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    Tree-ring:a suitable implement for spatial and temporal fire distribution analysis in savanna woodland and dry forest

    2015-06-05 08:54:05FranckSinsinRomainGleleKakaBettinaOrthmannBriceSinsin
    Journal of Forestry Research 2015年2期

    Franck Sinsin?Romain Gle`le`Kaka?¨?Bettina Orthmann?Brice Sinsin

    Tree-ring:a suitable implement for spatial and temporal fire distribution analysis in savanna woodland and dry forest

    Franck Sinsin1?Romain Gle`le`Kaka?¨2?Bettina Orthmann3?Brice Sinsin1

    Based on 120 stem discs collected during 3 months of fieldwork along a 12 km route,the history of fires in the Wari Maro Forest(09°10′0 N–02°10′0E)over the past century in savanna woodland and dry forest was reconstituted.Three major ecological areas are characterized:one highly burnt zone located between two relative less burnt areas.By analyzing tree rings,246 fire scars were identified.The scars were caused by 51 fire years, occurring at a mean interval of 2.23 years.From 1890 to 1965,only 6 years with fires were recorded from sampled trees.Since 1966,no year has passed without fire.The fire frequency point scale reached 14 years.This was the case of Burkea africana,which has been identified as a species tolerant to fire and could be planted to create a natural firewall.In contrast,Anogeissus leiocarpa is highly sensitive to fire,and in a dry forest ecosystem that burns seasonally,it requires a special conservation plan.Two newconcepts are described:the rebarking of trees after fire and Mean Kilometer Fire Interval.The first concept was tested with Daniellia oliveri(Rolfe)Hutch&Dalz trees,and the second concept was used to evaluate spatial fire distribution.We demonstrate thatsavanna woodland and dry forest were subjectto a degradation process caused by destructive fires related to vegetation cover clearance and illegal logging.

    Fire ecology·Tree-rings·Savanna woodland·Dry forest·Conservation strategies

    Introduction

    Bush fires are one of the strongest factors influencing the growth dynamics of tropical dry forests and savannas woodland.Such ecosystems respond to repeated fire disturbance by increasing the density of hardy species to the detrimentof sensitive species,which,in the long-term,may lead to a specialization of the ecosystems and the emergence of invasive species(Arseneault 2001).While ecosystems react to frequent fires by declining in area and by changing the floristic composition(Taylor 2010),tree species develop survival strategies by adopting favorable life types or by producing specialtissues of defense(N’Dri et al.2011).Cambium mostly lays down a cellular wall layer between the wood compartment formed before and that formed after a wound making it difficultfor pathogens to spread(Shigo 1984;Smith and Sutherland 1999a,b, 2001).The understanding of these self-defense strategies of trees to fires had been possible through dendropyrochronological investigations.It is also worth noting that the decline of sensitive species is not always exclusively due to the destruction of seeds and regeneration by fires.The fires also cause sudden significant physiological changes in the trees which affecttheir ability to fruit and to produce viable seeds(Danthu et al.2003).

    Many other scientific investigations have revealed the negative effects of bush fires on the stability of savannas woodland and dry forests and especially on the conservation of genetic resources(Salafski and Wollenberg 2000). Significant actions to combat the scourge have been implemented around the world,but forests are still burning. The situation is particularly alarming in West Africa where 12%of forest cover is annually affected by fire.FAO (2010)reported that forest fire is the major constraint preventing sustainable savannas woodland and dry forest managementin the subregion.Factors affecting wildfires in that region are many,and most of them are related to the life style of communities surrounding these ecosystems (Bowman and Wood 2009).Some crops residues like Sorghum bicolor decay slowly and upset the rooting of the next crop’s season justifying the use of fire for clearing cultivation(Hough 1993).For livestock breeders,fire is an essential tool for grassland management(Sheuyange et al. 2005).Hunters use fire to capture wildlife.People burn vegetation to destroy the refuges of certain animal species such as scorpions and snakes.

    According to certain traditions,the use of fire to burn vegetation is an inherited practice commonly accepted (Hough 1993).Charcoal production and honey harvest are other reasons for which fires are misused in savannas woodland and dry forests.When rationally used,bush fires can be an essential production factor,but sometimes,they have negative consequences(Ballouche 2004).Fires contribute to climate change(Swetnam 1993),they deplete carbon stocks and compromise regeneration of certain tree species(Danthu et al.2003).

    Wildfires could also have a positive impact in silvicultural terms.They thin forests,allow sunlight to penetrate under the canopy and promote tree regeneration.By doing so,fires improve the growth of resistant woody species, which in return,can favors carbon balance(Goldammer and de Ronde 2004;Hurteau and Brooks 2011).

    Wherever fires frequently burn forests,it is imperative to provide forest managers with accurate data related to the regimes,the spatial and temporal distribution of fires,and their impacts on the sustainability of the corresponding ecosystems.Remote sensing is one of the most effective approaches to investigate the spatial and temporal distribution of vegetation fires(Koffiet al.1995;Eva and Lambin 2000).According to that method,over 70%of detected fires were within the tropical belt,while 50% came from the African continent(Dwyer et al.1998). Although effective to study fires at the ecosystem level, satellite sensors do not provide accurate information about the impactof fires on the ecophysiology of individual trees that play important roles in the ecological balance at the microclimate(Kennedy et al.1994;van Wilgen et al. 2000).Because of this major constraint,the most relevant method to monitor fire at the ecosystem level and at the individual trees level is based on the analysis of fire scars from annualtree rings as proposed by severalstudies(Arno and Sneck 1977;McBride 1983;Grissino Mayer 2006; Richard 2008).On about 4000 ha in a montane ponderosa pine forest of central Colorado,Brown et al.(1999) recorded 77 fire years ranging from 1197 to 1999.In Norra Kvills National Park,six centuries wildfires history has been reconstructed at a fire frequency of 20 years(Niklasson and Drakenberg 2001).Fire frequency atpoint scale in this study revealed that trees can survive 20 different fires without dying.This is a key indicator in fire ecology as ithelps to recognize the most frequently burned habitats of an ecosystem,hence useful for the implementation of an efficient management design to control wildfires.

    In West Africa,particularly in savanna woodlands and dry forests affected by repeated fires and continuous decline of vegetation cover,appropriate data about past disturbances is unavailable.Although numerous scientific studies showed the difficulties to regenerate certain tree species,little is still understood about the topic.Therefore, the study of the spatial and temporal distribution of fires is essential to design an efficient management plan and to better conserve biodiversity.The main hypotheses of the study are:(1)savanna woodlands and dry forests that are closer to land use area experience more frequent fires and are more threatened;(2)trees and stands develop survival strategies in response to anthropologic disturbances.

    Materials and methods

    Study area

    The study was done in Wari Maro which belongs to the dry tropical savanna woodland and dry forest of the Guineo-Sudanian transition zone(White 1983).The study area is 1075 km2and is located in central Benin(09°10′0 N–02°10′0 E)(Fig.1a,b).With 7 months of droughtper year, the study area is characterized by a unimodal rainfall of 900–1200 mm.Temperatures vary between 19°and 40°C with monthly averages ranging from 23°to 28.5°C,the highest values being observed during the dry season.Figure 2 shows the variation of precipitation(P),temperature (T)and evapotranspiration(ETP)during the year.The relative humidity ranged between 50 and 98%.The soil is nearly ferruginous.The topography of the study area is dominated by inselbergs up to 620 m of altitude.

    Fig.1 a Localization of the research site.b Vegetation map of the research site showing the transect lines used

    As shown in the Fig.3,the vegetation is a savanna woodland and dry forest that is affected by anthropogenic disturbances including:the repeated misuse of fires,the selective logging and the progressing conversion of forests into agricultural lands.The vegetation is dominated by Isoberlina spp and other valuable ligneous native hardwood and deciduous species such as Afzelia africana, Anogeissus leiocarpa,Burkea africana,Daniellia oliveri, Khaya senegalensis,Lonchocarpus laxiflora and Pterocarpus erinaceus.

    Samples collection

    Along a‘transectline’of 4 m wide and 12 km long,a sampling area of 4.8 ha was marked,and oriented so that,it is centripetal to the forest(Fig.1b).Cross wood sections were collected from stumps of freshly demolished trees and from living trees during three months of fieldwork(January to March 2011 within every kilometer,ten stem discs from tentrees were removed with chainsaw at10 cm above ground in order to evaluate the spatial fire distribution.A total of 120 stem discs were collected from 7 native species:Anogeissus leiocarpa,Burkea africana,Daniellia oliveri,Isoberlinia doka,Isoberlinia tomentosa,Pterocarpus erinaceus and Lonchocarpus laxiflora.These stem discs were carefully labeled(e.g.name ofspecies,numberoftrees,position along the transect route at which the stem disc was collected)and organized into 12 batches as the transectline was divided in 12 segments.

    Fig.1 continued

    Fig.2 Climatic diagram of the study area

    Fig.3 Degradation state of the study area

    Stem discs processing and tree-rings identification

    Before transporting them to the International Tree-Ring Laboratory of Georg-August University of Go¨ttingen,the stem discs samples were pre-dried in the field during 2 weeks.To ensure a high quality surface,an electric polishing machine was used and the stem discs were gradually sanded with a finer grade abrasive paper (40–800 grit).The stem discs were dusted using air compressor.Macroscopic and microscopic observations were performed on the discs using a magnifying glass as well as a digital camera(Leica ect)on stereomicroscope(Wild etc.).Anatomical structure(Fig.4)of each studied species was studied using Leica program;and five criteria were used for:legibility of ring boundaries,arrangementof axial parenchyma,disposition of vessels,variation in wood density between earlywood and latewood and finally,the size of rays.Anogeissus leiocarpa was characterized by growth rings with distinct boundaries,diffuse-porous vessels,scanty paratracheal parenchyma and relatively thin fibres(Fig.4a).Burkea africana showed distinct treerings’boundaries.Axial parenchymas were represented by marginal bands,vessels were diffuse-porous and rays were thin(Fig.4b).Growth rings of Daniellia oliveri were narrow but well delimited with diffuse-porous and wide vessels.Axial parenchymas were marginal bands and rays were remarkable(Fig.4c).Isoberlinia doka and Isoberlinia tomentosa had a very well delimited wide growth rings,a diffuse-porous wood vessels,marginal bands axial parenchymaand thin rays(Fig.4d,e).

    Lonchocarpus laxiflora was a suitable species for dendrochronological analysis.Some rings were very wide and others were narrow.Ring boundaries were all well delimited.Growth rings were characterized by marginal parenchyma bands;vessels were wide in the latewood and thin in earlywood and rays were thin in size(Fig.4f). Pterocarpus erinaceus showed a variation in wood density between earlywood and latewood.Growth rings were wide and their boundaries were not easily delimited.With very small vessels,axial parenchymas were diffuse-in-aggregates and rays were thin(Fig.4g).

    Ring dating and width measurement

    Anatomical structures of the growth-rings were used to demarcate ring boundaries.Using standard dendrochronological approach,tree-rings were dated,tree widths were measured and growth chronologies were established. Counting and dating of tree-rings and their widths measurements were done from bark to pith to the nearest 0.01 mm using Time Series Analysis and Presentation (TSAPWin)software with a digital measuring device Lintab 5(Rinntech,Heidelberg,Germany)connected to a stereomicroscope(magnification 6.4–40×,Wild M3Z, Leica,Germany).Time series were visually synchronized for each species based on Gleichla¨ufigkeit,and student’s test was used to assess the inter-curves correlation degree. Using cross-dating principle(Grissino-Mayer 2001),false rings were eliminated,whereas missing rings were inserted.

    Fire scars dating

    Data entry

    By examining the position of scars on stem discs one-byone,the exact years and seasons of fire occurrence were determined.As proposed by Grissino Mayer(2006),the data were entered into a character-based data matrix of FHX2 system.The matrix file was named‘WM Fire’. Then,an ID was given to each sample.The ID consists of the first two letters of the scientific name of the species followed by the number of tree.For instance,the ID of the tree number 4 of Isoberlinia doka was‘DO4’. After this step,the germination year was entered as

    beginning year.The site information was documented as well.

    Fig.4 Anatomical structure of investigated species showing distinct tree-rings

    Data analysis

    From the file generated from FHX2 system,standard statistical data on fire regime were obtained:length of disc growth chronology,number of fire scars,number of fire years,number of dry season fire,number of vegetative season fire and,the mean fire interval.

    The length of the analyzed chronology is the number of years between the oldest year of germination and the year of sample collection.It therefore defines the period over which the historical investigation was conducted.

    The number of the analyzed fire scars is the totalnumber of considered scars for the fire regime analysis is indicated.

    Mean fire interval is the average number of years between two consecutive fire occurrences in a given ecosystem.The mean fire interval is positively correlated with the frequency of fires.

    Using the mean fire interval,three new fire regime parameters were developed and defined as follows:

    The Average Number of Years per Fire–ANYF(years) which is the ratio between the number of tree-rings counted on a given sample and the number of fire years(N) recorded on the same tree

    Sample Mean Fire Interval–SMFI(years)which was determined for each tree and which indicated the mean fire interval at point scale as a tree lived all its life at the same position and was able to record all fire coming at this specific location

    where N and X are respectively the total number of fire scars on a given sample in a particular fire year. Knowing the SMFI,the KMFI,the Kilometer Mean Fire Interval KMFI(years)was calculated as the ratio of sample mean fire interval and the number of analyzed samples per kilometer.The KMfiwas used to analyze the distribution of past fire occurrences along the walking transect line

    K means the number of analyzed samples per kilometer. In this study 0≤K≤10.

    Reaction of wood to fire

    By using microscopic observations(Leica software)and macroscopic observations(presence and absence of visible fire scar on transversalsection of stem discs),the impactof fire on wood technology was analyzed and.

    Bark width for all the samples were measured and their averages were calculated.These data were used to evaluate the effectiveness of protecting timbers against fire threats.

    Results

    Spatial and temporal fire distribution

    As shown in the Fig.5,analysis of the fire regime obtained along transect revealed a spatial fire interval characterized by a distribution similar to thatof Gauss.On this basis,the study vegetation was divided in two major ecological areas:a frequently burnt zone located between two relatively less burnt areas.The first four and the last five kilometers of transectwere less impacted by fire.A total 246 fire scars were analyzed,which come from 51 fire years,mostly during the dry season.The length of analyzed fire chronology was 132 years(1890–2011)and the mean fire interval was 2.23 years.The average time between 2 consecutives fire at sample scale ranged from 2.3 to 37.3 years with a total mean value of 11.39 years.About 92%of the fires belonged to the last six decades(Figs.6, 7).Since 1966,there has been fire every year.Based on the analyzed stem discs,fire frequency at point scale varied between 1 and 14;some trees experienced more fires than others.Fires during the years 1994,1995,2001,2004,2005 and 2007 had the highest negative impact on theecosystem.During each of these 6 years,at least 10%of the analyzed trees were injured.

    Fig.5 Spatial fire distribution along transect line of 12 km

    Fig.6 Temporal fire distribution

    Fig.7 Inter-species variation of trees′bark widths

    Interviews with different stakeholders groups provided further explanation on these results.The starting point of transect is located between cashew plantation(Anacardium occidentale)and woodland area.In this transition zone between land use and natural vegetation,fires are not desired and are actively fought because of their devastating effect on the productivity of cashew.Progressing in the forest along the transect direction and away from the cashew plantations,fire intervaland fire frequency increase untilthey reach the peak at6 km from the starting point.In Wari Maro,charcoal producers and illegal loggers are connected and work in channel.Immediately after felling a tree,illegal loggers are only interested in the stem that can yield morebeams;the remnants and the branches serve as raw materials for charcoal production.To escape the detection of the chainsaw by rangers and to avoid to be caught,loggers operate their illegal activities away from road network in the bush.

    Because Charcoal production is thus more intense within the fourth and the seventh kilometer of the transect route.This fire-dependant seasonal activity explains the seasonal occurrence of fires in and around forested areas hence high risk of forest deterioration.

    Table 1 Impactof fires on wood(qualitative analysis of fire scars on stem discs)

    Adaptation capacity of species

    Tree reactions to fires depend not only on their species and age,but also on the position of the tree in the burnt area, the season,and the intensity of the fire.Based on the anatomical structure and the variability of the wood reaction to fires,three distinct groups of species were found (Table 1).Represented by Anogeissus leiocarpa,the h igh fire sensitive species are vulnerable to fires(Table 1). These species has a thin bark,and when they reach their climax,severe fires during the dry season burn intensely their stem up to 3–4 m of height,leaving behind a large fire wound that can be observed on the stem many years afterward.The portions of a tree before and after a fire attack are separated by a wood gap more remarkable in the side of the stem disc from which fire comes(Fig.8).This wood gap showed dead tissues and carbon.The local populations living near those forests know very well the high sensitivity of Anogeissus leiocarpa to fires which in return makes this species a preferential choice for charcoal production.

    Figure 7 and Table 1 showed that Daniellia oliveri, Isoberlinia doka,Isoberlinia tomentosa and P.erinaceus form the group of species that have a relatively wide inner bark and a relatively thin outer bark(Fig.7).These species react to fires by forming remarkable scars and by healing their fire injuries very well.To seal its fire injuries, Daniellia oliveri produced special tissues without vessels like those of bark(Fig.8).

    Figure 8 shows three images:The first 2 pictures are stem discs from Diospyros abyssinica.On their transversal section,the two distinguishable and observable compartments of wood are separated by a‘bark’and a wood gap visible only under microscope.The last group of species tolerates fires,and they are represented by Burkea africana. Trees belonging to this group showed a less macroscopic and observable fire damages on their stem discs.Additionally,they have a wider outer bark and can survive many fires along their lifetime.Young individuals of this species also survive several fire occurrences.

    Fig.8 Reaction of wood to fires:rebarking of D.oliveri tree(left hand side image),compartmentalization of A.leiocarpa(centre)and less fire injury impact on B.africana stem(right hand side image)

    Tree growth response after fire

    While D.oliveri showed 3 years of progressive regrowth,I. doka instantly reacted by showing an abrupt growth after fire passage(Fig.9).This growth can be explained by the factthat fires enhance natural thinning and the residual ash provides mineral nutrients like potassium.

    Discussion

    Dendropyrochronology

    Fig.9 Abrupt growth after fire

    Douglass had pioneered the Tree-Ring’s science,and most importantly,the cross dating principle which he applied to numerous disciplines(Douglass 1941).By the early 1920s, he admitted the use of dendrochronology for studying dendropyrochronology,the dating the past occurrence of forest fires(Douglass 1929).This method was very useful to explain the historical occurrence of wildfires in the inland coniferous forests of western North America.By collecting and analyzing cross sections of fire-scarred trees, it is possible to identify the age classes of postfire trees.In logged areas,a method was designed to gather fire-scar and age-class data from stumps in order to interpret fire frequency,intensity,size;influence on stand composition and structure;and the effects of modern fire suppression. Between 1700 and 1900,Baisan and Swetnam(1990) recorded thirty-five major fire years from tree-rings in the Rincon Mountain Wilderness.Mean fire interval was estimated to 6.1 years in the Mica Mountain(1657–1893)as compared to 9.9 years for the mixed-conifer forest type (1748–1886).Using the temporaland synchrony records of dendrochronologically-dated fire scars,attributes and regulators of the fire regime from 1702 to 2007 were investigated in the south-western United States.Results of that study demonstrated how human land uses could incite site burning.The established fire regime,which predominately consisted of prescribed fires implemented since the 1960s,looked like the past frequent surface fire regime that occurred in Ponderosa pine foreston Native American lands and in similar forest types on non-tribal lands in the south-western United States(Stan et al.2014).Fire scars analysis was recently applied to twenty-six burnt Acacia aneura stands’with the purpose to evaluate the role of fire in maintaining the diversity and the vigour in the Gilbson Desert and Gascoyne–Murchison regions of Western Australia.Fire intervals were ranged from 3 to 52 years and the average juvenile-to–adult ratio was estimated to 0.49.Fire-return intervals less than 20 years produced then 2–3-year-old seedling regeneration lower than the half of the original stand population(Ward et al.2014).

    Spatial fire distribution was recently documented in the Central Appalachian Mountains from 1970 and 2003.From such investigation,the variation of fire activity according to the topography was demonstrated(Lafon and Grissino-Mayer 2007).

    Fire in Savanna woodland and dry Forest

    Fig.10 Growth rate of trees in environments with repeated fires

    Wildfires were reported in numerous studies as one of the most common factor that contributes to accelerated deforestation.Consequently,the ecosystem decreases in size and gives rise to small patches,making them more vulnerable.Forests lose some of their essentialfunctions by reducing their ecological niches,the variability of genetic resources and their ability to protect soils against erosion caused by rain and wind(Parminter 1992).Although it is well known that,savanna woodlands and dry forests are degraded because they generate income and recreation activities to human beings,the exact role of wildfires still remain poorly understood,issue(Cochrane 2001;Regan etal.2010).Severalauthors have established the expansion of agriculturallands as the leading cause of deforestation in the tropics.Recent studies have identified illegal logging, called‘forestcrime’by some authors,as another top cause of deforestation(FAO 2010).Illegal logging compromises the survival of selected species for logging and makes available the raw material for charcoal production in the forest.Such activity explains the repeated and seasonal fires recorded by trees.

    In Africa,fire history in Savanna woodland and dry forest remains poorly discussed.However,in Kruger National Park,South Africa,fires occurrence between 1941 and 1996 was reported(van Wilgen et al.2000). The ecosystem was burned all months of the year. Mean return fire of 4.5 years was estimated and a fire interval was ranged from 1 to 34 years(van Wilgen et al.2000).

    Trees adaptation to fire:Terminology and biology of fire scars

    An analysis of growth curves shows that in response to perturbation,trees show intraspecies and interspecific variation in growth.Fires play a key role by removing dead wood,by combating fungi,insects,and mistletoe and by providing minerals to the soil.In addition,by eliminating some trees,fires act as a natural thinning agent that promotes growth in diameter of surviving trees(Hunter et al. 2007).Post fires growth is characterized by very narrow rings in surviving Pinus sylvestris L.trees(Beghin et al. 2011).Some ecosystems are adapted to fire and need it to maintain their vigor and reproductive capacities(FAO 2010).

    Figure 10 gives an insight into the growth dynamic of the investigated species in frequently burned stands.Certain species adapt to their environment by acquiring some properties that protect them from the fire.Species like B. africana reduces their growth rate,acquired non-removing, ticker and fire-resistant bark even during drought seasons; these trees never grow very old and will not be vulnerable to fire in absence of bark harvesting.A similar observation was noticed in conifers,which open their cones or fruit through the influence of fire.The works of Smith and Sutherland(1999a,b;2001)gave a very good explanation of fire scars biology.

    Perspectives,management and strategies of conservation

    The classified forest of Wari-Maro is highly affected by anthropological disturbances.The observed degradation processes comes from repeated fire use,which is related to illegallogging activities and charcoalproduction inside the forest.Actions aimed at managing the sustainability of the Wari-Maro forest must address the following specific objectives:

    (1)To protect the remaining forest cover against human threats by adopting two strategies.The first strategy will move in the direction of policy development for more effective integration of the population in forest managementplans to foster better collaboration.And the second strategy will target the installation of natural firewalls in forest areas with high risk.This firewall will be composed of fire-resistant species with thick bark like Burkea africana.

    (2)To develop a special conservation plan for high sensitive-fire species like Anogeissus leiocarpa and those in dangerofextinction,such as Afzelia africana.

    (3)Finally,to restore degraded areas through reforestation.These management actions require preliminary studies:(i)identification of degraded areas based on satellite images analysis;(ii)evaluation of socioeconomic importance of illegal logging and charcoal production in Wari Maro;(iii)assessment of the intensity of deforestation and identification of vulnerable species.

    AcknowledgmentsThe laboratory investigation was carried out in the International Tree-Ring Lab of Georg-August Universita¨t Go¨ttingen.Therefore a specialthank you goes outto Martin Worbes and Esther Fichtler for their valuable contribution.The research was funded by Deutscher Akademisher Austausch Dienst(DAAD),Biodiversity Monitoring Transect Analysis(BIOTA)project and authors are consequently grateful to the German Federal Ministry of Education and Research.Supportof Roland Holou in the manuscriptediting is very much appreciated.

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    30 April 2013/Accepted:10 August 2013/Published online:25 April 2015

    ?Northeast Forestry University and Springer-Verlag Berlin Heidelberg 2015

    Projectfunding:The research was funded by Deutscher Akademisher Austausch Dienst(DAAD),Biodiversity Monitoring Transect Analysis(BIOTA)project.

    The online version is available at http://www.springerlink.com

    Corresponding editor:Chai Ruihai

    ?Franck Sinsin f.sinsin@gmail.com

    1Laboratoire d’Ecologie Applique′e,Faculte′des Sciences Agronomiques,Universite′d’Abomey-Calavi, 03 BP 1974 Cotonou,Be′nin

    2Laboratory of Biomathematics and Forest Estimations, Faculte′des Sciences Agronomiques,Universite′d’Abomey-Calavi,03 BP 1974 Cotonou,Be′nin

    3Institute of Biosciences,University of Rostock,Wari Maro, Germany

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