM 2 – 16 – 69.31471806 – Celtis mildbraedii ULM 0.25 0.031 24 4 44.79398673 – Celtis species ULM – 0.037 – 4 – 34.65735903 Celtis zenkeri ULM 0.48 0.555 48 28 13.47491252 – Chassalia kolly RUB 0.008 – 92 – 113.0447144 – Cleistopholis patens ANN 0.00392 16 – 69.31471806 – Coelocaryon species MYR – 0.048 – 4 – 34.65735903 Coffee ebracteolata RUB 0.484 – 8 – 51.98603854 – Cola acuminata STR 0.072 0.117 4 8 – 17.32867951 Cola gigantean STR 0.0017 – 4 – 34.65735903 – Cola hispida STR 0.22 – 48 – 96.78002527 – Cola millenii 0.28 0.705 40 64 – 11.75009073 Cola species 0.06 0.076 4 4 – – Corynanthe pachyceras RUB 0.12 – 4 – 34.65735903 – Deinbolla pinnata SAP 0.001816 – 32 – 86.64339757 – Diallum guineense CAE 0.053 0.005 20 4 40.23594781 – Diospyros barteri EBN 0.00018 – 4 – 34.65735903 – Dispyros mombutensis EBN 0.0046 – 4 – 34.65735903 – Diospyros suaveolens EBN 0.000072 – 4 – 34.65735903 – Discoglypremna caloneura EUP – 0.081 – 8 – 51.98603854 Dracaana fragans DRA 0.035 – 60 – 102.3586141 – Dracaena mannii DRA 0.26 0.458 236 116 17.75604035 – Dracaena species DRA 0.15 – 4 – 34.65735903 – Drypetes gilgiana EUP – 0.005 – 8 – 51.98603854 Elaeis guineensis ARA 2 1.009 28 12 21.18244651 – Fagara macrophylla RUT 0.19 – 8 – 51.98603854 – Fagara species RUT 0.099 – 4 – 34.65735903 Ficus exasperata MOR 0.065 0.197 16 8 17.32867951 – Ficus mucuso MOR 1.78 0.234 64 12 41.84941084 – Ficus species MOR 0.083 0.401 16 12 7.192051811 – Flacourtia species FLA – 0.001 – 8 – 51.98603854 Funtumia africana APO 0.86 0.96 132 92 9.025333638 – Funtumia elastica APO 2.88 1.321 352 124 26.08374025 – Funtumia species APO – 0.079 4 – 34.65735903 Guarea cedrata MEL 0.0248 – 4 – 34.65735903 – Holarrhena floribunda APO 0.0000848 – 4 – 34.65735903 – (Continued on next page)

Species density in the burnt plot (1520 ha−1) was higher than that of the unburnt plot (1148 ha−1)(Table 11). The basal area in the burnt plot, 21.34 m2 ha−1, is higher than 18.63 m2 ha−1 in the unburnt plot (Table 11). There were differences in the plant species in the two plots contributing to highest proportion of the basal area. In the burnt plot Alstonia boonei (3.5 m2h−1, 16.4%) contributed the highest basal area followed by Celtis zenkeri (1.61 m2 ha−1, 7.5%), Funtumia elastica (1.55 m2 ha−1, 7.0%) (Table 4) while in the unburnt plot Pierrodendron africanum (1.70 m2 ha−1, 9.1%), contributed the highest basal area followed by Anthocleista vogelii (1.57 m2 ha−1, 8.5%) and Funtumia elastica (1.32 m2 ha−1, 7.1%) (Table 10). The 164 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Table 10 (continued) Species Family Basal area Density (ha−1) Mortality rate Recruitment rate (m2 ha−1) 2008–2012 (% yr−1) 2008–2012 (% yr−1) 2008 2012 2008 2012 Homalium aylmeri SIM 0.056 – 36 – 89.58797346 – Icacina trichantha ICA 0.00388 – 156 – 126.2464002 – Irvingia species IRV 0.001604 – 4 – 34.65735903 – Keetia vulgare RUB 0.242 – 16 – 69.31471806 – Khaya species MEL 0.28 – 4 – 34.65735903 – Lannea welwitschii ANN 0.2 0.278 8 12 – 10.1366277 Lecaniodiscus cupanioides SAP 0.34 0.229 116 24 39.38840902 – Lindackeria dentata FLA 0.0056 0.061 12 4 27.46530722 – Lindackeria species FLA – 0.0183 – 4 – 34.65735903 Lonchorcarpus cynacerus APO 0.002324 – 4 – 34.65735903 – Maesopsis eminii RHA 0.38 1.312 12 24 – 17.32867951 Maesobotrya barteri EUP 0.28 – 24 – 79.45134576 – Margariteria discoides EUP – 0.41 – 12 −62.12266624 62.12266624 Malachantha alnifolia SAPO 0.002548 – 8 – 51.98603854 – Mallotus oppositifolius EUP 0.00904 – 60 – 102.3586141 – Mansonia altissima STR 0.002144 – 12 – 62.12266624 – Memecylon blakeoides MES 0.0000156 – 4 – 34.65735903 – Microdesmis puberula PAN 0.216 0.08 456 60 50.70370618 – Milicia excelsa MOR 0.044 0.0941 4 8 – 17.32867951 Monodora species ANN – 0.002 – 4 – 34.65735903 Monodora tenuifolia ANN 0.0464 – 8 – 51.98603854 – Morus mesozygia MOR 0.03216 4 – 34.65735903 – Musanga cecropioides MOR 0.94 – 4 – 34.65735903 – Myriantus arboreus MOR 1.08 1.001 68 60 3.129078574 – Napoleona imperialis LEC 0.068 0.067 76 8 56.28229497 – Napoleona vogelii LEC 0.017 – 32 – – – Newbouldia laevis BIG 0.12 0.013 60 12 40.23594781 – Oligocalyx zenkeri PAP 0.0003256 – 4 – 34.65735903 – Olax subscorpioides OLA 0.04006 0.103 28 24 3.853766996 – Oxyanthus unilocularis RUB 0.000588 – 4 – 34.65735903 – Pachecyras species RUB 0.0000814 – 4 – 34.65735903 – Pavetta corymbosa RUB 0.000588 – 4 – 34.65735903 – Phyllantus species EUP – 0.014 – 4 – 34.65735903 Pierreodendron africanum SIM 1.08 1.703 44 48 – 2.175284425 Pleiceras barteri APO 0.00962 – 4 – 34.65735903 – Pleiocarpa pycnantha APO 0.036 – 96 – 114.1087048 – Porterandia clandatha APO 0.013 – 4 – 34.65735903 – Pterocarpus osun PAP 1.9 – 12 – 62.12266624 – Pterocarpus species PAP – 0.023 – 8 – 51.98603854 Pycnanthus angolensis MYR 0.66 0.911 16 24 – 10.1366277 Rauvolfia vomitoria APO 0.03 – 4 – 34.65735903 – Ricinodendron heudelotii EUP 0.27 0.126 24 4 44.79398673 – Ritchiea duchesnei CAP 0.00002036 – 4 – 34.65735903 – Rothmannia species RUB – 0.079 – 4 – 34.65735903 Rothmannia whitfieldii RUB 0.02732 – 48 – 96.78002527 – Rytigynia umbellulata RUB 0.00014 – 8 – 51.98603854 – Spathodea campanulata BIG 0.102 – 4 – 34.65735903 – Sphenocentrum jollyanum MEN 0.000561 – 208 – 133.438452 – Sterculia tragacantha STR 0.01604 – 4 – 34.65735903 – Tabernaemontana APO 0.9 0.585 144 68 18.75763986 – pachysiphon Tetrapleura tetraptera MIM 1.1 – 8 – 51.98603854 – Trichilia heudelotii MEL 0.11 0.545 48 16 27.46530722 – Trichilia megalantha MEL 1.6 – 64 – 103.9720771 – Trichilia monadelpha MEL 0.24 – 12 – 62.12266624 – Trichilia prieureana MEL 0.52 0.061 168 16 58.78438143 – Trichilia species MEL – 0.14 – 20 – 74.89330684 Trilepisium madagascariense MOR 0.13 0.405 12 32 – 24.52073133 Triplochiton scleroxylon MEL 0.0424 0.468 4 8 – 17.32867951 Turraea species MEL 0.00001144 – 4 – 34.65735903 – Uvaria afzelii ANN 0.7 – 4 – 34.65735903 – Vitex grandiflora VER – 0.318 16 4 34.65735903 – Voacanga africana APO 0.0608 – – – – – Zanthoxylum zanthoxyloides RUT 0.063 – 4 – 34.65735903 −34.65735903 Unidentified – 0.056 – 4 −34.65735903 34.65735903 Unidentified – 0.048 – 4 −34.65735903 34.65735903 29.1844939 18.6334 3832 1148 30.1 −30.1 Note: Families are given as mnemonic three letter acronym following Weber(1982). BFF = before fire; AF = after fire. F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 165

Table 11 Summary of structural characteristics of the burnt and the unburnt plots of the secondary lowland rainforest at Ile-Ife, Nigeria in 2012. Parameters Burnt plot Unburnt plot All trees ≥1 cm (gbh) Trees ≥10 cm (dbh) All trees ≥1 cm (gbh) Trees ≥10 cm (dbh) Species density (ha−1) 1520 1032 1148 924 Basal area (m2 ha−1) 21.32 20.17 18.63 18.56 Species richness 63(3) 54(3) 55(2) 51(2) Number of genera 46 39 44 41 Number of family 24 23 26 26 Shannon–Weiner index 3.50 3.46 3.45 3.62 Pielou’s index 0.48 0.97 0.49 1.0 Sorenson’s index 55.9 54.5 – –

Fig. 2. Distribution of stem density of woody plants (≥1 cm gbh) in various girth size class in the burnt and the unburnt plots of the secondary lowland rain forest at Ile-Ife, Nigeria.

annual mortality rate in the burnt plot 25.7% yr−1 was lower than 30.1% yr−1 in the unburnt plot between 2008 and 2012 (Table 10). The annual recruitment rate in the burnt plot, −25.7% yr−1 during the same period, was higher than the annual recruitment rate of −30.1% yr−1 in the unburnt plot. The girth size class distribution of all tree species (≥1 cm gbh, ≥10 cm dbh) in the plots showed that there were greater number of individuals in the girth size classes 0–20 cm and ≥100 cm in the burnt plot but lower number of individuals in the girth size classes of 41–60 cm, 61–80 cm and 81–100 cm than in the unburnt plot (Figs. 2 and3).

4. Discussion

The results of the study and analyses of data from 1983, 1984, 1997, 2008 and 2012 studies showed the dynamics of floristic composition and structural characteristics of the forest in the course of succession after the fire disturbance. There was a decline in tree density as the mortality rate surpassed the recruitment rate in the burnt plot 29 years after ground fire disturbance with stand age. The fluctuations in the number of species and changes in tree species density in the burnt plot over the years agree with the assertion of Eggeling(1947) in Budongo rain forest, Uganda that there was an initial 166 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Fig. 3. Distribution of stem density of woody plants (trees ≥10 cm dbh) in various girth size classes in the burnt and the unburnt plots of the secondary lowland rain forest at Ile-Ife, Nigeria. rise in species numbers (species density) during succession, reaching a peak at intermediate phases of succession, followed by a decline during late succession. Appolinario et al.(2005) also reported a decline in tree density in Brazilian tropical semi-deciduous forest after a catastrophic flood. The decrease in the number of species and change in tree density with increasing age of the forest after twenty-nine years of fire disturbance is due to the dearth of early successional tree species such as Manihot glaziovii which established in the plot immediately after the fire had reached the limits of their life span and are gradually dying off, while others died presumably due to competition (Muoghalu, 2006). Most secondary forest early succession species are short-lived, often dying off at about 15 years of age and only a few exceptionally living beyond 25–30 years (UNESCO, 1978; Swaine and Hall, 1983; Lieberman and Lieberman, 1987; Manokaran and Kochummen, 1987). Chazdon(2008) has reported that it is as a result of growth suppression of the shade-intolerant trees in understorey and subcanopy, high mortality of short-lived, shade-intolerant pioneer trees. It is also as a result of the non-availability of high light demand of 75% intensity of early secondary forest tree species which was not normally available at later stage of succession (UNESCO, 1978). The co-existence of pioneer species, early successional tree species and late successional (shade-tolerant) tree species with abundant pioneer species at onset of succession in the forest after the fire agrees with the report by Gomez-Pompa and Vazquez-Yanes(1981) and Finegan(1996) that both pioneer and shade-tolerant species are present in the first phase of succession although pioneer species are more abundant. The pioneer species which reached their peak maturity at 25 years had decreased in density twenty-nine years after the fire as the forest recovered from the fire disturbance. This finding is in line with the initial floristic scheme (IFS) prediction that dominant pioneer species recruit poorly after initial canopy closure (Finegan, 1984, 1996). Swaine and Whitmore(1988) also reported that after canopy closure, recruitment of the dominant pioneer species becomes limited. The estimated 10% of late successional species (shade tolerant) recorded one year after the fire was less than 13% reported for shade tolerant plants in Ghanaian forest one year after abandonment (Swaine and Hall, 1983) but greater than 2% reported for Venezuelan Amazon forest (Uhl, 1987). The fluctuation in the percentage of species in the different successional stages over the years was as a result of death of early successional species and recruitment of late successional tree species and climate fluctuation in the forest over the years. The presence of all regenerational and successional guilds in the forest are similar to the findings of Kenzo et al.(2007) that all categories of tree species occurred in lowland mixed dipterocarp forest in Sarawak, Malaysia. The occurrence of all F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 167 regenerational and successional guilds in the forest over these years suggests that the forest follows the tolerance model of succession in the course of its recovery from the fire disturbance. The main mode of dispersal of seeds of the tree species in the forest was by animals. The observed 45.0% to 60.8% seed dispersal by animals in the forest was less than 70%–90% reported in Australian tropical forest (Wilson et al., 1989) and 70% in tropical forests (Gautier-Hion et al., 1985; Corlett, 1996; Da Silva and Tabarelli, 2000). The observed 13.2–22.5% abiotic vector (wind) mode of dispersal in this forest falls within the range of 10% to 30% reported by Wilson et al.(1989) in Australian tropical forest. The variation in the percentages of modes of seed dispersal in the forest over the years might be as a result of canopy closure which serves as windbreak and weight of the seeds in the course of succession. The dynamics of the floristic composition and species diversity in the plot with increasing age after the disturbance have resulted in changes in the dominance, number of families, density and species diversity as the forest recovers from the fire disturbance. Seven families are now dominant in the burnt part of the forest, namely, Apocynaceae, Euphorbiaceae, Meliaceae, Moraceae, Pandaceae, Sapindaceae and Ulmaceae. Seven new species were established in the plot in this survey period. These include Bridelia ferruginea, Futumina africana, Lannea welwitschii, Lonchocarpus erinaceous, Mallotus mildbraedii, Mallotus subulata and Millettia species. The presence of these new species show that the forest is still recovering from the fire disturbance. There had been fluctuation in Shannon–Weiner species diversity index as the forest recovered from disturbance over the years (1983, 1984, 1997, 2008 and 2012). The highest species diversity of 3.50 in 2012, 29 years after the fire after a decrease to 2.50 recorded 25 years after the fire indicates that species diversity is still increasing in the forest as it recovers from the fire disturbance and has not reached the peak after it is expected to drop gradually as the forest approaches mature stage of its succession. This finding agrees with the observation that tree species diversity tends to be low at early stage of succession, increases to a peak and decreases afterward as the matured stage of succession approaches (Whittaker, 1972; Bazzar, 1975; Ashton, 1978; Bormann and Likens, 1981). Similar observation has been reported by Grau et al.(1997) in a chronosequence study in Argentine subtropical montane forests. They found that Shannon–Weiner diversity of trees 10 cm dbh increased in young stands and by 45–50 years reached values similar to mature forests in the region. The Pielou’s evenness index which is the relative abundance of rare and common species that are in the community showed that species abundance was more evenly distributed before the fire (1983) and least distributed one year after the fire (1984)(see Table 4). There was a decrease in evenness index 29 years after the fire in 2012 which showed that few species were averagely dominant in the community as the forest recovers from the disturbance thereby affecting the evenness of species distribution in the plot. In this study, the basal area of 21.24 m2 ha−1 was lower than 24.26 m2 ha−1reported by Muoghalu(2006) for the same plot eighteen years after the fire but higher than 14.26 m2 ha−1reported by Nwosu(2010) twenty-five years after the fire. The value falls within the range of 17 to 40 m2 ha−1 reported for dry forests across the world (Murphy and Lugo, 1986) and the range of values from a variety of tropical forest types (Swaine et al., 1987a, b). The fluctuation of basal area in the forest over the years was as a result of the changes in species composition and the death of early successional tree species. However, the increase in basal area from 14.26 m2 ha−1 (2008) to 21.24 m2 ha−1 is as a result of increase in the number of individuals in high girth size classes as the forest increases in age after the fire. This agrees with the assertion of Peet and Christensen(1987) that basal increments are driven by overall tree growth increments rather than by changes in stem density. Such rapid and early successional increase of basal area has been observed in other studies (Saldarriaga et al., 1988; Denslow and Guzman, 2000; Steininger, 2000). The mean annual mortality rate of 22.7% yr−1 in relation to the total population for the period 2008–2012 is higher than a range of 1.00% yr−1 to 2.00% yr−1 reported for most natural tropical forests (Swaine et al., 1987a, b; Gomes et al., 2003), 0.9% yr−1 in a dry forest in Ghana (Swaine et al., 1990) and 2.03% yr−1 in a rain forest in Costa Rica (Lieberman and Lieberman, 1987). Mortality rate of the species from 3.85% yr−1 to 134.7% yr−1among the species in the plot in 2008–2012 (29 years after the fire) agrees with the observations of Manokaran and Kochummen(1987), Hubbell and Foster(1990) and Clark and Clark (1992) that different forest tree species have different mortality rates at a common site. The observed high mortality among trees of girth sizes 0–20 cm and 21–40 cm is in agreement with the report of Pinero et al.(1984), Conduit et al.(1995) and Zuidema and Boot(2002) that smaller trees typically suffer greater mortality rates. These high mortality rates of trees with smaller girth sizes 29 years after the fire could be due to inadequate supply of light reaching them resulting from canopy closure. Chazdon et al.(2005) and Capers et al.(2005) have observed that after canopy closure forest dynamics in the stem exclusion phase (phase 2) reflect high mortality of shade-intolerant shrubs and lianas. The mean annual recruitment rate of the total population—25.7% yr−1 (no recruitment) in this study was lower than 35.7% yr−1 reported by Muoghalu(2006) in this forest, 1.6 % yr −1 reported by Sabogal and Valerio(1998) in a deciduous forest and 0.4% yr−1 in a gallery forest of the Nicaraguan Pacific Coast. The results of the mortality and recruitment rates show that the forest is at the transition phase which is characterized by a first wave of tree mortality, caused by increased competition among the pioneer trees, accumulation of shade tolerant species in density (Bormann and Likens, 1979) before it enters steady state or climax phase. The Sorenson’s index of Similarity of the species composition in the burnt plot had fluctuated over the survey periods. This indicates that as secondary forests mature, the compositional similarity between tree species which was initially high, quickly declined followed by an increase later in succession as shade-tolerant trees reach reproductive maturity and produce seedlings that can establish in the forest (Chao et al., 2005). 168 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

There was change in the tree species dynamics of the 16 most abundant species in the forest over the various study periods. Some of the these abundant species such as Blighia unijugata, Ficus muccuso, Funtumia elastica Pycnanthus angolensis and Manihot glaziovii reduced from their original densities 29 years after the ground fire. Holarrhena floribunda was no longer present in the plot while tree species such as Lecaniodiscus cupanioides, Newbouldia laevis and Trilepisium madagasariense recruited new individuals into the forest. The basal area of Alstonia boonei and Pycnanthus angolensis increased from their original values. The mean decadal annual rainfall increase by 210.9 mm is higher than 87.6 mm reported by Thomas and William(1989). The negative relationship found between decadal mean minimum temperature, decadal mean maximum temperature, mean decadal annual rainfall and species richness, basal area and species diversity which was non-significant shows that as mean decadal minimum temperature, maximum temperature and annual rainfall increase species richness and diversity decrease. This is similar to the findings of Suttle et al.(2007) and Engel et al.(2009) who reported a negative effect of increased precipitation on species richness. It is however, in contrast with the positive relationship between increased precipitation and species richness and diversity reported by other workers (Sternberg et al., 1999; Zavaleta et al., 2003; Stevens et al., 2006; Yang et al., 2011). The non-significant negative relationship between mean decadal minimum temperature, maximum temperature, annual rainfall and tree basal area means that as these climatic factors decrease tree basal area increases. Furthermore, the non-significant positive relationship between decadal mean minimum temperature, maximum temperature, annual rainfall and density means that as these climatic factors increase density of trees increases. The decrease in the decadal mean minimum temperature (0.2 ◦C) is in contrast to 0.268 ◦C/decade reported by Giambelluca et al.(2008) as a worldwide increasing trend of air temperatures. Comparison of the burnt and unburnt plots in the forest showed that the burnt plot had higher species density, species diversity and richness and lower Pielou’s evenness than the unburnt plot (see Table 10). This result shows that fire disturbance can increase plant diversity by creating a wide range of different habitats at different stages along the successional continuum from disturbed state to climax vegetation. The 55.9% (0.559) Sorenson’s Similarity index between the burnt and unburnt plots in the forest shows an intermediate similarity between the two, burnt and unburnt plots in the forest. The value (55.9%) is lower than 71% maximum similarity index between undisturbed and moderately disturbed stand and higher than the 33% minimum similarity index between undisturbed and highly disturbed forest stands in Meghalaya, northeast India reported by Mishra et al.(2004). It is also lower than 60% similarity index reported by Shaheen et al.(2011) in Himalayan subtropical forests of lower, Nampra and Maira. In this study mortality and recruitment analyses were based on the entire tree population ≥1 cm in height at each survey period. This is a shortcoming of this study since mortality model works if the number of trees (ni) is the surviving proportion of the marked trees (n0) after time t and not if ni is the total number of trees in the population after time interval t. Similarly, the recruitment model requires that ni be the number of unmarked trees that have been recruited into at least the smallest size class measured at the start of the study. This possibly accounts for negative mortality and recruitment values reported for some of the species. However, it was assumed in this study that individuals recruited into the lowest class size measured at the start of the study for each species represented the individuals added to each species and the decrease in number of individuals of each species of all size classes in each study period represented individuals that died between enumeration intervals.

References

Anderson-Teixeira, K.J., Miller, A.D., Mohan, J.I., Hudiburg, T.W., Duval, B.D., De Lucia, E.H., 2013. Altered dynamics of forest recovery under a changing climate. Global Change Biol. 19 (7), 2001–2021. http://dx.doi.org/10.1111/gcb.12194. Appolinario, V., Oliveira-Filho, A.T., Guilherme, F.A.G., 2005. Tree population and community dynamics in a Brazilian tropical semi-deciduous forest. Rev. Bras. Botanica 28 (2), 347–360. Ashton, P.S., 1978. The natural forest: plant biology, regeneration and tree growth. In: Tropical Forest Ecosystems. UNESCO, Paris, pp. 180–215. Ayodele, O.J., 1986. Phosphorus availability in savannah soils of western Nigeria. Tropical Agriculture (Trinidad) 63, 297–300. Bazzar, F.A., 1975. Plant species diversity in old-field successional ecosystems in southern Illinois. Ecology 56, 485–488. Bormann, F.H., Likens, G.E., 1979. Pattern and Process in Forested Ecosystem: Disturbance, Development and the Steady State Based on the Hubbard Brook Ecosystem Study. Springer-Verlag, New York. Bormann, F.H., Likens, G.E., 1981. Pattern and Processes in a Forested Ecosystem. Springer-Verlag, New York. Brown, S., Lugo, A.E., 1990. Tropical secondary forests. J. Tropical Ecol. 6,1–32. Canhan, C.D., Marks, P.L., 1985. The response of woody plants to disturbance: patterns of establishment and growth. In: Pickett, S.T.A., White, P.S. (Eds.), The Ecology of Natural Disturbance and Patch Dynamics. Academic Press, Orlando, Forida, U.S.A, pp. 197–216. Capers, R.S., Chazdon, R.L., Redondo, B.A., Vilchez, A.B., 2005. Successional dynamics of woody seedling communities in tropical secondary forests. J. Ecol. 93, 1071–1084. Chao, A., Chazdon, R.L., Colwell, R.K., Shen, T.J., 2005. A new statistical approach for assessing similarity of species composition with incidence and abundance data. Ecol. Lett. 8, 148–159. Chazdon, R.L., 2008. Chance and determinism in tropical forest succession. In: Carson, W.P., Schnitzer, S.A. (Eds.), Tropical Forest Community Ecology. Wiley Blackwell, Malden, Massachusetts, pp. 384–408. Chazdon, R.L., Brenes, R.A., Varado, B.V., 2005. Effects of climate and stand age on annual tree dynamics in tropical second-growth rain forests. Ecology 86 (7), 1808–1815. Clark, D.A., Clark, D.B., 1992. Live history diversity of canopy and emergent trees in a neotropical rain forest. Ecol. Monogr. 62, 312–344. Conduit, R., Hubbell, S.P., Foster, R.B., 1995. Mortality rates of 205 neotropical tree and shrub species and the impact of a severe drought. Ecol. Monogr. 65, 419–439. F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170 169

Connell, J.H., 1978. Diversity in tropical rainforest and coral reefs. Science 199, 1302–1310. Corlett, R.T., 1995. Tropical forest secondary forests. Prog. Phys. Geograph. 19, 159–172. Corlett, R.T., 1996. Characteristics of vertebrate-dispersed fruits in Hong Kong. J. Tropical Ecol. 12, 819–833. Da Silva, J.M.C., Tabarelli, M., 2000. Tree species impoverishment and the future flora of the Atlantic forest of Northeast Brazil. Nature 404, 72–74. Dale, V.H., Joyce, L.A., McNulty, S., Neilson, R.P., Ayres, M.P., Flannigan, M.D., Hanson, P.J., Irland, L.C., Lugo, A.E., Peterson, C.J., Simberloff, D., Swanson, F.J., Stocks, B.J., Wotton, B.M., 2001. Climate change and forest disturbances. Bioscience 51, 723–734. De Jong, W., Chokkalingam, U., Smith, J., Sabogal, C., 2001. Tropical secondary forests in Asia: introduction and synthesis. J. Tropical Forest Sci. 13, 563–576. De Swardt, A.M.J., 1953. The Geology of the Country Around Ilesha. Bulletin No. 23. Geological Survey of Nigeria, Nigeria. Denslow, J.S., Guzman, G.S., 2000. Variation and stand structure, light and seedling abundance across a tropical moist forest chronosequence, Panama.J. Veg. Sci. 11, 201–212. Denslow, J.S., Ellison, A.E., Sanford, R.E., 1998. Tree fall gap size effect on above and below ground processes in tropical wet forest. J. Ecol. 86, 597–606. Eggeling, W.J., 1947. Observations on the ecology of the Budongo rain forest, Uganda. J. Ecol. 34, 20–87. Engel, E.C., Weltzin, J.F., Norby, R.T., Classen, A.T., 2009. Responses of an oldfield plant community to interacting factors of elevated [CO2] warming and soil moisture. J. Plant Ecol. 2,1–11. Evangelista, P.H., Kumar, S., Stohlgren, T.J., Young, N.E., 2011. Assessing forest vulnerality and the potential distribution of pine beetles under current and future climate scenarios in the interior west of the US. Forest Ecol. Manag. 262, 307–316. FAO/UNESCO, 1974. World soil classification. In: Legend to Soil Map of the World, vol. 1, UNESCO, Paris. Finegan, B., 1984. Forest succession. Nature 312, 109–114. Finegan, B., 1996. Pattern and process in neotropical secondary rain forest: the first 100 years of succession. Trends Ecol. Evol. 11, 119–124. Foster, D.R., 1985. Vegetation development following fire in Picea mariana (black spruce)-pleurozium forest of south-eastern Labrado, Canada. J. Ecol. 73, 517–534. Franklin, J.F., Spies, T.A., van Pelt, R., Carey, A.B., Thornburgh, D.A., Berg, D.R., Lindenmayer, D.B., Harmon, M.E., Keeton, W.S., Shaw, D.C., Bible, K., Chen, J.Q., 2002. Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example. Forest Ecol. Manag. 155, 399–423. Gautier-Hion, A., Duplantier, J.M., Quris, R., Feer, F., Sourd, C., Decoux, J.P., Dubost, D., Emmors, L., Erard, C., Hecktsweiler, P., Moungazi, A., 1985. Fruit characters as a basis of fruit choice and seed dispersal in a tropical forest vertebrate community. Oecologia 65, 324–337. Giambelluca, T.W., Diaz, H.F., Luke, M.S.A., 2008. Secular temperature changes in Hawaii. Geophys. Res. Lett. 35. Glitzenstein, J.S., Harcombe, P.A., Strenge, D.R., 1986. Disturbance, succession and maintenance of species in an east Texas Forest. Ecol. Monogr. 56, 243–258. Gomes, E.P.C., Mantovani, W., Kageyama, P.Y., 2003. Mortality and recruitment of trees in a secondary montane rain forest in southeastern Brazil. Brazilian J. Biol. 63, 47–60. Gomez-Pompa, A., Vazquez-Yanes, C., 1981. Successional studies of a rain forest in Mexico. In: West, D.C., Shugart, H.H., Botkin, D.B. (Eds.), Forest Succession: Concepts and Application. Springer-Verlag, New York, pp. 246–266. Gough, C.M., Vogel, C.S., Harrold, K.H., George, K., Curtis, P.S., 2007. The legacy of harvest and fire on ecosystem carbon storage in a north temperate forest. Global Change Biol. 13 (9), 1935–1949. Grau, H.R., Arturi, M.F., Brown, A.D., Acenolaza, P.G., 1997. Floristic and structural patterns along a chronosequence of secondary forest succession in Argentinean subtropical Montane Forests. Forest Ecol. Manag. 95, 161–171. Hall, J.B. (1969) The vegetation of Ile-Ife. Bulletin No. 1. University of Ife Herbarium, Ile-ife, Nigeria. Harmon, M.E., Bond-Lamberty, B., Tang, J., Vargas, R., 2011. Heterotrophic respiration in disturbed forests: a review with examples from North America, J. Geophys. Res. 116. Hawthorne, W.D. (1995) Ecological Profile of Ghanaian Forest Trees. Tropical Forestry Paper 29. Doi: Oxford Forest Institute, Department of Plant Sciences, South Parks Road, Oxford OX1 3RB, UK. Hicke, J.A., Allen, C.D., Desai, A.R., Dietze, M.C., Hall, R.J., Hogg, E.H.(TED), Kashian, D.M., Moore, D., Raffa, K.F., Sturrock, R.N., Vogelmann, J., 2012. Effects of biotic disturbances on forest carbon cycling in United States and Canada. Global Change Biol. 18,7–34. Hubbell, S.P., Foster, R.B., 1990. Structure dynamics equilibrium status of old-growth forest on Barro Colorado Island. In: Gentry, A.H. (Ed.), Four Neotropical Rain Forests. Yale University Press, New Haven, CT, pp. 522–541. Hurtt, G.C., Chini, L., Frolking, S., Betts, R., Feddema, J., Fischer, G., Fisk, J.P., Hibbard, K., Janetos, A., Jones, C.D., Kindermann, G., Kinoshita, T., Kinoshita, T., Klein Goldewijk, K., Riahi, K., Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., Van Vuuren, D.P., Wang, Y.P., 2011. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Clim. Change 109 (1), 117–161. Huston, M., 1979. A general hypothesis of species diversity. Amer. Nat. 113, 354–361. Hutchinson, J., Dalziel, J.M., 1954–1972. Flora of West Tropical Africa. (Revised by Keay, R.W.J., Hepper, F.M.) Crown Agents for Overseas Governments, London. IPCC, 2007. Climate Change. the Physical Science Basis. Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovermental Panel on Climate Change, IPCC. Cambridge University Press, Cambridge. Isichei, A.O., Ekeleme, F., Jimoh, B.A., 1986. Changes in a secondary forest in southwestern Nigeria following a ground fire. J. Tropical Ecol. 2, 249–256. Isichei, A.O., Muoghalu, J.I., Akeredolu, F.A., Afolabi, O.A., 1995. Fuel characteristics and emissions from biomass burning and land use in Nigeria. Environ. Monit. Assess. 38, 279–288. Johnstone, J.F., Hollingsworth, T.N., Chapin, F.S., Mack, M.C., 2010. Changes in fire regime break the legacy lock on successional trajectories in Alaskan boreal forest. Global Change Biol. 16 (4), 1281–1295. Keay, R.W.J., 1959. An Outline of Nigerian Vegetation, third ed. Government Printer, Lagos, Nigeria. Kenzo, T., Ichie, T., Watanabe, Y., Hiromi, T., 2007. Ecological distribution of homobaric and heterobaric leaves in tree species of Malaysian lowland tropical rain forest. Am. J. Bot. 94 (5), 764–775. Kirilenko, A.P., Sedjo, R.A., 2007. Climate change impacts on forestry. Proc. Natl. Acad. Sci. 104, 19697–19702. Kinnard, M., O’Brien, T., 1998. Letter from Indonesia: forest fires that raged throughout Indonesia are linked to quirky El Nino. Wildl. Conserv. Kio, P.R.O., Nnaobi, C.H., 1983. An economic analysis of the effects of forest fires-a case study of plantation losses in the 1982/83 dry season in southern Nigeria. In: Paper Presented at Workshop on Forest Fires, Ecology and Environment. Forest Research Institute, Ibadan. Lieberman, D., Lieberman, M., 1987. Forest tree growth and dynamics at La Selva, Costa Rica (1969–1982). J. Tropical Ecol. 3, 347–358. Liu, H.P., Randerson, J.T., Lindfors, J., Chapin, F.S., 2005. Changes in the surface energy budget after fire in boreal ecosystems of interior Alaska: an annual perspective. J. Geophys. Res.: Atmos. 110 (13),1–12. Macchi, M., Oviedo, G., Gotheil, S., Cross, K., Boedhihartono, A., Wolfangel, C., Howell, M., 2008. Indigenous and traditional Peoples and Climate Change. Issues Paper, IUCN, Gland, Switzerland. Maness, H., Kushner, P.J., Fung, I., 2012. Summertime climate response to mountain pine beetle disturbance in British Columbia. Nat. Geosci. 6, 65–70. Manokaran, N., Kochummen, K.M., 1987. Recruitment, growth and mortality of tree species in a lowland dipterocarp forest in Peninsular Malaysia. J. Tropical Ecol. 3, 315–330. 170 F.O. Ademoh et al. / Global Ecology and Conservation 9 (2017) 148–170

Mishra, B.P., Tripathi, O.P., Tripathi, R.S., Pandey, H.N., 2004. Effects of anthropogenic disturbance on plant diversity and community structure of a sacred groove in Meghalaya, northeast India. Biodivers. Conserv. 13 (2), 421–436. Muoghalu, J.I., 2006. Tree species population dynamics in a secondary forest at Ile-Ife, Nigeria after a ground fire. African J. Ecol. 45, 62–71. Murphy, P.G., Lugo, A.E., 1986. Ecology of tropical dry forest. Annu. Rev. Ecol. Syst. 17, 89–96. Nwosu, C.M., 2010. Tree Mortality, Recruitment and Litter Production Changes in a Secondary Lowland Rainforest At Ile-Ife, Nigeria, 25 Years After a Ground Fire (M.Sc. Thesis), Obafemi Awolowo University, Ile-Ife. Odiwe, A.I., Muoghalu, J.I., 2001. Ecosystem dynamics in a Nigerian secondary lowland rainforest 14 years after a ground fire. Tree species population dynamics. Nigerian J. Bot. 14,7–24. Odiwe, A.I., Muoghalu, J.I., 2003. Litter fall dynamics and forest floor litter as influenced by fire in a secondary lowland rain forest in Nigeria. Tropical Ecol. 44, 241–249. O’Halloran, T.L., Law, B.E., Goulden, M.L., 2012. Radiative forcing of natural forest disturbances. Global Change Biol. 18, 555–565. Oliver, C.D., 1981. Forest development in North America following major disturbance. Forest Ecol. Manag. 3, 153–168. Onochie, C.F.A., 1979. The Nigerian rain forest: an overview. In: Okali, D.U.U. (Ed.), The Nigerian Rainforest Ecosystem. The Nigerian Man and Biosphere Committee, Ibadan, Nigeria, pp. 1–13. Paine, R.T., Levin, S.A., 1981. Intertidal landscape of disturbance and the dynamics of pattern. Ecol. Monograph 51, 145–178. Pan, Y., Birdsey, R.A., Fang, J., Houghton, R., Kauppi, P.E., Kurz, W.A., Phillips, O.L., Shvidenko, A., Lewis, S.L., Canadell, J.G., Ciais, P., Jackson, R.B., Pacala, S.W., McGuire, A.D., Piao, S., Rautiainen, A., Sitch, S., Hayes, D., 2011. A large persistent carbon sink in the world’s forests. Science 333 (6045), 988–993. Peet, R.K., Christensen, N.L., 1987. Competition and tree death. Bioscience 37, 586–595. Pickett, S.T.A., White, P.S. (Eds.), 1985. The Ecology of Natural Disturbance and Patch Dynamics. Academic Press, New York, U.S.A. Pinero, D., Martinez-Ramos, M., Sarukhan, J., 1984. A population model of Astrocaryum mexicanum and a sensitivity analysis of its finite rate of increase.J. Ecol. 72, 977–991. Randerson, J.T., Liu, H., Flanner, M.G., 2006. The impact of boreal forest fire on climate warming. Science 314, 1130–1132. Richards, P.W., 1996. The Tropical Rain Forest, second ed. Cambridge University Press, Cambridge, United Kingdom. Running, S.W., 2008. Ecosystem disturbance, carbon and climate. Science 321, 652–653. Sabogal, C., Valerio, L., 1998. Floristic composition, structure and regeneration in a dry forest of the Nicaraguan Pacific Coast. In: Dallmeier, F., Comiskey, J.A. (Eds.), Forest Biodiversity in the North Central and South America and the Caribbean: Research and Monitoring. Man and the Biosphere Series, vol. 21. UNESCO, U.S.A, New York, U.S.A, pp. 187–212. Saldarriaga, J.G., West, D.C., Tharp, M.L., Uhl, C., 1988. Long-term chronosequence of forest succession in the upper Rio Negro of Colombia and Venezuela.J. Ecol. 76, 938–958. Shaheen, H., Qureshi, R.A., Shinwari, Z.K., 2011. Structural diversity, vegetation dynamics and anthropogenic impact on lesser Himalayan subtropical forests of Bagh District, Kashmir. Pakistan J. Bot. 43 (4), 1861–1866. Shannon, C.E., Weiner, W., 1949. The Mathematical Theory of Communication. University of Illinois Press, Urban. Sousa, W.P., 1984. The role of disturbance in natural communities. Annu. Rev. Ecol. Syst. 15, 353–391. Steininger, M.K., 2000. Secondary forest structure and biomass following short and extended land-use in central and southern Amazon. J. Tropical Ecol. 16, 689–708. Sternberg, M., Brown, V.K., Masters, G.J., Clarke, G.J., 1999. Plant community dynamics in a calcareous grassland under climate change manipulations. Plant Ecol. 143, 29–37. Stevens, M.H.H., Shirk, R., Steiner, C.E., 2006. Water and fertilizer have opposite effects on plant species richness in a mesic early successional habitat. Plant Ecol. 183, 27–34. Suttle, K.B., Thomsen, M.A., Power, M.E., 2007. Species interactions reverse grassland responses to changing climate. Science 315, 640–642. Swaine, M.D., 1992. Characteristics of dry forest in west Africa and the influence of fire. J. Veg. Sci. 3, 365–374. Swaine, M.D., Hall, J.B., 1983. Early succession on cleared forest land in Ghana. J. Ecol. 71, 601–629. Swaine, M.D., Whitmore, T.C., 1988. On the definition of ecological species groups in tropical rain forests. Vegetatio 75, 81–86. Swaine, M.D., Hall, J.B., Alexander, C.J., 1987a. Tree population dynamics at Kade, Ghana (1968–1982). J. Ecol. 3, 331–345. Swaine, M.D., Lieberman, D., Putz, F.E., 1987b. The dynamics of tree populations in tropical forest: a review. J. Tropical Ecol. 3, 359–369. Swaine, M.D., Lieberman, D., Hall, J.B., 1990. Structure and dynamics of tropical dry forest in Ghana. Vegetatio 88, 31–51. Taylor, D.L., 1973. Some ecological implication of forest fires control in Yellowstone National Park, Wyoming. Ecology 54, 1394–1396. Ter Steege, H., 2003. Long-Term Changes in Tropical Tree Diversity. Studies from Guiana Shield, Africa, Borneo and Malanesia. In: Tropenbos Series, vol. 22, Tropenbos International, Wageningen, The Netherlands. Thomas, R.K., William, E.R., 1989. The impact of decadal fluctuations in mean precipitation and temperature on runoff: a sensitivity study over the United States. Clim. Change 15, 423–447. Uhl, C., 1987. Factors controlling succession following slash-and-burn agriculture in Amazonia. J. Ecol. 75, 377–408. UNESCO, 1978. Tropical Forest Ecosystems. Natural Resources Research XIV. A State-of-Knowledge Report prepared by UNESCO/UNEP/FAO, UNESCO, Paris. USDA, 1975. Soil Taxonomy. In: Agriculture Handbook, vol. 436. U.S. Department of Agriculture, Washington. Warner, R.R., Chesson, P.L., 1985. Coexistence mediated by recruitment fluctuation: a field guide to the storage effect. Amer. Nat. 125, 768–789. Weber, W.A., 1982. Mnemonic three letter acronym for the families of vascular plants: A device for more effective herbarium curation. Taxonomy 31, 74–82. Westerling, A.L., Hidalgo, H.G., Cayan, D.R., Swetnam, T.W., 2006. Warming and earlier spring increase western U.S forest wildfire activity. Science 313, 940–943. Westerling, A.L., Turner, M.G., Smithwick, E.A.H., Romme, W.H., Ryan, M.G., 2011. Continued warming could transform greater yellowstone fire regimes by mid-21st century. Proc. Natl. Acad. Sci. 108 (32), 13165–13170. White, F., 1983. The Vegetation of Africa-A Descriptive Memoir to a Vegetation Map of Africa. UNESCO, Paris. Whitmore, T.C., 1989. ‘Southeast Asian tropical forests’. In: Leith, H., Werger, M.J.A. (Eds.), Tropical Rainforest Ecosystems. Ecosystems of the World, vol. 14B. Elsevier, Amsterdam, The Netherlands, pp. 195–218. Whitmore, T.C., 1991. Tropical rain forest dynamics and its implications for management. In: Gomes-Pampa, A., Whitmore, T.C., Hadley, M. (Eds.), Rainforest Regeneration and Management. In: Man and the Biosphere Series, vol. 6, UNESCO, Paris, pp. 67–89. Whittaker, R.H., 1972. Evolution and measurement of species diversity. Taxon 21, 213–251. Wilson, R.C., 1922. The Geology of the Western Railway Section 1. Bulletin No. 2. Geological Survey of Nigeria, Nigeria. Wilson, M.F., Irvine, A.K., Walsh, N.G., 1989. Vertebrate dispersal syndromes in some Australian and New Zealand plant communities, with geographic comparisons. Biotropica 21, 133–147. Yang, Y., Luo, Y., Finzi, A.C., 2011. Carbon and nitrogen dynamics during forest stand development: a global synthesis. New Phytol. 190, 977–989. Zavaleta, E.S., Shaw, M.R., Chiariello, N.R., Thomas, B.D., Cleland, E.E., Field, C.B., Mooney, H.A., 2003. Grassland responses to three years of elevated temperature, CO2, precipitation and nitrogen deposition. Ecol. Monograph 73, 585–604. Zuidema, P.A., Boot, R.G.A., 2002. Demography of the Brazil nut tree (Bertholletia elxcelsa) in the Bolivian Amazon: impact of seed extraction on recruitment and population dynamics. J. Tropical Ecol. 18,1–31.