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Morphological, Molecular and Macro-Biochemical Diversity of Moroccan Pistacia lentiscus L.: A Three-Level Synthesis across Eleven Populations

This study synthesizes morphological, molecular, and biochemical analyses of eleven Moroccan *Pistacia lentiscus* populations to reveal high, largely independent diversity across all levels driven by biological traits rather than geography, thereby advocating for the conservation of a broad network of stands, particularly in arid regions.

Original authors: Wassila Bouta¹, Taoufik El Rasafi, Said Bouda¹, Abdelmajid Haddioui¹

Published 2026-07-13

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Wassila Bouta¹, Taoufik El Rasafi, Said Bouda¹, Abdelmajid Haddioui¹

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine the Mastic tree (Pistacia lentiscus) as a chameleon of the Moroccan landscape. For a long time, scientists thought they knew how these trees were organized: that trees living close together in the mountains looked and acted alike, while those far away in the hot, dry lowlands were totally different. They assumed geography was the boss, writing the script for how these plants grew, what their DNA looked like, and what chemicals were inside their leaves.

But a new study, which acts like a detective bringing together three different sets of clues, has flipped that script. The researchers took a deep dive into eleven different wild populations of these trees, stretching from the cool, wet Middle Atlas mountains down to the scorching, arid Souss lowlands. They didn't just look at one thing; they checked the trees' appearance (morphology), their genetic code (molecular markers), and the chemical soup inside their leaves (macro-biochemistry).

Here is the twist: The trees are a chaotic, beautiful mess that refuses to follow the map.

The Three Layers of Clues

1. The Look-At-You Layer (Morphology)
First, the team measured 24 different physical traits, like the length of a leaf, the width of a fruit, and the color of the almond. They found huge differences between trees. But here's the kicker: the trees didn't group up by where they lived. A tree from the high mountains didn't necessarily look like its neighbor; it might look more like a tree hundreds of kilometers away.

The Verdict: The paper proves that the trees' physical shapes are highly variable. However, the study shows that this variation does follow the environment. When the climate gets drier or colder, the leaves and fruits change shape. It's like a student who changes their outfit depending on the weather outside—plastic and responsive.

2. The Secret Code Layer (Molecular/Genetics)
Next, they cracked open the trees' DNA using special markers called ISSR. They found that the genetic diversity was huge. About 91% of the genetic spots they checked were different from one another.

The Big Surprise: The paper explicitly rules out the idea that geography or climate organizes this genetic code. When they tried to group the trees by mountain range or rainfall, those groups explained less than 4% of the genetic differences. In fact, the genetic code is completely disconnected from the map. A tree in the High Atlas might be genetically closer to a tree in the Souss desert than to its neighbor just a few miles away.
The Cause: The authors suggest this is because the trees are "dioecious" (having separate male and female trees) and rely on birds to carry their seeds. Birds fly far and wide, dropping seeds in random spots, which scrambles the genetic map. It's like a game of musical chairs where the birds are the ones moving the chairs, not the wind or the terrain.

3. The Chemical Kitchen Layer (Biochemistry)
Finally, they analyzed the leaves' "menu"—measuring proteins, fats, sugars, and minerals. They found significant differences in the chemical makeup of the leaves between populations.

The Verdict: Just like the DNA, the chemical recipe does not follow the geography or the climate. The study measured that neither the distance between trees nor the difference in rainfall explained the chemical differences. The trees are chemically unique, but their uniqueness is a mystery to the map.

The "Three-Level" Mystery Solved

The most exciting part of this research is how these three layers talk to each other. The authors ran statistical tests (called Mantel tests) to see if the physical look, the DNA, and the chemicals were all telling the same story.

They weren't.
The paper shows that these three levels are statistically independent.

Knowing a tree's DNA does not tell you what its leaves look like.
Knowing the leaf chemicals does not tell you the DNA.
Knowing the physical shape does not tell you the chemicals.

It's as if you have three different radio stations playing at the same time, but they are all broadcasting on completely different frequencies. The only thing that connects the physical look of the tree to the outside world is the environment itself (the weather), which changes the shape of the leaves. But the DNA and the chemicals? They are doing their own thing, completely decoupled from where the tree is standing.

What This Means for the Future

The paper argues that we cannot save these trees by just protecting a few big, "perfect" forests. Because the genetic and chemical diversity is scattered randomly across the landscape, we need to protect a network of many different populations.

There is one specific spot that gets a special shout-out: the isolated population in the Souss lowlands. This group is sitting on the edge of the desert, facing a drying climate. The study highlights that this specific group is genetically and chemically distinct, making it a unique piece of the puzzle that we must not lose.

In short, the Moroccan Mastic tree is a master of disguise and a wanderer of the genome. It proves that nature's diversity is often a chaotic mosaic, not a neat, orderly map. To save it, we have to protect the whole messy, beautiful puzzle, not just the pieces that look like they fit together.

Technical Summary: Morphological, Molecular, and Macro-Biochemical Diversity of Moroccan Pistacia lentiscus L.

Problem Statement
Pistacia lentiscus L. (mastic tree) is a keystone dioecious shrub in the Mediterranean Basin, valued for its ecological resilience and economic products. While Moroccan populations are widespread, their diversity had previously been characterized only in fragmented, single-level studies. There was a lack of integrated evidence determining whether morphological, molecular, and biochemical variations in Moroccan populations are congruent, how they relate to geographic and bioclimatic gradients, and whether population structure follows a simple isolation-by-distance model.

Methodology
This study synthesizes three previously published datasets (Bouta et al. 2020, 2022, 2024) derived from the same eleven natural populations of P. lentiscus sampled across a bioclimatic gradient in central and southwestern Morocco (Middle Atlas, High Atlas, and the arid Souss lowlands). The study did not generate new experimental data but performed new concordance and spatial analyses on existing population means and distance matrices.

The three levels of analysis were:

Morphological: Assessment of 24 morpho-pomological traits (quantitative and qualitative) across 240 trees (10 per population, 20 fruits per tree). Analysis included ANOVA, Pearson correlations, Principal Component Analysis (PCA), and hierarchical clustering.
Molecular: Genotyping of 55 individuals (5 per population) using 13 Inter-Simple Sequence Repeat (ISSR) primers. Metrics included Polymorphism Information Content (PIC), Resolving Power (Rp), gene diversity ( $H_t$ , $H_s$ ), fixation index ( $F_{ST}$ ), and gene flow ( $N_m$ ). Population structure was inferred using AMOVA and Bayesian clustering (STRUCTURE).
Macro-Biochemical: Determination of leaf proximate composition (dry matter, ash, crude protein, fat, fiber, sugars, minerals, and energy value) for all eleven populations. Analysis utilized ANOVA, PCA, and Ward hierarchical clustering.

Synthesis and Statistical Testing
To test the hypothesis that diversity is congruent and weakly related to geography, the authors performed:

Mantel and Partial Mantel Tests: To correlate morphological, genetic, and biochemical distance matrices against geographic and bioclimatic (altitude, rainfall, temperature) distance matrices.
Multiple Regression on Distance Matrices (MRM): To quantify the predictive power of geography and environment on each level of differentiation.
Procrustes Analysis (PROTEST): To test for congruence among the ordinations of the three data types.

Key Results

High Diversity at All Levels:
- Morphology: Significant variation was found among and within populations. PCA and clustering resolved four distinct groups that did not align with geographic origin (e.g., the Middle Atlas population of Azilal grouped with the distant coastal Souss population).
- Molecular: ISSR markers revealed high genetic diversity (91% polymorphic loci, $H_t = 0.31$ ). However, differentiation was strong ( $F_{ST} = 0.42$ ) with low gene flow ( $N_m \approx 0.95$ ). AMOVA showed that geographic and bioclimatic groupings explained less than 4% of molecular variance. STRUCTURE analysis identified five gene pools that ignored geographic boundaries.
- Biochemistry: Significant differences existed in minerals, nitrogenous matter, protein, and energy value. Clustering resolved four groups that, like morphology, cut across geographic origins.
Decoupling of Levels and Geography:
- Independence: The three levels of diversity were statistically independent of one another (Mantel $r$ values were non-significant between morphological-genetic, biochemical-genetic, and morphological-biochemical matrices).
- Geographic/Bioclimatic Correlation:
  - Genetic and Biochemical: Neither genetic nor biochemical differentiation correlated significantly with geographic or bioclimatic distance.
  - Morphological: Morphological distance correlated significantly with both geographic ( $r=0.43$ ) and bioclimatic ( $r=0.51$ ) distances. However, partial Mantel tests revealed this was an isolation-by-environment pattern (significant correlation with environment after controlling for geography) rather than simple isolation-by-distance. This suggests phenotypic plasticity in response to the bioclimatic gradient.
Drivers of Structure:
The observed patterns are attributed to the species' biology: strict dioecy enforces outcrossing (maintaining high within-population diversity), short-distance wind pollination leads to drift between neighboring stands, and bird-mediated seed dispersal creates unpredictable long-distance connections that scramble geographic gradients.

Significance and Claims
The paper claims to provide the first integrated, multi-level synthesis of P. lentiscus diversity in Morocco. Its primary contribution is demonstrating that while the species is highly diverse, this diversity is organized as a mosaic independent of geographic or bioclimatic origin for neutral genetic and biochemical markers.

The authors argue that conservation strategies should prioritize protecting a network of differentiated populations rather than focusing on a few large reserves. Specifically, they highlight the isolated Souss population (Imiouddare) as a priority for conservation due to its distinct genetic and biochemical profile and its location on an arid margin increasingly exposed to drying climates. The study concludes that morphology tracks the environment via plasticity, whereas neutral genetic and biochemical markers reflect a history of fragmentation and drift, necessitating a multi-faceted approach to understand the species' true diversity.

The Three Layers of Clues

The "Three-Level" Mystery Solved

What This Means for the Future

Technical Summary: Morphological, Molecular, and Macro-Biochemical Diversity of Moroccan Pistacia lentiscus L.

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