Do gender and age influence agroforestry farmers' knowledge of tree species uses in an area of the Atlantic Forest, Brazil?

ABSTRACT

This study aimed to explore the extent of knowledge of tree species and their uses by agroforestry farmers in the Vale do Ribeira, Brazil, to verify whether gender and age are related to species knowledge in different use categories. The study was conducted using semi-structured interviews, guided tours, direct observation and collection and identification of botanical material. Analyses were based on the frequency with which plants were mentioned. Forty farmers (17 women and 23 men aged 18 to 78 years) were interviewed. There were significant differences in the species richness cited exclusively by each gender; the number of species mentioned by men (36 sp.) was higher than by women (11 sp.). Men exhibited a greater knowledge of such categories as construction, organic matter, fuel, animal feed, technology and beekeeping, whereas there were no significant differences for food, medical and other categories. Age was also a distinguishing factor; younger people mentioned the lowest number of species (74 sp.) compared to adults (163 sp.) and the elderly (150 sp.). The greater number of species mentioned exclusively by men may indicate the existence of specialized knowledge, whereas environmental constraints and the availability of plant resources may limit the knowledge of young people.

Keywords
agroforestry farmers; Atlantic Forest; Cooperafloresta; ethnobotany; intracultural variations; Vale do Ribeira

Introduction

Globally, several societies have the potential to offer low-cost technological solutions that are adapted to regional conditions. These societies depend on the qualitative and quantitative aspects of natural resources to survive (Kang & Akinnifesi 2000). Studies that address rural populations are important because they can contribute to the protection and management of plant resources (Albuquerque 1997). In particular, farmers are surrounded by a wide variety of both wild and cultivated plants (Scherr 1991). In addition, the way these populations use, manage and technologically process many of the plants may have been influenced by indigenous knowledge (Oliveira Jr & Cabreira 2012). In this regard, rural communities hold broad knowledge of rain forest uses and can develop well-managed, complex and successful agroforests (Kang & Akinnifesi 2000).

Agroforestry is a practice that prioritizes the use of local resources and knowledge to increase biodiversity and achieve ecological balance in forest succession (Altieri & Nicholls 2012; Lunelli et al. 2013). Trees are not only an important resource for human populations (Assogbadjo et al. 2012; Brandt et al. 2013) but also represent the main structural component of forest areas and are responsible for ecological functions that influence both biotic and abiotic environments (García-Barrios & Ong 2004).

Local knowledge dynamics may be influenced by several factors. Literature highlights gender roles (Guimbo et al. 2011) and age (Mathez-Stiefel et al. 2012), as factors that directly influence the way people interact with plants. Social and cultural contexts determine the roles suitable for women and men and encourage them to develop different activities (Pfeiffer & Butz 2005; Howard & Nabanoga 2007) that may vary over time and differ by region.

Regarding gender, women are usually observed to be in charge of affairs that permeate the home environment-particularly with regard to caring for children and other family members (Howard 2003). However, in rural areas, women are also the largest food producers, accounting for 80 % of the production in Africa, 60 % in Asia and 40 % in Latin America (Howard 2003). Many of these women are involved in the selection and breeding of plant varieties and are genuine guardians of biodiversity (Shiva 2002). In contrast, men tend to focus their activities on paid work such as commercial crops and woodcutting activities-mainly for construction purposes-leading them to work in locations distant from their homes (Camou-Guerrero et al. 2008; Lyon & Hardesty 2014; Ramos et al. 2015)

Age is also a factor to consider because knowledge is traditionally transmitted from generation to generation and can be transformed over time. There is a tendency for older people to have greater knowledge of resources because experiences naturally provide greater opportunities for learning throughout life (Case et al. 2005; Lyon & Hardesty 2014). In this context, migration (Reyes-García et al. 2005; Ceuterick et al. 2008; Gandolfo & Hanazaki 2011), modernization (Quinlan & Quinlan 2007) and access to plant resources (Zuchiwschi et al. 2010; Albuquerque et al. 2011) can influence knowledge variations among different age groups.

A better understanding of people's knowledge can strengthen planning efficiency when choosing species for inclusion in the Agroforest Systems (SAF), improve social acceptability and add value to the local identity. Although studies have been conducted on this topic, no well-defined pattern has emerged (Avilez et al. 2016); therefore, studies that contribute to the understanding of the role of gender knowledge of plants are needed. Based on these considerations, this study aimed to analyse the knowledge and use of tree species by agroforestry farmers in the Vale do Ribeira, Brazil, to investigate the relationships between age and gender and knowledge of tree species in different use categories.

Materials and methods

Study area

This study was conducted in the Vale do Ribeira region, which is located between the southeastern portion of São Paulo State (SP) and the northeastern portion of Paraná State (PR), Brazil (Fig. 1). The climate, according to the Köppen classification, is Cfa-type humid subtropical, with no dry season and a hot summer in which average temperature is approximately 23 °C (Setzer 1966). The average annual rainfall exceeds 1,500 mm; the highest incidence occurs in January and the lowest in August (Lepsh et al. 1990). The region has irregular relief with large altimetric gaps ranging from 2 m in the coastal lowlands to 1,300 m in the mountain zone (Alves 2004). The predominant soils are Argisol and Latosol (Red-Yellow) followed by Cambisol and Entisol (Lepsh 2002). This territory is home to the largest contiguous area of the Atlantic Forest in the country, characterized by dense rain forest (Ivanauskas et al. 2012). Currently, banana crops, cattle and buffalo farming are the most important economic activities in the region. Family farmers and settlements represent approximately 76 % of the rural enterprises, which own 18 % of the total agricultural area (SIT 2013). From social aspects, the population in the Vale do Ribeira has a low income and educational level, a high incidence of infant mortality and illiteracy and a lack of infrastructure and basic sanitation (Adams et al. 2013).

Figure 1
The geographic location of the Vale do Ribeira region highlighting the cities: Barra do Turvo 24°45'23"S and 48°30'17"W), Adrianópolis (24°41′3″S and 48°58′12″W) and Bocaiuva do Sul (25°12'22"S and 49°06'54"W) as well as the respective rural districts where the member families of Cooperafloresta live (Image: Zé Diniz, 2014).

The Association of Agroforestry Farmers of Barra do Turvo and Adrianópolis (Cooperafloresta) started in 1996 after its founders became interested in a newly introduced production model. Historically, the slash-and-burn technique was conducted in this area prior to planting corn, beans and bananas (Neves et al. 2012). However, to meet legal requirements, even the brief time that the land was required to rest (Gomes et al. 2013) contributed to soil degradation processes that hampered agricultural productivity. Famers individually selling their crops was also a limiting factor because of the high costs involved in shipping produce to distant markets. Based on this scenario and thanks to the influence of external actors and institutions, it was possible to transform the conditions of local life.

Today, 112 families are members of the association, including a total of 322 people living in rural districts in the municipalities of Barra do Turvo (SP), Adrianópolis (PR) and Bocaiuva do Sul (PR) along the border of São Paulo and Paraná (Fig. 1). Approximately 5 % of the community's population is involved in association activities. The association focuses on implementing agroecology-based agroforestry methods to generate income, recover local knowledge and educate farmers about environmental issues. This practice has fostered increased production and conservation of biological diversity and natural resources and provided social and economic advantages to the association's members (Steenbock et al. 2013).

The Cooperafloresta is headquartered in Barra do Turvo, a small town 360 km from the city of São Paulo whose total population is 7,729 inhabitants who predominantly live in the rural areas (59 %) (IBGE 2010). Approximately 22.62 % of the residents are illiterate, and the average monthly rural income is R$ 1.068,51 (IBGE Cidades 2016). The main access to the area is a highway that is approximately 30 km from the town centre. Public transportation serves this stretch, whereas the rural districts are served by school buses that provide transportation to the city centre. The first public school was established in 1972 and offered only a basic education, whereas, today, the city has eight public schools that offer preschool, primary and secondary school including youth and adult education (unpubl. res.), a health centre and health professionals that serve people in rural districts.

Cooperafloresta consists of family farmers and, especially, quilombolas". Quilombolas are descendant populations of black slaves who currently perform activities related to agriculture, handicrafts, collecting and fishing (Diegues & Arruda 2001). Barra do Turvo contains a nucleus of remaining quilombolas whose land is measured in Conservation Units (UCs). These are the Sustainable Development Reserves (RDS) of Barreiro-Anhemas, Quilombos of Barra do Turvo and Pinheirinhos: places where traditional people can maintain their way of life as long as they use natural resources sustainably (Brasil 2000). Other quilombola nuclei in the region were granted legal land rights recognition by INCRA (the National Institute of Colonization and Agrarian Reform). These form communities in the neighbourhoods of Pedra Preta, Cedro, Ribeirão Grande/Terra Seca and Reginaldo (Andrade & Tatto 2013).

The members are divided into groups of at least five families in accordance with the rural neighbourhoods where they live. Each group is responsible for choosing a board representative and holding monthly meetings and weekly collective work. Elected representatives represent the group in discussions and decisions at board meetings and are also responsible for disseminating information resulting from the meetings. The collective work can involve either physical labour or training. Collective work is a joint effort that promotes mutual aid among the farmers in the management of their land (Devide et al. 2013) and is conducted in different places. The training efforts are facilitated by the technical body that supports the organization and targeted to develop improved production strategies, commercialization and product certification.

Generally, members are spouses who are jointly involved in managing the agroforestry activities, but other family members may also be involved. In some cases, members' children are also members of the association and have their own management areas, but they also help their parents. The membership requirements involve practicing agroforestry, avoiding the burning of vegetation or the use of pesticides and chemical fertilizers, and participating in training and management activities, collective work and management of the Cooperafloresta. However, new members are permitted only upon the joint approval of the working group and the Council. Member families are also responsible for preparing agroforest management plans; they can count on technical support to achieve this outcome. Among the administrative procedures, self-management of resources is prioritized at both association scope association and individually (agroforestry). Farmers can hold positions at all levels except the technical positions.

Informant profiles

The 40 interviewed farmers, 17 women and 23 men, ranged from 18 to 78 years of age and belong to 23 family units with a mean age of 50 years (Fig. 2). Approximately 78 % of the participants have lived in the area since they were born; another 18 % come from nearby rural areas and 4 % from northeastern Brazil. Regarding education, 42 % attended up to the fourth grade of basic school, 25 % had no schooling, 20 % completed the eighth grade of basic school and 12 % completed high school. Agroforestry production is the exclusive source of income for 20 % of the sampled households. The other families, in addition to agricultural production, may have incomes supplemented by the government (65 %) including retirement, family allowance and pension, hold paid jobs such as cattle farming, beekeeping, public services, tourism and housecleaning or earn income from self-employment (35 %).

Figure 2
Gender distribution in relation to the age groups of the interviewed farmers, members of Cooperafloresta, and the Vale do Ribeira, Brazil.

Ethnobotanical data collection

Meetings were held to present the study proposal and answer questions to obtain prior consent of the association and meet legal procedures involving authorization to access local knowledge (IPHAN authorization No. 01450.004903 /2013-5). Members of the Cooperafloresta who were over 18 years of age and agreed to sign the Free and Informed Consent Term were permitted to participate in the survey. The participants were selected through non-probabilistic sampling using the "snowball" technique (Tongco 2007). The first participants (n = 13) were suggested by the technical staff of the association because they were able to answer the survey questions. In turn, these first participants were asked to refer other farmers. The spouses and children of the first participants were contacted as well because information regarding the use of plants may not be shared among the people in the same household (Araújo et al. 2012).

The sampling effort was assessed by a rarefaction curve associated with the Jacknife 1 index (Williams et al. 2007) and compiled from data generated by EstimateS 9.0 software (Collwell 2013). Rarefaction curves in ethnobotany studies show that the sampling effort is sufficient when few new species are added by completing new interviews (Begossi 1996). Thus, this procedure was conducted for the population in general; a total of 40 participants (23 men and 17 women) were required for the effort to be sufficient. The Jacknife 1 index is used to reduce the underestimation of the true number of species in a single sample and is based on the presence of a species in a single sample unit (Collwell & Coddington 1994). In this case, it was possible to calculate that approximately 80 % of the expected richness (Sobs = 218 and Sest = 272.6) was sampled after the 40 interviews were conducted (Fig. 3).

Figure 3
A rarefaction curve containing the number of cited ethnospecies and the number of interviews conducted with member farmers of Cooperafloresta, Ribeira Valley, Brazil. Confidence intervals are at the 95 % level, and associations with the wealth estimator used Jacknife 1.

Data collection occurred between July 2012 and December 2013 and involved semi-structured interviews (a socioeconomic questionnaire and a free list), guided tours and direct observations (Albuquerque et al. 2014). The socioeconomic questionnaire aimed to define participant profiles based on provided data such as age, gender, occupation, source of income and period of residence. On the free list, the participants were asked to indicate all useful and locally known trees. Based on this list, in a second meeting with the participants, specific questions were asked regarding each of the mentioned plants and concerning their uses. The guided tour consisted of a walk with all participants through yards, gardens, trails and woods where they could encounter the largest number of plants mentioned in the free list. The plant specimens were photographed and, whenever possible, were collected for taxonomic identification and herborization. Additionally, the direct observations were combined with records of the phenomena observed in the field to support the qualitative analyses.

Data analysis

The plants included in the free list were analysed according to their popular names and considering ethnospecies (Hanazaki et al. 2000). When one or more ethnospecies referred to a single botanical species, only one popular name was recorded. The identification of the collected plant material was performed by comparison with herbarium material and by consulting with specialists and through support from the literature. The reference material in the Herbarium Maria Fidalgo Eneyda P. K.-Instituto de Botânica, São Paulo, SP, Brazil, was indicated for each identified species. This procedure was adopted because most specimens are sterile or belong to common species already deposited in the herbarium.

The species on the list were grouped into nine use categories: food, animal feed, construction, fuel, organic matter, medicines, beekeeping, technology and others according to Ramos et al. (2014) and Cunha & Albuquerque (2006) and analysed based on the frequency with which they were mentioned. The participants were classified according to gender (men and women) and age group to identify differences in knowledge between groups. For the age-based categorization, the classification used by the Brazilian institute of geography and statistics-IBGE (2010)-was adopted: 15-24 years (young person, n = 4), 25-59 years (adult, n = 25) and above 60 years (elderly, n = 11). The participants' knowledge was analysed based on the total number and average of the mentioned species and the number of native, exotic and species reported exclusively by each group. To determine whether the variables were significantly different, Kruskal-Wallis tests were applied to the average number of species mentioned by men and women and between young people, adults and the elderly, while chi-square tests were used for the total number of listed species. Both statistical procedures were performed using BioEstat 5.0 software (Ayres et al. 2007).

Results

Knowledge in relation to gender

Knowledge did not differ between the genders with regard to the total richness of known species (X² = 1.94, p = 0.18)-men mentioned 173 (44.13±17.33) and women mentioned 148 (34.76 ± 09.10) species (Tab. 1). When analysing the differences between their knowledge in the respective use categories, as shown in Tab. 2, men mentioned more species in the beekeeping category (X² = 5.78, p = 0.02) and the mean values of species used in construction mentioned by men were higher (H = 6.64, p = 0.09). However, the number of species mentioned exclusively by men (36 sp.) was higher than that mentioned by women (11 sp.) (X² = 13.29, p = 0.0005). Considering the plants exclusively reported by each gender, men mentioned significantly higher species richness in the construction (X ² =13.44, p = 0.0005), organic matter (X ² = 4.78, p = 0.04), fuel (X ² = 7.75, p = 0.009), animal feed (X ² = 5.56, p = 0.02), technology (X ² = 8.25, p = 0.006) and beekeeping (X ² = 10.80, p = 0.0019) categories, whereas in the food (X ² = 2.33, p = 0.19), medical (X ² = 1.38, p = 0.326) and other categories (X ² = 2.61, p = 0.15), there were no significant differences between genders. The 11 species listed solely by women were related to their uses as food (6 sp.), feed (3 sp.), construction (1 sp.), organic matter (1 sp.), medicine (1 sp.) and others (1 sp.).

Table 1
A list of tree species cited as useful by the agroforestry farmers of Barra do Turvo and Adrianópolis in the Vale do Ribeira, Brazil, showing the botanical families, scientific and local names in alphabetical order and their use categories: food (Fd), animal feed (Af), construction (C), fuel (Fl), organic matter (Or), medicines (M), beekeeping (B), technology (T) and others (O). Legend: * Synonyms-when one or more ethnospecies refers to a single botanical species. ** Homonyms (type 1)-when an ethnospecies refers to two or more plant species of the same genus. *** Homonyms (type 2)-when an ethnospecies refers to two or more plant species of different types.

Botanical families/ Scientific name	Local name	Origin	Use categories
ACANTHACEAE
Aphelandra liboniana Linden ex Hook.	Balsamo de bugre	N	M
ADOXACEAE
Sambucus australis Cham. & Schltdl.	Sabugueiro	N	Or, M
ANCARDIACEAE
Astronium graveolens Jacq.	Pau amargo, pau tenente	N	C, Or, M
Anacardium occidentale L.	Caju	N	Fd, M
Lithrea molleoides (Vell.) Engl.	Aroeira**	N	Af, C, Fl, Or, M, O
Schinus terebinthifolia Raddi		N
Mangifera indica L.	Manga	E	Fd, Or, M, O
Myracrodruon urundeuva Allemão	Méssica	N	M, O
Spondias dulcis Parkinson	Cajá manga	E	Fd, C, Or
Spondias mombin L.	Cajá mirim	N	Fd, Or, B
Spondias purpurea L.	Ciriguela	E	Fd, B
ANNONACEAE
Annona emarginata (Schltdl.) H. Rainer	Ariticum, araticum*	N	Fd, Fl, C, Or, T
Annona muricata L.	Graviola	E	Fd, Or
Annona squamosa L.	Fruta do conde, ata*	E	Fd
Annona sylvatica A.St.-Hil.	Ariticum duro	N	Fd
Duguetia lanceolata A.St.-Hil.	Graviola azeda, graviola doce*	N	Fd, Or
APOCYNACEAE
Aspidosperma polyneurum Müll. Arg.	Guatambu perova, perovinha*	N	C, T
Aspidosperma subincanum Mart.	Guatambu	N	Fl, C, T
Tabernaemontana catharinensis A. DC.	Goriana, gueriana*	N	C
AQUIFOLIACEAE
Ilex paraguariensis A. St.-Hil.	Erva mate	N	Fd
ARALIACEAE
Dendropanax cf. cuneatus (DC.) Decne. & Planch.	Caruru, embu**	N	Af, Fd, Or
ARAUCARIACEAE
Araucaria angustifolia (Bertol.) Kuntze	Pinheiro, araucária*	N	Fd, C, M, T
ARECACEAE
Archontophoenix alexandrae (F. Muell.) H. Wendl. & Drude	Palmeira real	E	Fd
Astrocaryum aculeatissimum (Schott) Burret	Brajaúva, bajarova*	N	Af, Fd, C, T
Bactris gasipaes Kunth	Pupunha	N	Af, Fd, C, Or, B
Bactris setosa Mart.	Tucum	N	Fd, Fl, T
Cocos nucifera L.	Coco	E	Fd
Euterpe edulis Mart.	Juçara	N	Af, Fd, Or
Geonoma elegans Mart.	Guaricana	N	Or
Syagrus romanzoffiana (Cham.) Glassman	Jerivá, jarová*	N	Af, Fd, B
ASTERACEAE
Baccharis cf. semiserrata DC.	Tapixaba, alecrim, vassoreira*	N	Or, Fl, M, B
Vernonia densiflora Gardner	Assa peixe	N	Fl, Or, M, B
BIGNONIACEAE
Handroanthus chrysotrichus (Mart. Ex A. DC.) Mattos	Ipê amarelo**	N	C, Or, M, Or, T
Handroanthus serratifolius (A.H.Gentry) S.Grose		N
Handroanthus impetiginosus (Mart. ex DC.) Mattos	Ipê roxo**	N	C, M, Or, T
Handroanthus cf. ochraceus (Cham.) Mattos		N
Jacaranda micrantha Cham.	Carova, varova*	N	Af , Fl, C, M, B. Or, T
BIXACEAE
Bixa orellana L.	Coloral, urucum*	N	Fd, Or, M, O
BORAGINACEAE
Cordia magnoliifolia Cham.	Erva drinda	N	Af
CANNABACEAE
Trema micrantha (L.) Blume	Crandiuva, carandiuva, canjuva*	N	Af, Fl, Or, O
CELASTRACEAE
Maytenus ilicifolia Mart. ex Reissek	Espinheira santa	N	M
CLUSIACEAE
Garcinia cochinchinensis Choisy	Mangustão	E	Fd
Garcinia gardneriana (Planch. & Triana) Zappi	Vacupari	N	Fd, C, Or
CONNARACEAE
Connarus sp.	Amarelinho**		Af , Fl, C, Or, T
EBENACEAE
Diospyros kaki Thunb.	Caqui	E	Fd, Or
ELAEOCARPACEAE
Sloanea guianensis (Aubl.) Benth.	Cabriteira	N	Fl, C
EUPHORBIACEAE
Alchornea glandulosa Poepp. & Endl.	Tapiá, tapiaeiro*	N	Fl, C, Or, B, T
Croton floribundus Spreng.	Tapixingui, capixingui*	N	Af, Fl, C, Or, B
Croton urucurana Baill	Sambueiro	N	Or, Fl
Maprounea brasiliensis A.St.-Hil.	Sucareiro	N	Or
Maprounea guianensis Aubl.	Amarelino**	N	Af, Fl, C, Or
Sapium glandulosum (L.) Morong	Pica cu, leiteiro*	N	Or, B, O
FABACEAE
Anadenanthera colubrina (Vell.) Brenan	Angico, gorocaia*	N	Fl, C, Or, M, B, O
Arachis hypogaea L.	Amendoim	E	Fd
Bauhinia blakeana Dunn.	Pata de vaca	E	M, Fl
Caesalpinia echinata Lam.	Pau Brasil	N	C
Carya illinoinensis (Wangenh.) K. Koch	Noz Pecã	E	Fd
Cassia ferruginea (Schrad.) Schrad. ex DC.	Canafrista, quaresmeira*	N	Fl, C, B, Or, T
Centrolobium tomentosum Guillemin ex Benth.	Aririvá, ararivá, araribá, arivá**	N	Fl, C, Or, T
Tachigali cf. multijuga Benth.		N
Copaifera langsdorffii Desf.	Copaíba	N	Af, C, M, T
Dahlstedtia pinnata (Benth.) Malme	Cabreuva	N	C
Dinizia excelsa Ducke	Angelim	N	C, B, T
Enterolobium contortisiliquum (Vell.) Morong	Caquera**	N	C, M, B
Senna multijuga (Rich.) H.S.Irwin & Barneby		N
Erythrina crista-galli L.	Corticeira brejo	N	Or
Erythrina sp.	Corticeira, cortumeiro, mulungu*		Or, M, B, O
Erythrina speciosa Andrews	Eritrina	N	Or, O
Hymenaea courbaril L.	Jatobá, Jataí*	N	Af, Fd, Fl, C, M, T
Inga spp.	Ingá		Fd, Fl, Or, B
Inga edulis Mart.	Ingá cipó, ingá de metro*	N	Af, Fd, Fl, Or, B
Inga sessilis (Vell.) Mart.	Ingá macaco, ingá branco*	N	Af, Fd, C, Or, B, O
Inga marginata Willd.	Ingá mirim, ingá feijão*	N	Af, Fd, C, Or, B, O
Leucaena leucocephala (Lam.) R. de Wit.	Leucena	E	Fl, C, Or
Lonchocarpus muehlbergianus Hassl.	Imbira caboclo, timboeiro, timbó*	N	Fl, C, Or, T, O
Machaerium nyctitans (Vell.) Benth.	Bico de pato	N	Af, Fl, C, Or, B, T
Machaerium stipitatum Vogel	Carandá, sapuva, asa de grilo*	N	Fl, C, T
Mimosa scabrella Benth.	Bracatinga	N	Af, Fl, C, Or, B, T
Myrocarpus frondosus Allemão	Cabureira, caburê, cabuí*	N	C
Myroxylon peruiferum L.f.	Jacarandá	N	Fd, Fl, C, Or, B, T
Ormosia arborea (Vell.) Harms	Olho de cabra	N	Or
Piptadenia gonoacantha (Mart.) J.F. Macbr.	Jacaré	N	Fl, C, Or, M
Piptadenia paniculata Benth.	Mamica de cabela	N	Fl, Or, M
Schizolobium parahyba (Vell.) Blake	Guapiruvu	N	Fl, C, Or, T, O
Swartzia submarginata (Benth.) Mansano	Guê	N	Fl, C
Vitex polygama Cham.	Tarumã	N	Af, Fd, Fl, C, M
LAURACEAE
cf. Cinnamomum sp.	Canela**		Fl, C, T
Nectandra megapotamica (Spreng.) Mez		N
Cinnamomum triplinerve (Ruiz & Pav.) Kosterm.	Canela amarela	N	Af, C, Or, B, T
Cryptocarya sp.	Canela iutinga, canela niutinga*		Af, Fl, C, M
Nectandra membranacea (Sw.) Griseb.	Canela preta	N	C, T
Ocotea brachybotrya (Meisn.) Mez	Canela feijão	N	C
Ocotea prolifera (Nees & Mart.) Mez	Canela sassafrás, canela cravo, canela de cheiro**	N	Fd, C, M, T
Ocotea puberula (Rich.) Nees	Canela niuva, canela sebo, canela branca*	N	Af, Fl, C, Or, M, T
Persea americana Mill.	Abacate	E	Fd, Fl, Or, M
Persea willdenovii Kosterm.	Canela andrade	N	C, M
LECYTHIDACEAE
Cariniana estrellensis (Raddi) Kuntze	Imbira caboclo branca	N	O
LYTHRACEAE
Punica granatum L.	Romã	E	Fd, M
MAGNOLIACEAE
Magnolia ovata (A. St.-Hil.) Spreng.	Maria mole, vaguaçu*	N	C
MALPIGHIACEAE
Malpighia emarginata DC.	Acerola	E	Fd, Or
MALVACEAE
Ceiba speciosa (A. St.-Hil.) Ravenna	Paineira	N	Af , Or
Dombeya wallichii(Lindl.) Baill.	Atrapéia, estrapéia*	E	Or, B
Luehea divaricata Mart. & Zucc.	Açoita cavalo, tamanqueira, tucaneira*	N	Af, Fl, C, Or, M, B, T
Malvaviscus arboreus Cav.	Sapateira	E	C
Pachira glabra Pasq	Castanheira	E	Fd
Pseudobombax grandiflorum (Cav.) A.Robyns	Embiruçu, imbiruçu*	N	Af, Or, O
Theobroma cacao L.	Cacau, cacau amarelo*	E	Fd
MELASTOMATACEAE
Tibouchina fothergillae (Schrank & Mart. ex DC.) Cogn.	Jacatirão, flor de maio, natal**	N	Fl, C, Or, B, O
Tibouchina mutabilis (Vell.) Cogn.		N
MELIACEAE
Cabralea canjerana (Vell.) Mart.	Cajarana, canharanda*	N	Af , C
Cedrela fissilis Vell.	Cedro, cedro branco*	N	C, Or, M, T, O
Khaya senegalensis (Desr.) A. Juss.	Mogno africano	E	C
Melia azedarach L.	Espinheira santa, santa barbara**	E	Af, Fl, C, T
Swietenia macrophylla King	Mogno	N	C
Toona ciliata M.Roem.	Cedro australiano	E	C
MORACEAE
Artocarpus heterophyllus Lam.	Jaca	E	Af, Fd, Fl, C, Or, M, O, T
Ficus luschnathiana (Miq.) Miq.	Figueira branca	N	Af, C, Or
Maclura tinctoria (L.) D. Don ex Steud.	Taiuva, amoreira branca*	N	Af, Fd, C, Or, M
Morus nigra L.	Amora	E	Af, Fd, C, Or, M, O
MUNTINGIACEAE
Muntingia calabura L.	Calabura	N	Af, Fd
MYRISTICACEAE
Virola cf. bicuhyba (Schott ex Spreng.) Warb.	Bucuveira**	N	Af, C, M, Or
MYRTACEAE
Campomanesia neriiflora (O.Berg) Nied.	Gabiroba miúda	N	Fd, C, M, T
Campomanesia phaea (O.Berg) Landrum	Cambuci	N	Fd
Campomanesia xanthocarpa (Mart.) O.Berg	Gabiroba, gabiroba amarela, gabiroba de porco	N	Af, Fd, Fl, C, Or, M, B, T
Eucalyptus sp.	Eucalipto	E	Fl, C, Or, M
Eugenia beaurepairiana (Kiaersk.) D.Legrand	Murta	N	Af, Fd
Eugenia brasiliensis Lam.	Grumixama	N	Fd
Eugenia florida DC.	Camarinho	N	Af, Fd, Fl, C, Or, B
Eugenia involucrata DC.	Cereja	N	Af, Fd, C, B
Eugenia pyriformis Cambess.	Uvaia, ovalha**	N	Fd
Psidium myrtoides O.Berg		N
Eugenia sp.	Vatinga		C
Eugenia uniflora L.	Pitanga	N	Fd, M, B, Or
Myrcia splendens (Sw.) DC.	Guamirim	N	Fl, B
Myrciaria glazioviana (Kiaersk.) G.M.Barroso ex Sobral	Cabeludinha	N	Fd, Af
Pimenta pseudocaryophyllus (Gomes) Landrum	Canela sassafrás, canela cravo, canela de cheiro**	N	Fd, C, M, T
Plinia peruviana (Poir.) Govaerts	Jabuticaba	N	Fd, M
Psidium cattleianum Sabine	Araçá**	N	Af, Fd, Fl, C, Or, M
Psidium cf. rufum DC.		N
Psidium guajava L.	Goiaba	E	Fd, Fl, C, Or, B
Syzygium cumini (L.) Skeels	Jambolão	E	Af, Fd
Syzygium jambos (L.) Alsto	Jambo, jambre*	E	Fd
OLACACEAE
Tetrastylidium grandifolium (Baill.) Sleumer	Mandigaru	N	C
OXALIDACEAE
Averrhoa carambola L.	Carambola	E	Af , Fd, B
PERACEAE
Pera glabrata (Schott) Poepp. ex Baill.	Bucuveira**	N	Af, C, M, Or
PHYLLANTHACEAE
Hieronyma alchorneoides Allemão	Urucurana, urucuveira, nicurana*	N	Af, Fd, Fl, C, Or, O, T
PHYTOLACCACEAE
Gallesia integrifolia (Spreng.) Harms	Guararema, pau d'alho*	N	Fd, C, Or, O, T
Phytolacca dioica L.	Caruru, embu**	N	Af, Fd, Or
Seguieria langsdorffii Moq.	Limoeiro bravo	N	Or, B
PIPERACEAE
Piper aduncum L.	Jaborandi**	N	Af, Fd, Fl, Or, M
Piper arboreum Aubl.		N
PRIMULACEAE
Myrsine cf. lancifolia Mart.	Pororoca, capororoca*	N	Af, Fl, C, Or
PROTEACEAE
Roupala montana cf. var. brasiliensis (Klotzsch) K.S.Edwards	Carvalho	N	C, M, T
RHAMNACEAE
Hovenia dulcis Thunb.	Uva japão	E	Af, Fd, Fl, C, Or, B
ROSACEAE
Eriobotrya japonica (Thunb.) Lindl.	Ameixa	E	Af, Fd, Fl, M, B
Malus x domestica Borkh.	Maçã	E	Fd
Prunus myrtifolia (L.) Urb.	Pêssegueiro bravo	N	C, O
Prunus persica (L.) Batsch	Pêssego	E	Fd, Or, M, B
Pyrus communis L.	Pêra	E	Fd
RUBIACEAE
Bathysa australis (A. St.-Hil.) Hook. f. ex K. Schum.	João henrique	N	Or
Coffea arabica L.	Café	E	Fd, M
Coutarea hexandra (Jacq.) K.Schum	Quina amarela	N	Af, C, M, T
Genipa americana L.	Jenipapo	N	Fd
Posoqueria latifolia (Rudge) Schult.	Fruto de macaco, limão macaco*	N	Fd
Psychotria suterella Müll. Arg.	Alface de anta	N	Af
RUTACEAE
Citrus x aurantiifolia (Christm.) Swingle	Lima da pérsia, limão galego*	E	Fd
Citrus × latifolia Tanaka ex Q. Jiménez	Limão taiti	E	Fd
Citrus limon (L.) Osbeck	Limão, limoeiro	E	Fd, M, B
Citrus x limonia Osbeck	Limão rosa	E	Fd
Citrus reticulata Blanco	Mexirica	E	Fd, M
Citrus X sinensis (L.) Osbeck	Laranja, laranja bahia, laranja pêra*	E	Fd, Fl, M, B
SABIACEAE
Meliosma itatiaiae Urb.	Orelha de mula	N	C, Or, T
SALICACEAE
Casearia cf. obliqua Spreng.	Erva de macuco, guaçatunga**	N	Fl, C, Or, M, O
Casearia sylvestris Sw.		N
SAPINDACEAE
Cupania oblongifolia Mart.	Migué pintado	N	Fl, C, Or, T
Litchi chinensis Sonn.	Lichia	E	Fd
Matayba intermedia Radlk.	Caviuna	N	C, T
SAPOTACEAE
Chrysophyllum inornatum Mart.	Aleixo	N	T
Pouteria caimito (Ruiz & Pav.) Radlk.	Abiu	N	Fd
SOLANACEAE
Acnistus arborescens (L.) Schltdl.	Fumo bravo	N	Af, C, Or
Cestrum intermedium Sendtn.	Erva de sabiá, pimenta de sabiá*	N	Af, Or
Solanum granulosoleprosum Dunal	Cuvitinga	N	Af, Or, B
Solanum paniculatum L.	Jurubeba	N	M
Solanum pseudoquina A.St.-Hil.	Quina branca	N	Af, Fl, C, Or, B, T
URTICACEAE
Cecropia spp.	Embaúba		Af, Fd, Fl, C, Or, M
Cecropia glaziovii Snethl.	Embaúva vermelha	N	Af, Or, M,
Cecropia pachystachya Trécul	Embaúva branca	N	Fl
Coussapoa microcarpa (Schott) Rizzini	Figueira mata pau	N	Or
VERBENACEAE
Aloysia virgata (Ruiz & Pav.) Juss.	Repeludo	N	Af, Fl, B
Citharexylum myrianthum Cham.	Jacataiuva	N	Fl, C, B
VOCHYSIACEAE
Vochysia magnifica Warm.	Guaricica, guarapicica*	N	C
UNDERTERMINED
Undetermined 1	Aurêque		Or
Undetermined 2	Calvi		C
Undetermined 3	Canela bataieira		C
Undetermined 4	Canela bosta		C
Undetermined 5	Canela carne de paca		Fl, C, Or
Undetermined 6	Canela cascuda		C
Undetermined 7	Canela coqueiro		C, Or, T
Undetermined 8	Canela embuia, embuia		C
Undetermined 9	Canelinha		Af, C, Or, T
Undetermined 10	Caxeta		C, T
Undetermined 11	Ceboleiro		C
Undetermined 12	Cedro rosa		C
Undetermined 13	Comocaia		Fd
Undetermined 14	Coração de bugre		Fl, C, T
Undetermined 15	Cuvatã		C, T
Undetermined 16	Figueira		Af, Fl, C, Or, T
Undetermined 17	Figueira preta		Af, C, Or
Undetermined 18	Figueira verdadeira		Af, Or
Undetermined 19	Flor de cuitelo		Or
Undetermined 20	Guaçatunga branca		C, B
Undetermined 21	Guaçatunga preta		C, B
Undetermined 22	Guapeba		C
Undetermined 23	Guaraqui		C, T
Undetermined 24	Imbira caboclo amarela		Or
Undetermined 25	Ipê		C, M, T
Undetermined 26	Ipê branco		C, T
Undetermined 27	Ipê rosa		C
Undetermined 28	Jacatirão branco		Fl, C
Undetermined 29	Jacatirão preto		Fl
Undetermined 30	Jaracacha		Fd
Undetermined 31	Jequitibá		C
Undetermined 32	Juá		M
Undetermined 33	Madeira de são joão		C
Undetermined 34	Maria preta		C, T, Or
Undetermined 35	Pau de sangue branco		C
Undetermined 36	Pau de sangue vermelho		M
Undetermined 37	Pau gambá		M
Undetermined 38	Pau de sangue, insangueiro		Or, C
Undetermined 39	Peroba amarela		C, T
Undetermined 40	Peroba escura		C
Undetermined 41	Peroba graúda		C
Undetermined 42	Peroba miúda		C
Undetermined 43	Peroba rosa		C
Undetermined 44	Vapuana		Af, C

Table 2
Analysis of the influence of gender on the knowledge of local tree species among farmers who are members of Cooperafloresta, the Vale do Ribeira, Brazil, in different use categories. TN: total number of cited species, TA: total average of cited species, NC: number of cited native species, NE: number of cited exotic species, and Ec: number of cited exclusive species. H: men (n = 23), M: women (n = 17). Data are presented as means ± standard deviations. Different letters in the same row indicate significant differences through Chi-Square* (p<0.05) and Kruskal-Wallis** (p<0.05) tests. ^x denotes sampling sizes insufficient to perform statistical testing.

Categories	TN*		TA**		NC*		NE*		Ec
	M	W	M	W	M	W	M	W	M	W
Food	75a	68a	17.91 ± 7.30 a	16.88 ± 5.87a	40a	35ª	35a	33a	14a	7a
Construction	74a	52a	14.83 ± 9.31b	7.59 ± 4.47a	65a	44ª	9a	8a	29b	7a
Org. matter	65a	50a	6.83 ± 5.37a	5.59 ± 3.24a	53a	39ª	12a	11a	31b	16a
Fuel	59a	44a	5.78 ± 4.04a	6.18 ± 3.15a	53a	38ª	6a	6a	22b	7a
Medicine	47a	53a	5.22 ± 3.64a	8.29 ± 5.44a	37a	41ª	10a	12a	10a	16a
Animal feed	44a	28a	3.39 ± 3.66a	2.88 ± 2.55a	36a	21ª	8a	7a	31b	15a
Technology	44a	27a	4.57 ± 3.63a	2.53 ± 2.43a	42b	23ª	2x	4x	26b	9a
Others	25a	34a	2.17 ± 2.08a	2.94 ± 3.17a	22a	30ª	3x	4x	11a	20a
Beekeeping	37b	19a	2.91 ± 4.28a	1.53 ± 2.12a	29b	12ª	8x	7x	24b	6a

Knowledge in relation to age

The total species richness was 74 (33.25±20.55) by young people, 163 (39.08±12.96) by adults and 150 (45.09±18.19) by the elderly. Statistically, significant differences were found when young people were compared with adults (X² = 33.42, p < 0.0001) and with the elderly (X² = 30.12, p < 0.0001), indicating that the species richness familiar to participants aged 18-24 is below that of adults and the elderly. However, adults and the elderly (X² = 0.54, p = 0.49) mentioned a similar number of useful trees. The analysis of the influence of age in terms of knowledge of use categories (Tab. 3) revealed that adults mentioned more species employed as organic matter, fuel and medicine than did young people (X² = 33.13, p < 0.0001; X² = 35.83, p < 0.0001; X² = 45.06, p < 0.0001, respectively) and the elderly (X² = 13.88, p = 0.0003; X² = 7.51, p = 0.0084; X² = 6.54, p = 0.01, respectively). The elderly mentioned higher average values of species used for technology than did young people (H = 7.58, p = 0.005) or adults (H = 4.46, p = 0.03).

Table 3
A variance analysis of tree species knowledge by age group of farmers associated with Cooperafloresta, the Vale do Ribeira, Brazil, across different use categories. TN: total number of cited species, TA: total average of cited species, NC: number of cited native species, NE: number of cited exotic species, Ec: total number of cited exclusive species. J: young person (18-24 years, n = 4), A: adult (25-59 years, n = 25) and I: elderly (>60 years, n = 11). Data are presented as means ± standard deviations. Different letters in the same row indicate significant differences through Chi-Square* (p<0.05) and Kruskal-Wallis** (p<0.05) tests. ^x denotes sampling sizes insufficient to perform statistical testing.

Categories

TN*

AvT**

NC*

NE*

Ex

Y

A

E

Y

A

E

Y

A

E

Y

A

E

Y

A

E

Food

42a

69b

66b

20.25 ± 12.84a

16.72 ± 5.13a

18.18 ± 7.80a

13a

36b

33b

29a

33a

33a

1a

14b

9b

Construction

16a

71b

63b

5.75 ± 5.44a

10.96 ± 7.24a

15.73 ± 10.29a

12a

61b

56b

4a

10a

7a

1a

17b

8b

Org. matter

17a

71c

33b

5.75 ± 3.10a

7.04 ± 4.98a

4.82 ± 3.95a

13a

56c

30b

4a

15b

3a

1a

38b

8a

Fuel

9a

58c

32b

2.25 ± 1.89a

6.84 ± 3.53b

5.27 ± 3.61ab

8a

50c

30b

1x

8x

2x

1a

31b

6a

Medicine

4a

56c

32b

1.00 ± 1.15a

7.80 ± 4.86b

5.64 ± 3.41b

4a

44c

25b

0a

12b

7b

0a

31c

7b

Animal feed

0a

43b

37b

0a

3.8 ± 2.84b

4.55 ± 3.83b

0a

33b

31b

0a

10b

6b

0a

22b

16b

Technology

1a

44b

32b

0.25 ± 0.50a

3.28 ± 2.79b

5.91 ± 3.62c

1a

39b

30b

0x

5x

2x

0a

21c

9b

Others

5a

29b

28b

1.25 ± 0.50a

2.20 ± 2.16a

3.64 ± 3.56a

3a

25b

26b

2x

4x

2x

0a

15b

14b

Beekeeping

6a

32b

21b

1.50 ± 3.00a

2.52 ± 4.00a

2.18 ± 2.82a

4a

24b

16b

2x

8a

5a

0a

19b

11b

Considering the plants reported exclusively among age groups, the number of species cited by adults (29 sp.) was higher than that cited by youngsters (2 sp., X ² = 23.51, p < 0.0001) and the elderly (9 sp., X ² = 10.52, p = 0.0021) and was significantly different regarding the use categories: organic matter (adult × youngster, X ² = 35.10, p < 0.0001; adult × elderly, X ² = 19.56, p < 0.0001), fuel (adult × youngster, X ² = 28.12, p < 0.0001; adult × elderly, X ² = 16.89, p < 0.0001), medicine (adult × youngster, X ² = 31, p < 0.0001; adult × elderly, X² = 15.15, p = 0.0002) and technology (adult × youngster, X ² = 21, p < 0.0001; adult × elderly, X ² = 4.8, p = 0.0446). The species mentioned only by young people were in the food and construction categories, whereas the plants known exclusively by the elderly were in the animal feed (3 sp.), fuel (1 sp.), organic matter (2 sp.), medicine (1 sp.), technology (1 sp.) and other categories (4 sp.).

Discussion

Knowledge in relation to gender

Homogeneous knowledge between the genders has been reported by other studies (Sop et al. 2012; Brandt et al. 2013) and may be related to the knowledge is transmitted (Reyes-García et al. 2009). In this case, the collective work helped agroforestry management to become a rich opportunity for learning and sharing experiences among all the participants (Steenbock et al. 2013). Collective work is often used to manage tasks such as opening new areas and planting that require extra manpower. However, the training efforts are aimed at integrating technical and scientific knowledge with local knowledge to develop improved production strategies, commercialization and product certification. In this sense, Reyes-García et al. (2009) highlighted the importance of social relations in the construction of knowledge, in which the status of an individual in a network of information may explain the levels of the knowledge that individual acquires.

However, the fact that some species were exclusively mentioned by each gender indicates specialized knowledge in certain use categories because women and men have distinct jobs and social interactions (Howard 2003; Camou-Guerrero et al. 2008; Reyes-Garcia et al. 2010). Previous studies have found that women have greater knowledge of native species for food and medicinal use (Voeks & Leony 2004; Camou-Guerrero et al. 2008; Guimbo et al. 2011), whereas men possess more knowledge about native tree species used in construction and technology (Estrada-Castillón et al. 2014; Lyon & Hardesty 2014; Ramos et al. 2015).

This knowledge divergence may relate to the farmers' relationships with biodiversity (Zuchiwschi et al. 2010; Albuquerque et al. 2011). In the past, attempts to diversify the local economy through extensive cattle farming and exploitation of palm and timber resources may have put men in closer contact with the local flora. The difficult access and long distances to work locations from residences meant that these activities were mainly conducted by men; women had limited time to stay in these places. Moreover, the work of managing these plant resources often involved physical issues. This disparity may explain why men were able to mention a greater number of exclusive species used as timber.

Currently, men still go travel to forested areas more often and work there longer than women because of the distance between these locations and people's homes. Despite conducting the same type of farming activity, the responsibilities of each gender were somewhat different. Sometimes, women and men work together to determine planting times, the planted varieties, the amount of stored seeds and whether they were bought or traded, which are the main factors in preserving biodiversity "in situ". In this case, men leave in the morning or late in the afternoon to perform pruning, weeding or harvesting in the more distant agroforestry fields, while women travel to these locations less frequently. Instead, the women care for backyard areas and agroforest orchards located close to their homes as well as assume the primary family caregiver roles such as meal preparation and the treatment of diseases. However, there are a few families in which only women are members and bear the primary responsibility for agroforestry management-in addition to taking care of the family. This finding corroborates with worldwide growth in the number of women who have assumed the householder role in rural areas (1/3 of homes around the world, Howard & Nabanoga 2007) due to the migration of men to the cities.

Knowledge in relation to age

Several authors have reported that individuals in their respective studies became more knowledgeable as their age increased (Mathez-Stiefel et al. 2012; Sop et al. 2012). One of the reasons why older people have accumulated more knowledge than younger people may be related to the experiences these individuals have during their lives. In this sense, higher average species mentions and higher exclusive species mentions by the elderly in the technology category may be related to the experiences and opportunities that occurred during each individual's life (Phillips & Gentry 1993). Canoes, for example, were widely used by farmers in the past as a means of transportation. However, the construction of the Capivari-Cachoeira dam system reduced the flow of the Turvo River, hindering river navigation in the region. In addition to canoes, many farmers made household items such as sieves, spoons, mortars and pestles from native flora. However, many of these items have been replaced by manufactured versions or are no longer used, reducing the need for technological uses of the native flora by the younger population.

The greatest richness of useful species mentioned by the 25-59 age group involved the organic matter, fuel and medicine categories. This result may indicate that adults have greater contact with the plant resources used for these purposes. Estrada-Castillón et al. (2014) found an accumulated knowledge regarding the number of citations of useful species for the same age group in a population in semi-arid Mexico. People in this age group may be more active in agroforestry management and recognize the importance of vegetation cover; therefore, they experiment with several species. However, a greater knowledge of species for use as fuel may be associated with lower costs: people more often use wood than gas stoves to prepare food. Adults also cited a greater number of exotic species in the construction category. This result may be related to current environmental legislation that encourages the abandonment and replacement of native species by exotic ones (Oliveira Jr et al. 2013).

Moreover, learning takes time, which may be one reason why older people tend to have accumulated more knowledge than young people. Young people's repertoire of information regarding the local flora may increase as they have more opportunities to learn about them. However, some studies show that age cannot be a differentiating factor in the variation of knowledge because young people attend the houses of elders to learn their teachings (Martins et al. 2014). In this regard, Cooperafloresta has a training programme on agroforestry for children and adolescents, in which the members' children meet regularly with educators and other farmers to learn about agroecology principles and agroforestry practices. Another objective of this training is to minimize migration by young people by providing them with tools that allow them to be engaged with the association.

The small number of young people interviewed shows that they have mostly moved to urban centres in search of better employment opportunities and access to education. Farmers in this study supported the access of their children to formal education, but-unlike those observed by Legesse et al. (2013), the parents also encourage their children to undertake activities related to agroforestry to make a higher quality of life possible. There are many cases of children who studied abroad so that they could bring back their newly acquired expertise to their place of origin after graduation. However, when the young people do not return, migration also affects knowledge preservation by causing a break in the transmission of information that can affect the knowledge of the use of plant resources in the long term.

It is important to remember that this study made a deliberate selection of participants who have greater knowledge of local resources. This limits the interpretation of the results because they represent this particular group's knowledge rather than the knowledge of the entire community. Unexpectedly, the results showed no differences in the total knowledge of mentioned species between genders, but when considering the species reported exclusively by each group, the men mentioned significantly higher numbers of species, which may indicate the existence of specialized knowledge in this group for certain categories. As expected, age proved to be a differentiating factor: young people cited fewer species compared with adults and the elderly, and the fact that the experiences occur throughout each individual's lifetime may be related to older people's greater accumulation of knowledge.

The ethnoknowledge in agroforestry systems differs from that in groups with more traditional relationships with the forest. This difference occurs because agroforestry systems-especially those with an agroecological base, as in Cooperafloresta-include components such as feminism and the empowerment of young people, which can introduce differences in the pattern of knowledge between gender and age. Another interesting point is that young people were traditionally included in the family dynamics, working as assistants to their parents, fostering strong knowledge transmission. Among young agroforestry farmers we find that young protagonists act with more autonomy when compared to historical times and, in addition to family dynamics, they obtain knowledge from other sources such as joint efforts, workshops and interactions with technical experts (not necessarily only through formal education), all of which are much more prevalent today.

Acknowledgements

The authors extend their appreciation and gratitude to the farmers who contribute to the survey; to Carlos Carriel and Rodrigo Ozelame, who facilitated the initial dialogue; to the support by Fundação Florestal, especially Wagner Portilho and Airton Vieira; to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the scholarship granted to the first author; and finally, to Sonia Aragaki Filomena Dias , Geraldo Franco, João Baitello and Osny de Aguiaro for their efforts in botanical identification.

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Publication Dates

• Publication in this collection
  Oct-Dec 2016

History

• Received
  29 June 2016
• Accepted
  16 Nov 2016