Does habitat fragmentation reduce genetic ... - Wiley Online Library

Ecography 31: 751
756, 2008 doi: 10.1111/j.1600-0587.2008.05622.x # 2008 The Authors. Journal compilation # 2008 Ecography Subject Editor: Francisco Pugnaire. Accepted 18 June 2008

Does habitat fragmentation reduce genetic diversity and subpopulation connectivity? Gandour Mhemmed, Hessini Kamel and Abdelly Chedly G. Mhemmed ([email protected]), H. Kamel and A. Chedly, Laboratoire d’Adaptation des Plantes aux Stress Abiotiques, Centre de Biotechnologie, Technopole de Borj-Ce´dria, B.P. 901, 2050 Hammam-Lif, Tunisia.

The estimation of levels of genetic variation has received considerable attention because it is generally thought to be indicative of overall species vitality and the potential for evolutionary responses to environmental changes. Here, we use allozymes markers and two distinct collections of Cakile maritima, an annual species from sandy coastal habitats (2000 generation and 2005 generation collected from 9 populations in their natural habitats), to assess the magnitude of expected genetic change. We compared genetic diversity between generations (all populations combined), and then between populations at each generation. Based on 13 loci scored from the eight enzymes examined, a high genetic diversity was detected at both the population and generation level as compared to other herbaceous species. However, allelic richness reduction in the 2005 generation suggested restricted gene flow and a high risk of future genetic bottlenecks, if larger tracts of coastal areas disappear. Most loci showed deviation from Hardy-Weinberg equilibrium due to excess of heterozygotes in all populations suggesting that this species has an allogamic mode of reproduction. It appears most likely that this species has experienced a recent decrease in population size, and that genetic drift in small populations has resulted in a loss of alleles occurring at low frequency. Despite the deterioration process, maintenance of high genetic diversity suggests that there are some ecological factors determining population structure.

The estimation of levels of genetic variation has received considerable attention because it is generally thought to be indicative of overall species vitality and the potential for evolutionary responses to environmental changes (Templeton et al. 1990, Barrett and Kohn 1991, Ellstrand and Elam 1993, Frankel et al. 1995). Where fragmentation has occurred in the relatively recent past and where it continues, particularly in habitats subject to marked environmental instability, regional populations are unlikely to be in genetic equilibrium. Genetic assessment of fragmented populations may be used to address whether their subpopulations represent a common genetic pool, whether genetic differentiation of subpopulations is correlated with geographical distance or whether subpopulations are in equilibrium. Along the Tunisian coast, extensive clearing for urbanism, tourist development and agriculture has resulted in isolated fragments of what had previously been a continuous band of native vegetation on sand dunes. Such changes might include the erosion of genetic variability and the acceleration of genetic divergence between remnant populations by means of two mechanisms: reduced gene flow, and an increase in random genetic drift (Lamont et al. 1993, Olsen and Jain 1994, Young et al. 1996). These changes are also predicted to affect population viability in the short and long terms. In the short term, fragmented plant populations are

expected to suffer increased disease and pest susceptibility (Barrett and Kohn 1991), loss of incompatibility alleles, and fixation of deleterious alleles (Huenneke 1991). In the long term, loss of genetic variation is expected to reduce the ability of populations to respond to changing selection pressures (Young et al. 1996). May et al. (1994) estimated that impending extinction rates of animals and plants are at least four orders of magnitude greater than the background rate as judged by analyses of the fossil record. This is particularly attributable to fragile marine ecosystems that are greatly deteriorated because of habitat loss and fragmentation after the construction of huge hotels, swimming pools and, worse, ill-designed jetties (Sanjeev 2006). This environmental damage has had a range of negative direct and indirect impacts on flora including contributing to the decline of some rare and threatened plant species and communities (Liddle 1997, Buckley 2001). In this context, Endels et al. (2002) show that in small landscape elements, deterministic processes (such as habitat deterioration and abandonment of management regimes) are the first and most important step in population decline. Hence, it limits the possibilities for numerous species to realize their life cycle in their natural habitats. As a result, it might reduce the genetic diversity within populations (Wright 1969, Ellstrand and Elam 1993), which can have important 751

consequences for long-term survival (Newman and Pilson 1997, Booy et al. 2000). In this study, we compared genetic diversity of past collections (in 2000) with recent collections (in 2005) of Cakile maritima in order to see whether there has been a loss of genetic diversity in this species as its range and it population size have shrunk. Ideally we would like to quantify the degree to which historic levels of anthropogenic habitat fragmentation have changed allelic frequencies in remaining habitat isolates and what are the possible future changes in these frequencies. To address this issue, we sampled 9 populations of coastal species Cakile maritima in 2000 and again in 2005, and in four distinct environments of Tunisia (humid, sub-humid, semi arid and arid).

Material and methods Study species Cakile maritima (Brassicaceae) is an annual diploid species (2n 18). Its annual character is not strict, since some individuals may survive over two or three years. In such instances, the number of seeds produced may be almost 20 fold that produced by a single reproductive cycle (Thorne 1967, Barbour and Rodman 1970, Boyd 1988, 1993). On the Tunisian coast, seedlings germinate continuously through the autumn and winter, and some adults from the previous year persist beyond a single growing season, thus resulting in some overlap between generations. Except for occasional individuals, C. maritima is generally selfincompatible (Rodman 1974, Thrall et al. 2000). Pollen dispersion is likely to result from wind and insects (C. maritima is visited by several insects, unpubl.). An interesting feature for this species is that it produces dimorphic seeds, which have different dispersal capabilities (Payne and Maun 1981). Thus, it is highly likely that there could be strong genetic structure at very local spatial scales promoting consanguineous mating. This would also have implications for within-population resistance structure and rates of disease spread. Cakile maritima was probably one of the first species appeared after successive glaciations (Davy et al. 2006). It grows in sandy habitats along the North Atlantic Ocean, the Mediterranean Sea coasts, the Canary Islands and southwest Asia (Clausing et al. 2000). In these regions, it colonizes beaches and dunes that are frequently troubled by surf and wind. According to Pottier-Alapetite (1979), in Tunisia, this species is frequent along the coast from north to south.

However these populations have been severely fragmented by human activities and urbanization in the past decade. Sampling procedure and description of studied sites Nine population of Cakile maritima were selected for this study (Table 1). This sample encompasses the complete range of distribution of this species in Tunisia, which extend from 34831?N to 37815?N. In each population, siliculas were collected from 30 mother plants
10 m distant from each other. Seeds were kept moist in Petri dishes to germinate. Four-day-old seedlings were individually transplanted to plastic pots filled with sand. Plants were watered daily with freshwater. Distances between clones were kept to estimate the degree of fragmentation in each population. In fact, distance inferior to 100 m between clones designs area weakly deteriorated (class 1), distance between 100 and 300 m between clones was considered as a sign of area moderately deteriorated (class 2), distance between 300 and 700 m between clones indicates a deteriorated area (class 3) and distance superior to 700 m between clone were considered as a sign of highly deteriorated area (class 4). Electrophoresis procedure An electrophoresis survey was used to estimate genetic variability within and among C. maritima populations. Approximately 200 mg of leaf tissue was collected from each plant (one month old), ground under liquid nitrogen and mixed with 100 ml of extraction buffer (PVP-potassium phosphate grinding buffer pH 7), as described by Thrall et al. (2000) and centrifuged at 19 000 g for 20 min. The extracts were stored in an ultra-cold freezer (708C) until analysis. Horizontal starch-gel electrophoresis was performed for seven enzyme systems revealing a minimum of 13 isozyme loci of eight enzymes: peroxidase (PRX; EC 1.11.1.7), isocitrate dehydrogenase (IDH, EC 1.1.1.42), glutamate oxaloacetate transaminase (GOT, EC 2.6.1.1), shikimate dehydrogenase (SKD, EC 1.1.1.25), leucine aminopeptidase (LAP, EC 3.4.11.1) 6-phosphogluconate dehydrogenase (6-PGD, EC 1.1.1.44) and malate dehydrogenase (MDH, EC 1.1.1.37). The compositions of gel and electrode buffers were described by Soltis et al. (1983) and the methods used to stain allozyme bands were described by Michaud et al. (1992) for PRX, by Cardy et al. (1980) for IDH, GOT, LAP, SKD, 6-PGD and MDH. For acid phosphatase (ACPH, EC 3.1.3.2) vertical

Table 1. Geographical, climatic characteristics and degree of deterioration (1: weakly deteriorated, 2: moderately deteriorated, 3: deteriorated, 4: highly deteriorated) for the sampled populations of Cakile maritima. Alpha-numeric code CM1Biz CM2BKH CM3CHF CM4ENF CM5HAM CM6JRB CM7RAD CM8SOS CM9TAB

752

Population locality

Climate region

Latitude

Longitude

Degree of deterioration

Bizerte Bkhalta Chaffar Enfidha Hammamet Jerba Raoued Sousse Tabarka

Sub-humid Semi-arid Arid Semi-arid Sub-humid Arid Sub-humid Semi-arid Humid

37815?N 35837?N 34831?N 36807?N 36822?N 33850?N 36856?N 35853?N 36857?N

9854?E 11802?E 10834?E 10828?E 10832?E 118E 10815?E 10836?E 8845?E

2 1 1 1 4 2 2 4 3

zoned polyacrylamid gels were prepared following Laemmli (1970) and stained according to Selander et al. (1971). Genetic analysis Loci were numbered consecutively, with the most anodally migrating locus designed as locus 1. Alleles at each locus were labelled numerically according to their distance migration, beginning from the most cathodal form in both cases. Interpretation of banding patterns was done on the basis of the quaternary structure of isozyme and number of loci usually expressed in diploid plants, according to standard principles. To calculate the levels of genetic diversity, the following statistics were computed: the percentage of polymorphic loci when the most common allele had a frequency of B0.95 (P); the mean number of alleles per locus (A); the observed heterozygosity (Ho); the expected panmictic heterozygosity (He) and the comparison between grouped populations 2000 and populations 2005. Calculations were performed with FSTAT (ver. 2.9.3.2. Goudet 2002), Biosysis-1 and Genetix 4.02. The mean fixation index (F) for all polymorphic loci in each population was also computed in order to compare genotype proportions with those expected under HardyWeinberg equilibrium. A chi-square test (x2) was used to evaluate deviation of F from zero, with Levene’s (1949) correction for small sample size. The partitioning of genetic diversity within and between populations was analysed using Nei’s (1973) gene diversity statistics: total genetic diversity (Fit), genetic diversity within populations (Fis) and genetic diversity between populations (Fst) were calculated for all polymorphic loci. The 95% confidence intervals for Fis and Fst (Bootstrapped over loci) and standard error (Jack-knifed over loci) were calculated with FSTAT. Standard error of allelic richness He and Ho, was calculated from the nine population values in each group. Gene flow (Nm) was determined using Wright’s (1951) equation Nm 1Fst/4Fst, where N is the population size and m the average rate of immigration. We estimated effective population size using the method by Xu and Fu (2004) as u 4Nem where m is the mutation rate. Thus, current effective population size is given by the scaled estimator u rather than actual number of individuals. u values were estimated for each locus and the value presented is the average weighted for differences in sample size. Spearman’s

correlations between loss of allelic richness and the state of origin sites were calculated following appropriate procedures (Snedecor and Cochran 1967). It is worth noting that Spearman’s rank correlation is the best-known procedure for studying the degree of relationship between 2 variables when there is sub-normality in both pairs of variables.

Results Comparison of allozyme diversity between the 2000 and 2005 generation A total of 13 loci were scored: IDH (1); PRX (5); ACPH (1); GOT (1); MDH (1); PGD (2); SKD (1); LAP (1). Additional zones of activity were present for IDH, ACPH, and LAP but they were not included in the analyses because lack of resolution and staining intensity precluded an unambiguous interpretation. These loci gave an average of 2.22 and 2.08 alleles per locus in generation 2000 and generation 2005 respectively (Table 2). Thus, allelic richness was 14% lower in 2005 generation p 0.0034, 2500 permutations). Loss of allelic richness was highly correlated with degree of habitat fragmentation (r 0.86, p0.0015) (Fig. 1) and moderately correlated with current effective population size (r 0.57, p 0.023) (Fig. 2). Gene diversity was lower in 2005 generation (He 0.29 vs He 0.33) (p 0.021) (Table 5). Total genetic diversity (F) in generation 2000 was 0.526 (90.129) as compared to 0.417 (90.176) in generation 2005 (Table 4). The proportion of polymorphic loci was 80.32 in generation 2000 and 73.47 in generation 2005 (Table 3). A total of 3 unique alleles were detected in generation 2000 and none was detected in generation 2005 (x2 15.79, DF 1, p0.0002, x2 test). In fact, generation 2005 had a subset of the alleles present in generation 2000 and consequently, we assisted to a decrease of 3 alleles in five years. A total of 46 alleles were found at the 13 polymorphic loci studied in generation 2005 versus 49 alleles in generation 2000. Missed alleles in generation 2005 were ACPH196, GOT94 and SKD106. Observed and expected mean heterozygosities ranged from 0.152 (0.076) and 0.193 (0.061) to 0.311 (0.089) and 0.385 (0.067) in generation 2005 and from 0.157 (0.043) and 0.200 (0.063) to 0.360 (0.079) and 0.432 (0.063) in generation 2000. Overall, observed and expected

Table 2. Allelic richness and gene diversity per locus for each generation (2000 and 2005). Locus PRX1 PRX2 PRX3 PRX4 PRX5 IDH2 ACPH1 MDH SKD GOT LAP 6PGDH1 6PGDH2

Allelic richness 2000

Allelic richness 2005

Gene diversity (2000)

Gene diversity (2005)

1.990 2.560 3.770 3.100 2.000 2.520 1.810 1.310 2.969 4.526 2.496 2.652 3.920

1.863 2.065 3.466 2.797 2.000 2.168 1.066 1.660 1.881 3.429 2.168 2.239 3.362

0.254 0.146 0.603 0.356 0.470 0.512 0.068 0.120 0.278 0.570 0.492 0.183 0.353

0.170 0.108 0.541 0.316 0.456 0.500 0.0073 0.073 0.140 0.492 0.489 0.154 0.349

753

y = 0.0098x - 0.0064 R2 = 0.7526

0

1

2

3

loss of allelic richness

Loss of allelic richness

0.045 0.040 0.035 0.030 0.025 0.020 0.015 0.010 0.005 0.000

4

0.045 0.040 0.035 0.030 0.025 0.020 0.015 0.010 0.005 0.000

5

y = -4E-05x + 0.0424 R2 = 0.3354

0

200

Degree of disturbance

400

600

800

1000

1200

Current effective population size

Figure 1. Loss of allelic richness in relation to degree of habitat deterioration.

Figure 2. Loss of allelic richness in relation to current effective population size.

heterozygosities were lower in generation 2005, although the statistical significance of the difference was marginal (Ho 0.2 in generation 2005; 0.209 in generation 2000 and He 0.291 in generation 2005; 0.33 in generation 2000; p0.044 and 0.049 respectively). Particularly the largest effect was shown in Tabarka population (0.439 vs 0.311) followed by Hammamet and Bkhalta population (Table 3). Levels of inbreeding in generation 2000 were one and half times as high as levels of inbreeding in generation 2005 (p 0.0031, 2500 permutation). The 95% confidence interval (CI) indicates that inbreeding in both generations is significantly raised above zero (Fis 0.311, 95% CI 0.016
0.66 and Fis 0.455, 95% CI 0.207
0.720) confirming that significant inbreeding within populations occurs in these generations. Genetic differentiation (Fst) between populations within each generation was high for 2005 generation when compared with population from 2000 generation (p  0.0019, 1000 permutation: Fst 0.155, 95% CI 0.086
0.236; Fst 0.127, 95% CI 0.074
0.194) (Table 5). Pairwise population differentiation test carried out by using the log-likelihood statistic showed that all possible populations pairs within each generation were significantly differentiated (a 0.05). The highest values for Fst among generation 2005, 0.467, and the highest among 2000, 0.353, occurred at the PRX-2 and PRX-4 loci respectively. The lowest values for both generation 2005 and 2000 occurred at ACPH-1 and IDH-2 (0.004 and 0.023, respectively). While analyzing the relationship between (1 Fst)/4Fst and geographic distance for generation 2005, a slightly positive but non-significant value was observed (correlation: 0.004; p0.98). For generation 2000, this relationship was slightly positive, but also non-significant (correlation: 0.174; p0.36).

Discussion Our results show that genetic diversity decreased over time, and that the degree of fragmentation as well as the size of the founding population is an important factor in the overall level of genetic variability over time. In generation 2000 considered as from continuous landscape the genetic differentiation between populations is low, indicating that at spatial scale of our study, the continuous area is subject to panmictic breeding. Allelic richness is more sensitive to population fragmentation than is gene diversity because of the preferential elimination of rare alleles that contribute little to heterozigosity (Nei et al. 1975, Cornuet and Luikart 1996). Because gene diversity may take many generations to reach equilibrium after fragmentation and reduction in population size (Varvio et al. 1986, Cornuet and Luikart 1996), allelic richness may more accurately reflect current levels of genetic diversity within unstable population (Lowe et al. 2004). In our case, in addition to evidence of spatial structure within Tunisian populations, we found evidence of inter-annual variation in genetic diversity among replicate samples from the same regions. In fact, we found a reduction in allelic richness (31.7 vs 30.2) particularly for three loci (ACPH, GOT and SKD), and a reduction in expected heterozygosity (0.3 vs 0.2). Thus, we believe there are two likely sources for this apparent temporal shift. First, the anthropogenic activities are the main threats to Cakile maritima, derived mainly from destruction of beaches a consequence of massive urbanization and hotel construction for tourism development in the last century. Second, the physical degradation and/or removal of coastal sand dune habitats have led to the fragmentation or even disappearance of former populations. Nei et al. (1975) have shown that the reduction in average heterozygosity per locus

Table 3. Expected heterozygosity (He), percentage of loci polymorphic (P) and Fis (correlations between uniting gametes within subpopulations) per population and per generation, effective population size (Ne). Population

He 2000

He 2005

P 2000

P 2005

Fis 2000

Fis 2005

Ne 2000

Ne 2005

Tabarka Raoued Hammamet Bkhalta Chaffar Sousse Enfidha Bizerte Jerba

0.439 0.287 0.28 0.395 0.327 0.252 0.346 0.411 0.297

0.311 0.182 0.194 0.204 0.194 0.152 0.197 0.196 0.174

92.3 76.5 76.9 85.5 78.1 61.5 69.7 92.3 85.2

84.6 53.8 69.2 84.6 76.9 53.8 69.2 84.6 84.6

0.346 0.433 0.397 0.541 0.464 0.409 0.498 0.595 0.397

0.194 0.287 0.207 0.419 0.416 0.213 0.315 0.328 0.396

865 1082.5 992.5 1352.5 1160 1022.5 1245 1484.5 992.5

485 717.5 517.5 1047.5 1040 532.5 787.5 820 990

754

Table 4. Weir and Cockerham (1984) statistics on genetic structure across the nine study populations of Cakile maritima, Fit (total genetic diversity), Fis (genetic diversity within populations), and Fst (genetic diversity between populations) calculated independently for generation 2000 and generation 2005. The mean value was calculated across all loci. Locus

PRX-1 PRX-2 PRX-3 PRX-4 PRX-5 IDH-2 ACPH-1 MDH SKD GOT LAP 6PGD-1 6PGD-2 Mean SE

Fit

Fst

Gen 2005

Gen 2000

Gen 2005

Gen 2000

Gen 2005

Gen 2000

0.405 0.909 0.926 0.67 0.194 0.292 0.004 0.634 0.98 0.594 0.508 0.658 0.771 0.417 0.176

0.605 0.826 0.889 0.722 0.29 0.069 0.751 0.728 0.828 0.651 0.235 0.723 0.811 0.526 0.129

0.09 0.467 0.149 0.398 0.093 0.021 0.004 0.132 0.074 0.214 0.031 0.215 0.147 0.155 0.042

0.118 0.212 0.08 0.353 0.053 0.023 0.114 0.209 0.083 0.153 0.04 0.159 0.159 0.127 0.034

0.349 0.826 0.913 0.458 0.109 0.319 0 0.552 0.978 0.488 0.557 0.588 0.735 0.311 0.191

0.603 0.767 0.879 0.578 0.251 0.094 0.722 0.658 0.812 0.589 0.286 0.676 0.775 0.455 0.14

depends not only on the size of the population bottleneck, but also on the subsequent rate of population growth. If population growth is rapid, reduction in average heterozygosity is small, even given a small number of founders. Regardless of growth rate, however, populations undergoing bottlenecks tend to lose low frequency alleles, reducing polymorphism, and the number of alleles per locus (Godt and Hamrick 1991). While rare alleles will be the first to be lost, extended bottlenecks, acting over many generations, will cause loss of more common alleles, leading to a severe depletion of genetic diversity (Lande 1988). This is the first time that a significant short time pattern of decreasing allelic richness is documented for an herbaceous species from Brassicacea family. This consistent short time pattern could be invoked as an indicator of overexploitation of studied area. This finding coincides with those predicted by Templeton et al. (1990) and Montgomery et al. (2000). It is of interest to note that the gene flow observed in the generation 2000 is significantly higher than in the generation 2005 (1.71 vs 1.36). In other words, a higher gene flow in continuous habitat than in relatively fragmented habitats. Working with other species (Rana temporaria), Johansson et al. (2005) found a high degree of gene flow in a continuous landscape compared to a fragmented landscape. Jacquemyn et al. (2003) working with Primula vulgaris, have found that populations along arable fields showed decreased recruitment rates compared to populations Table 5. Population genetic structure and genetic diversity compared between the two generations. Parameter Inbreeding coefficient, Fis Genetic differentiation, Fst Number of rare allele absent Allelic richness Observed heterozygosity, Ho Expected heterozygosity

Fis

Generation 2000

Generation 2005

p

0.455 (0.191)

0.311 (0.14)

0.0031

0.127 (0.034)

0.155 (0.042)

0.0019

0

3

0.0002

2.22 (0.26) 0.210

2.08 (0.244) 0.200

0.0034 0.044

0.305

0.293

0.049

located in forests or grassland, especially in the absence of disturbance. Under this scenario, the observed loss of genetic variation in geographically isolated populations would be due to the local extinction and the resulting loss of gene flow from neighbouring populations. However, in some cases we assessed to a conservation of high gene flow measured indirectly (Nm) between populations. Thus, we suggest that there is a putative correction by a sea seed transport. Given reduction in gene flow, populations are expected to diverge genetically due to drift, the random loss of alleles due to small population size (Wright 1951). Comparing the distances between populations in 2000 and populations in 2005, an increase of 3.2% was noted. Results provide evidence that short-term interruption was able to increase the genetic divergence between natural populations of Cakile maritima. As a consequence, population tended to be more clustered and subgroups within meta-population appeared. Conclusion In conclusion, our study provides evidence that Cakile maritima still harbours a great wealth of genetic diversity, but the current pattern of fragmentation may lead to longterm loss of genetic diversity. Future studies may want to address the interaction between the degree of isolation and fragment size to understand the pattern of landscape mosaic that can sustain genetic diverse populations.

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