GEOGRAPHIC DIVERSITY OF CURRENTLY FRUIT TREE SPECIES IN ALBANIA

Transcription

1 GEOGRAPHIC DIVERSITY OF CURRENTLY FRUIT TREE SPECIES IN ALBANIA Belul Gixhari 1 ; Ilir Çiçi 1 ; Raimonda Sevo 1. ( 1 ) Albania Gene Bank, Agricultural University of Tirana, Tirana. agb08dokument@gmail.com; gixharibelul@ubt.edu.al

2 Introduction: Fruit Tree Species Fruit tree crops and especially wild species provide an invaluable source of genes for the improvement of cultivated fruit crops. Albania is one of the Balkan countries with high level of diversity for many cultivated and wild species including currently fruit tree crops. Genetic resources of fruit trees have a major contribution to the growth of agricultural food products in all regions of Albania. Fruit trees are economically, socially and culturally important crops grown over a wide range of ecological habitats in the country, in the range of 10,190 million trees, MAFCP (2010). 2

3 Plant Genetic Resources Plant genetic resources (PGR) play a key role in contributing to the sustainable development of agriculture, helping to increase agricultural food productions. Today, preservation of genetic resources is regarded as an important need for human society. The gene banks offer the main means to store genetic plant materials, and they protect genetic materials, providing the raw material for the improvement of crops. 3

4 Geographic studies provide critical information about the diversity present in specific geographic areas, Maxted et al. (1995). can be used for the assessment of the current conservation status of PGR and can be used for the prioritization of the areas suitable for in situ conservation. Geographic information systems (GIS) are useful tools for ecogeographic analysis, Guarino et al. (2002). 4

5 Documentation of PGR Increasing of usage value of the fruit tree species, in ex situ (field collection) and on farm status of conservation, needs a wellorganized documentation system. Today documentation of PGR is considered an integral part of the conservation of plant genetic resources. The purposes of the study = Application of GIS tools for: Improvement of gene-bank collections representation. Detection of higher diversity areas, and diversity differences between areas. Identification of the prioritized collecting sites, and gaps. Development of a more systematic strategy of conservation. ICE 2012, June,1-4, Tirana, ALB B. GIXHARI (Agriculture University of Tirana) 5

6 Materials and methods Description of the study area: The research was conducted in 11 districts of Albania (ALB): Berat (BR), Dibra (DI), Durres (DR), Elbasan (EL), Fier (FR), Gjirokaster (GJ), Korce (KO), Kukes (KU), Shkoder (SH), Tirana (TR) and Vlora (VL). The geographic areas were separated into small grid square cells (25 x 25 km). To include all species at least once, 34 grid cells were selected. Combination analysis of species occurrence data with climatic data, was realized using higher resolution grid square cells (5 x 5 km = 2.5 min), and free GIS World Environmental data for ALB. 6

7 Materials and methods Data sampling: Each individual plant/species represents a georefernced observation = known as presence point. Presence points include basic passport data, an identification code (ID), the taxonomic name, longitude and latitude. All Geo-referenced observations, chosen to carry out spatial analysis, were entered into the GIS analysis, as presence points. Diversity distribution: The analysis focuses solely on the study of diversity at the species levels (unit of α diversity). Species diversity include: the number of species (richness-r) and how equally abundant the species are (evenness-e). 7

8 Materials and methods Species richness and evenness Species richness (S) was calculated as a simplest account of the number of different species in a given area and the species evenness (E) as the relative abundance of individuals among the species. For GIS analysis in this study: Diversity indices as Shannon's diversity index (H), Brillouin index (B), Simpson's index (D), Simpson reciprocal index (1/D), Margalef's index (D MG ), and Richness estimators (E abundance and evenness) as Chao-1 and 2; Jacknife-1 and 2, were used. 8

9 Materials and methods: Diversity Indices: Shannon's diversity index (H), takes into account the number of species and the evenness of the species. Brillouin index (B), is used instead of the Shannon index when diversity of non random samples or collections is being estimated. Simpson's index (D), gives the probability of any two individuals, drawn at random from an infinite community, belonging to different species. Simpson reciprocal index (1/D), To eliminate misinterpretation of Simpson index (where low value of D show higher diversity and otherwise) we used Simpson reciprocal index (1/D) easy to be interpretated. Margalef's index (D MG ), is a diversity index weighted towards species richness. Diversity Indices were calculated using Biodiversity & DIVA-GIS tools. 9

10 Materials and methods: Richness estimators: Chao-1 and 2: An estimation method to predict how many species would have been discovered the if sampling had been more intensive. Jacknife-1 and 2: An estimation method to predict how many species would have been discovered if the sampling had been more intensive Richness estimators were calculated using Biodiversity & DIVA-GIS tools. 10

11 Materials and methods Reserve selection: Distinction of the minimum number of areas (grid cells) necessary to conserve a given number of species, varieties or alleles of the gene pool under study Hijmans et al. (2001), was realized using reserve selection modelling, developed by Rebelo et al.(1992). Reserve selection ranks grid cells that should be given priority for conservation of PGR, Scheldeman et al. (2010). Cluster analysis method was used to measure distance or similarity between species presence/absence in different areas (grid cells). 11

12 Results and discussion: Data quality Data quality includes the accuracy and precision of geographic coordinates and documenting farmer named species and knowledge's. All data recorded during collecting expeditions were checked for inconsistencies and quality. Data points without coordinates were removed. Data points with incorrect coordinates on the administrative unit (district) were assigned coordinates where possible while duplicate or doubtful data were removed. All tree species were also screened carefully to resolve any scientific name conflicts. 12

13 Results and discussion Geographic distribution: After checking the data and autocorrelation of present points, from a total of 768 presence points (32 species), only 592 Georeferenced observations (21 species) were used to evaluate the geographic distribution and diversity of currently fruit tree species grown in Albania. Study results for: Diversity indices (D- group) and Richness Estimators (E-group), and mean values (averages) of each grid cells, and standard deviations of means, used to assess diversity are given on the Fig 1 and table 1. 13

14 Fig 1: Geographic distribution of fruit tree species 14

15 Table 1. Diversity indices (D- group) and Richness Estimators (Egroup), mean values and standard deviations of means, calculated for each collecting areas (District). 15

16 Diversity distribution and species richness results: Study results analysis show the presence of variability between observed areas related to number & kind of tree species collected (α diversity) and different geographic distribution of fruit tree species and diversity differences between areas and (β diversity). Spatial analysis detects areas of high diversity (α diversity): Districts of EL, TR and DI were the areas where high species richness (S) was observed (respectively 16, 13, and 13 species). At the second range with highest number of species were KO, BR, FR, VL and SH districts (S = 10 species). Low species richness occurs in KU and DR districts (S 3 and 7) 16

17 Richness map of fruit tree species 17

18 Diversity indices (D): Margalef index values (D MG ) > 2.80 show presence of higher species diversity in the areas of EL, BR, DI and FR districts. Shannon index values (H > 2.20) show the presence of higher diversity in areas of EL, TR and DI districts. Simpson reciprocal index (1/D > 0.87) shows presence of higher diversity in districts of DI, BR, FR, KO and TR districts. Brillouin index values (B > 2.00) clearly shows that high species diversity occurs in EL, DI and TR districts. 18

19 Richness estimators (E): Richness estimators (E abundance and evenness) as Chao-1 and 2; Jacknife-1 and 2 estimators, calculated using DIVA-GIS tools, show the presence of differences between areas analyzed. In term of richness estimators (abundance and evenness) the areas of EL, DI and TR districts seems to be the more richness areas in fruit tree species in Albania. GIS analysis proved that Albania is a very rich country in plant tree species diversity and in plant genetic resources. 19

20 Reserve selection method (a) Reserve selection results, Rebelo at al. (1992), ranked the minimum grid cells that should be given priority for conservation and modelled species richness maps. Ranking and mapping of species richness gave the first priority to the grid cell with the highest α diversity (Elbasan areas 13 species and Dibra areas 11 species). 20

21 Reserve selection method (b) Based on the modelled richness maps, EL and DI districts appears to be the areas with the highest potential fruit tree species diversity and with the most potential priority areas for in situ conservation of fruit tree species. 21

22 Reserve selection method (c): GIS analysis gave the subsequent priority to the additional areas that best complement the initial ones because they contain the highest number of new species, varieties or alleles that were not found in the previously selected grid cells (β diversity), Scheldeman at al. (2010). Confrontation of grid cells shows the highest number of new species (alleles) was found in BR district (3 new species), in DI district (3 other new species) and in FR district (2 new species). 22

23 Cluster analysis: This method, based on the distance or similarity measured, classified diversity and species richness, of each areas (grid cells) in different clusters. Cluster dendrogram show clearly the presence of similarity (70.588) between DI (joiner 1) & KO (joiner 2) areas; and similarity ( ) between FR and VL; and similarity ( ) between EL and TR areas; and so on. 23

24 Richness modelling: Bioclimatic factors that delimits the potential distribution of Fr. tree species. Study results show the great number of presence (collected) points were situated into: excellent suitable areas (from 20 to 30%), very high suitable areas (from 10 to 20%), high suitable areas (from 5 to 10%), (suitable grid cells are shown respectively in red, brown and yellow colour). There were also present points (collected points) situated in not suitable or low suitable areas for fruit tree species distribution. These points can be considered with reserve as new alleles adapted in those areas. The analysis needs more studies. ICE 2012, June,1-4, Tirana, ALB 24 B. GIXHARI (Agriculture University of Tirana)

25 Richness modelling: Combination of species occurrence data with climatic data delimitates the potential distribution of each species gave this map. Results demonstrate precipitation of driest month and precipitation seasonality seems to be the most limiting factors for the N-E part of ALB (grid cells in yellow and green colours); and mean monthly temperature range and maximum temperature of warmest month for central part of ALB (grid cells in red and green dark colours), and low precipitation of driest month and temperature seasonality for the S-W part of ALB (grid cells in yellow and red orange colours). This analysis needs more other studies. 25

26 CONCLUSION GIS analysis show the presence of variability between geographic areas related to number and kind of tree species collected and proved that Albania is a very rich country in plant tree species diversity. Based on the modelled richness maps, EL, DI and TR districts appears to be the areas with the highest potential fruit trees species diversity and with the most potential priority areas for in situ conservation of fruit tree species and GIS analysis gave the subsequent priority to the additional areas (BR, DI and FR) that contain the highest number of new species (or alleles) respectively 3, 3 and 2 new alleles. 26

27 CONCLUSION Cluster analysis identified the similarity between collecting areas (grid cells): DI and KO show similarity between them; also FR and VL; EL and TR areas; etc. Bio-climatic factors that most delimits the potential distribution of each tree species seems to be: precipitation of driest month and precipitation seasonality for the N-E part of ALB, and maximum temperature of warmest month for central ALB, and precipitation of driest month for S-W part of ALB. Application of GIS tools improved representativeness of genebank collections, and identified prioritized collecting sites and potential priority areas for in situ conservation. 27

28 28