Phylogenetic Diversity in Forests: Insights into Evolutionary Patterns and Conservation Strategies

Abstract

Forests harbor most of the world’s terrestrial biodiversity; however, traditional conservation frameworks prioritize species richness over evolutionary diversity. Phylogenetic diversity (PD) reflects the complete evolutionary history contained within a community, offering a more comprehensive understanding of biodiversity. This review examines the theoretical foundations of PD, highlights methodological advancements in its assessment, and discusses its conservation applications in forest ecosystems. We discuss key metrics, including Faith’s PD, mean pairwise distance (MPD), mean nearest taxon distance (MNTD), and indices, including the net relatedness index (NRI) and nearest taxon index (NTI), as well as analytical tools (Picante, Phylocom, Biodiverse) and frameworks like the categorical analysis of neo- and paleo-endemism (CANAPE) and the evolutionarily distinct and globally endangered (EDGE) index, evaluating their effectiveness in identifying evolutionarily significant conservation areas. We examine global and regional forest PD patterns, including elevational and latitudinal gradients, using case studies from the Pan-Himalayan region, Tibetan Plateau, and northern Pakistan, along with the environmental and anthropogenic drivers, e.g., soil pH, precipitation, land-use change, and invasive species, and historical biogeographic forces that shape lineage diversification. We emphasize the need for data standardization, regional research expansion, and the inclusion of PD in national biodiversity strategies and global policy frameworks. This review highlights the transformative potential of shifting from species-centric to evolutionarily informed conservation, and provides a critical framework for enhancing the long-term resilience and adaptive capacity of forest ecosystems.

1. Introduction

Biodiversity across the globe is under unprecedented threat due to anthropogenic pressures, including climate change, habitat loss, and ecosystem degradation [1,2]. Forest ecosystems, which support over 80% of terrestrial biodiversity, are particularly vulnerable [3,4]. Forest degradation and deforestation endanger countless plant and animal species and disrupt essential ecological functions, such as carbon storage, water regulation, and nutrient cycling [5,6]. Conventional indicators that are used to monitor and manage forest biodiversity, such as species richness and abundance, have been instrumental in informing conservation efforts. However, these traditional measures often fail to capture the deeper evolutionary context and do not adequately reflect the functional and adaptive potential of ecosystems [7,8,9].

In recent years, there has been growing recognition that biodiversity is more than species abundance [10,11,12]. The evolutionary relationships among species in a community, including their divergence times and degrees of relatedness, can provide critical insights into an ecosystem’s resilience and function. Understanding these relationships reveals how closely related species often share functional traits and ecological roles, which influence community stability and ecosystem processes [13]. This has led to the development and application of Faith phylogenetic diversity (PD) as a complementary framework for biodiversity assessment [14,15]. Phylogenetic diversity measures the amount of evolutionary history represented within a community or region, offering a more comprehensive view of biodiversity that incorporates lineage divergence, evolutionary distinctiveness, and adaptive breadth [16]. Unlike species richness, which treats all species equally, PD allows conservationists to prioritize species that represent unique lineages and habitats that support a greater span of evolutionary history, and thereby serves as a powerful tool for safeguarding biodiversity over the long term [15,17].

Despite its growing importance, the application of PD in forest ecology and conservation is still evolving. Numerous metrics, including PD, mean pairwise distance (MPD), mean nearest taxon distance (MNTD), and indices such as the net relatedness index (NRI) and the nearest taxon index (NTI), have been developed to quantify PD [18,19]. For instance, the framework developed by Roy et al. [20] emphasizes the importance of standardizing biodiversity measures and provides a foundation for comparing ecosystem diversity across varied landscapes. These tools enable ecologists to assess patterns of phylogenetic clustering or overdispersion within communities, providing insights into processes like environmental filtering or competitive exclusion. Moreover, spatial metrics that incorporate PD, such as phylogenetic endemism (PE) and relative PD (RPD), help identify evolutionary hotspots and refugia that may otherwise be overlooked in conservation assessments [21,22]. Advanced software tools like Picante, Phylocom, and Biodiverse, often in combination with geospatial data, facilitate such analyses and have made PD studies more accessible to researchers worldwide [23].

Forest ecosystems offer unique opportunities for the application of phylogenetic frameworks, as well as unique challenges [24,25]. The patterns of phylogenetic diversity vary considerably across forest types and environmental gradients. Tropical forests, for instance, tend to harbor a vast array of ancient and divergent lineages, which results in high phylogenetic diversity (PD) and phylogenetic endemism (PE), reflecting their role as evolutionary museums and cradles [26]. In contrast, temperate and boreal forests may exhibit lower overall PDs; however, they frequently reveal deep evolutionary clustering due to historical constraints or strong environmental filtering [27]. Elevational and latitudinal gradients also influence the phylogenetic structure of forests, with zones of overdispersion often being found at middle elevations or middle latitudes. Furthermore, natural and anthropogenic drivers, such as climatic factors, soil properties, logging, and land-use change, play significant roles in influencing phylogenetic patterns [28,29,30]. A comprehensive understanding of these dynamics is essential to creating conservation strategies that not only preserve species richness but also maintain the evolutionary potential of forest ecosystems [27,31].

Recognizing the conservation value of evolutionary distinctiveness, several global initiatives have begun to incorporate PD into their planning and policy frameworks. Metrics such as EDGE and tools such as CANAPE are used to highlight regions with unique evolutionary histories that merit urgent protection [32,33,34]. However, the practical integration of PD into forest management remains limited, often due to data deficiencies, a lack of standardized methodologies, and insufficient awareness among practitioners [35,36,37]. At the same time, emerging trends in phylogenomics, trait–phylogeny integration, and remote sensing offer promising avenues for enhancing the precision and applicability of PD assessments [38,39,40]. These technological and analytical advancements can bridge the gap between theoretical insight and practical conservation and offer particularly strong potential in regions where traditional biodiversity surveys are logistically challenging.

Given this background, this review aims to synthesize the current knowledge on the application of PD in forest ecosystems, providing a comprehensive overview of its theoretical foundations, measurement tools, observed patterns, environmental and anthropogenic drivers, and practical applications in conservation. By critically evaluating recent methodological advances and identifying key research gaps, this review seeks to support the integration of phylogenetic metrics into forest biodiversity assessments and management strategies. Ultimately, we aim to promote an evolutionary perspective in the field of forest conservation and to encourage policies and practices that safeguard both the current species richness and the deep evolutionary history of forest ecosystems.

Literature Search and Methodology

This review article synthesizes the current knowledge and recent advances in phylogenetic diversity research within forest ecosystems. No original experimental work was conducted. Instead, this review is based on a systematic and comprehensive analysis of peer-reviewed journal articles, review papers, and authoritative sources that are relevant to phylogenetic diversity metrics, ecological drivers, conservation applications, and methodological advances that are relevant to PD. The relevant literature was identified through searches of major academic databases including Web of Science, Google Scholar, ScienceDirect, MDPI, Wiley, and Springer. The searches utilized targeted keywords and phrases such as “phylogenetic diversity,” “forest ecosystems,” “phylogenetic endemism,” “evolutionary distinctiveness,” “biodiversity conservation,” and “community phylogenetics.” Boolean operators (AND, OR) were used to refine the searches and capture a broad scope of pertinent studies. The timeframe for the included publications primarily ranged from 2000 to 2025, which was chosen to incorporate foundational studies as well as the latest developments. Additionally, one seminal article from 1992 was included to provide historical context and ensure that foundational concepts for phylogenetic diversity were represented. The inclusion criteria mandated that the included studies focus on forest ecosystems and address phylogenetic diversity either empirically or methodologically. The included articles were limited to peer-reviewed works published in English. Grey literature, literature on non-forest ecosystems, conference abstracts, and unpublished data were excluded to maintain academic rigor. An initial set of approximately 287 records was retrieved, and these were screened for relevance and quality by their titles and abstracts. Following this, 186 articles were reviewed in full text, with 157 meeting all criteria for inclusion in the final review. This approach ensured a wide yet focused coverage of the topic.

2. Concepts and Metrics of Phylogenetic Diversity

The concept of biodiversity has evolved beyond merely cataloging species to encompass the relationships and functions that sustain ecosystems [41]. In this context, PD has emerged as a critical tool for capturing the evolutionary dimensions of biodiversity [42]. Building upon traditional species counts, the PD of a community emphasizes the evolutionary distinctiveness of community members by quantifying the divergence among their lineages. This allows ecologists to capture not just the number of species in an ecosystem, but also the depth of evolutionary history that they represent. By identifying areas and lineages of high evolutionary significance, the PD can facilitate more robust conservation planning [43,44]. The application of PD is particularly relevant in forest ecosystems, where diverse lineages have often coexisted over long evolutionary timescales and been shaped by complex environmental filters [45]. This section outlines the core concepts, quantitative metrics, and analytical tools that form the foundation of phylogenetic diversity research.

2.1. Core Concepts

Phylogenetic diversity refers to the total branch length of a phylogenetic tree that spans all species within a given community or sample [46]. This measure was first formalized by Faith (1992) and has since become foundational in ecological and conservation studies [47]. The value of PD lies in its ability to quantify the amount of evolutionary history within a community [48]. For instance, a forest plot containing species from ancient, distantly related lineages, such as gymnosperms and angiosperms, would exhibit a higher PD than a plot composed entirely of recently diverged species, even if both plots contained the same number of species. This allows PD to serve as a proxy for functional and genetic diversity, particularly in systems where comprehensive trait data may be lacking.

Phylogenetic endemism, a measure closely linked to PD, captures the extent to which unique evolutionary lineages are geographically restricted [49]. It is particularly useful for identifying regions that harbor ancient or relictual lineages, which are often considered evolutionary refugia. Such high-PE areas often have significant conservation value, as the loss of geographically restricted lineages would represent a disproportionate erosion of evolutionary history. Relative metrics, such as RPD and relative PE (RPE), are used to assess deviations from expected values under null models, and enable standardized comparisons across regions or taxa [50]. These ratio-based measures help differentiate between areas that are characterized by long branches (representing ancient lineages) and those that are characterized by short branches (indicating recent radiations), and thus help to refine prioritization in conservation decision-making [42].

A critical distinction must be made between phylogenetic, taxonomic, and functional diversity. While taxonomic diversity counts species and functional diversity measures trait variance, phylogenetic diversity integrates lineage relationships, encompassing both deep and recent divergences. Although these dimensions can be congruent, they often diverge, which underscores the importance of using PD as a complementary axis in biodiversity assessment. Forest ecosystems may exhibit high species richness but low PD if they are dominated by a few speciose clades or, conversely, they may exhibit low species richness but high PD if they are composed of relatively few but distantly related taxa [51,52]. Understanding these nuances is essential for developing conservation strategies that maximize evolutionary potential and enhance ecological resilience.

2.2. Quantitative Metrics and Formulas

Quantifying phylogenetic diversity requires robust metrics that capture both evolutionary distances and the community structure. A range of metrics, such as PD, MPD, and the NTI, have been developed to assess evolutionary patterns in forest communities [53]. It is important to note that each of these metrics comes with specific assumptions and sensitivities. For example, PD is sensitive to species richness and tree topology, while the MPD and MNTD are impacted by sampling efforts and the presence of incomplete phylogenies. Detailed summaries of these metrics, including their mathematical formulations, ecological interpretations, strengths, and limitations, are provided in Table 1. PD is the most direct measure and is calculated as the sum of the lengths of the branches that connect all species in a community on a phylogenetic tree. This approach assumes that each unit of branch length represents an equal amount of evolutionary history, which makes it both intuitive and widely applicable [54]. However, PD does not account for the relative positions of species within the tree, which prompted the development of pairwise metrics such as the MPD and MNTD; the MPD assesses the average phylogenetic distance among all pairs of species in a community, whereas the MNTD focuses on the distance to the closest relative, thus emphasizing more recent evolutionary events.

Indices such as the NRI and the NTI are often used to interpret these PD metrics within an ecological context. These indices compare observed values to those generated under a null model, typically by randomizing species occurrences across a fixed phylogenetic tree [55,56]. Positive NRI or NTI values indicate phylogenetic clustering, i.e., that the co-occurring species are more closely related than expected, which is often attributed to environmental filtering. Negative values suggest phylogenetic overdispersion, which indicates processes such as competitive exclusion or historical dispersal events. Thus, these standard effect size (SES) metrics provide a statistical framework for testing community assembly processes and can reveal hidden ecological filters in forest environments. Moreover, metrics such as PE and RPD extend conventional PD metrics by incorporating spatial distributions and null expectations, respectively, offering valuable tools for identifying biodiversity hotspots and evolutionary refugia [42,57].

The selection of a suitable null model is crucial when applying these metrics, as different models control for different ecological and evolutionary constraints. For instance, the independent swap algorithm randomizes species occurrences while preserving row and column totals in the community matrix, thereby maintaining the observed species richness and site occupancy [57,58]. Other models, such as the tip-shuffling model, randomizes the tree topology itself. The choice of null model should align with the ecological hypothesis being tested, and multiple models are often compared to ensure robust inference. In forest ecosystems, where both historical (e.g., glacial refugia) and environmental filters (e.g., elevation, soil type) significantly influence the PD, selecting an appropriate null model is essential to accurate interpretation.

Table 1. Summary of the key phylogenetic diversity metrics used in forest ecology and conservation.

Metric	Formula/Basis	Description	Strengths	Limitations	References
PD (Faith’s Phylogenetic Diversity)	∑ (branch lengths connecting all species in a sample)	Measures total evolutionary history represented in a community	Simple, widely adopted, scales with richness	Sensitive to species richness and tree topology	[18]
MPD (Mean Pairwise Distance)	Mean of all phylogenetic distances between species pairs	Reflects average relatedness across a community; emphasizes deep divergence	Detects phylogenetic clustering and overdispersion	Biased by richness; influenced by basal divergence	[59,60]
MNTD (Mean Nearest Taxon Distance)	Mean phylogenetic distance to each species’ closest relative	Captures tip-level evolutionary divergence across a community	Useful for identifying recent radiations	Sensitive to rare taxa and sample completeness	[18,61]
NTI (Nearest Taxon Index)	−(MNTDobs − MNTDrand)/ StDev(MNTDrand)	Measures degree of tip-level clustering relative to null model	Indicates recent evolutionary filtering	Depends strongly on null model and taxon resolution	[59]
NRI (Net Relatedness Index)	−(MPDobs − MPDrand)/StDev(MPDrand)	Quantifies overall community clustering against random expectations	Captures deep phylogenetic structure	Impacted by species pool and branch length distributions	[60,61]
PE (Phylogenetic Endemism)	PD with each taxon’s branch length weighted by the inverse of their range size	Measures geographically restricted evolutionary history	Highlights endemism hotspots and refugia	Requires detailed range and tree data	[62,63]
RPD (Relative Phylogenetic Diversity)	Observed PD/the PD expected from null model	Compares the observed PD to a null expectation	Indicates over- or under-dispersion	Interpretation depends on null model	[63]

Table 1. Summary of the key phylogenetic diversity metrics used in forest ecology and conservation.

Metric	Formula/Basis	Description	Strengths	Limitations	References
PD (Faith’s Phylogenetic Diversity)	∑ (branch lengths connecting all species in a sample)	Measures total evolutionary history represented in a community	Simple, widely adopted, scales with richness	Sensitive to species richness and tree topology	[18]
MPD (Mean Pairwise Distance)	Mean of all phylogenetic distances between species pairs	Reflects average relatedness across a community; emphasizes deep divergence	Detects phylogenetic clustering and overdispersion	Biased by richness; influenced by basal divergence	[59,60]
MNTD (Mean Nearest Taxon Distance)	Mean phylogenetic distance to each species’ closest relative	Captures tip-level evolutionary divergence across a community	Useful for identifying recent radiations	Sensitive to rare taxa and sample completeness	[18,61]
NTI (Nearest Taxon Index)	−(MNTDobs − MNTDrand)/ StDev(MNTDrand)	Measures degree of tip-level clustering relative to null model	Indicates recent evolutionary filtering	Depends strongly on null model and taxon resolution	[59]
NRI (Net Relatedness Index)	−(MPDobs − MPDrand)/StDev(MPDrand)	Quantifies overall community clustering against random expectations	Captures deep phylogenetic structure	Impacted by species pool and branch length distributions	[60,61]
PE (Phylogenetic Endemism)	PD with each taxon’s branch length weighted by the inverse of their range size	Measures geographically restricted evolutionary history	Highlights endemism hotspots and refugia	Requires detailed range and tree data	[62,63]
RPD (Relative Phylogenetic Diversity)	Observed PD/the PD expected from null model	Compares the observed PD to a null expectation	Indicates over- or under-dispersion	Interpretation depends on null model	[63]

2.3. Tools and Software

The calculation and visualization of phylogenetic diversity metrics have been greatly advanced by a suite of computational tools and software packages. Among the most widely used is Picante, an R package that is specifically designed for integrating phylogenies with ecological data. Picante allows users to compute the PD MPD, MNTD, NRI, NTI, and other indices while supporting null model analyses and trait-based metrics. Its seamless compatibility with other R packages, such as vegan and ape, makes it suitable for ecological modeling and statistical analysis [64,65,66]. Phylocom, another foundational tool, is a standalone application that specializes in analyzing community phylogenetic structures and evolutionary trait dispersion. It includes functions for calculating independent contrasts, modeling trait evolution, and assessing community turnover, which makes it highly valuable for forest biodiversity research [67,68].

For spatial and biogeographical analyses, Biodiverse provides a powerful graphical interface that is optimized for identifying spatial patterns in PD and PE [69,70]. A key feature is its ability to perform CANAPEs, a statistical method that classifies regions based on whether their endemism stems from ancient or recently diverged lineages [71]. This tool is particularly useful in forest biogeography, where understanding the temporal origins of lineages can inform conservation decisions. Additionally, Biodiverse supports raster-based inputs, enabling the integration of layers that contain environmental data, such as the climate, elevation, and land use.

All of these tools require two essential inputs: a phylogenetic tree, preferably an ultrametric tree that represents divergence times, and a community matrix that indicates species’ presence/absence or abundance across sites. Increasingly, these tools also incorporate environmental layers, enabling the simultaneous analysis of phylogenetic diversity and environmental gradients. With the growing popularity and accessibility of high-throughput sequencing technologies and global phylogenies, the ability to conduct robust PD analyses across spatial and ecological scales is rapidly expanding [72]. The integration of evolutionary history, community structures, and spatial dynamics is revolutionizing forest biodiversity assessments and shaping the next generation of conservation strategies. Figure 1 summarizes the computational tools and their required data inputs, as well as future research directions in phylogenetic diversity and the major developments affecting them.

3. Patterns of Phylogenetic Diversity in Forest Ecosystems

The phylogenetic diversity of species is not evenly distributed across the globe but instead reflects complex evolutionary, ecological, and biogeographic histories that vary by region, biome, and environmental context [73]. Forest ecosystems, in particular, exhibit striking differences in their phylogenetic composition depending on their location, age, and level of disturbance. These patterns are influenced by both deep-time evolutionary processes, such as continental drift and ancient climate shifts, and more recent ecological dynamics, such as dispersal, competition, and anthropogenic fragmentation. While species richness has traditionally served as the most visible signal of biodiversity, PD reveals hidden layers of evolutionary history that can differentiate forests with superficially similar taxonomic profiles [74,75]. In this section, we explore how forest PD varies globally, with a special focus on elevational and latitudinal shifts, and present case-specific insights from Asian montane systems, including the Pan-Himalayan region and Tibetan Plateau.

3.1. Global Patterns

Globally, tropical forests harbor the highest levels of phylogenetic diversity, a trend that is attributed to the coexistence of both ancient and rapidly diversifying lineages within these relatively stable, long-lived ecosystems [75]. For instance, the Amazon rainforest, recognized for its immense taxonomic diversity, exhibits a broad phylogenetic spread owing to the co-occurrence of lineages that diverged tens of millions of years ago, e.g., families such as Fabaceae, Rubiaceae, and Lauraceae, which contributes significantly to the total branch length captured by PD metrics. In contrast, boreal forests, while potentially hosting a comparable number of species across vast spatial extents, tend to consist of more closely related taxa, such as those within the Pinaceae and Betulaceae families, exhibiting lower PDs as a result despite their extensive distribution and ecological significance [76,77]. Global trends in the phylogenetic diversity of forests, with a focus on trends across tropical–boreal and disturbed–undisturbed gradients, are summarized in Figure 2.

Phylogenetic clustering is commonly observed in long-established, undisturbed forests, particularly those with strong environmental filters, such as nutrient-poor soils, consistent moisture regimes, or extreme temperatures. These conditions tend to drive selection toward a narrow range of functional traits, which, in turn, favors closely related species that are adapted to such conditions [78]. For instance, lowland tropical rainforests in Southeast Asia, although species-rich, can exhibit phylogenetic clustering due to the dominance of a few ancient lineages that have radiated within the region. In contrast, forests recovering from recent disturbances, or those located in ecotonal zones, often exhibit higher phylogenetic overdispersion, potentially due to colonization by species from multiple evolutionary origins [79,80]. These examples demonstrate that, while species richness may provide a snapshot of abundance, the phylogenetic diversity offers a more intricate map of the evolutionary processes that shape forest communities.

3.2. Elevational and Latitudinal Gradients

Phylogenetic diversity often exhibits nonlinear trends along elevational gradients, reflecting the interplay between environmental heterogeneity and historical lineage diversification. In many mountainous regions worldwide, including the Andes, Himalayas, and African montane systems, the PD is observed to peak at middle elevations. This phenomenon is attributed to the ecological coexistence of both basal (early-diverging) and more recently derived lineages in these zones, which often represent transitions between lowland and highland forest types [81]. Mid-elevation zones generally provide a range of microhabitats that support species with varied evolutionary histories, which often results in a higher PD relative to the species count alone. These zones also frequently act as refugia during climatic shifts, preserving lineages that may have gone extinct elsewhere, particularly due to their climatic buffering properties [82].

Latitudinal trends in PD also reveal significant biogeographical patterns. Typically, regions closer to the equator, i.e., tropical regions, tend to exhibit higher raw PDs, which reflect the accumulation of species over long evolutionary timescales in relatively stable climates [47]. However, these forests may also exhibit higher phylogenetic clustering, as ecological niches are often conserved among closely related species, a phenomenon that is referred to as niche conservatism. In contrast, temperate and subtropical forests, particularly those in middle latitudes, often exhibit greater phylogenetic overdispersion [81,83]. This may result from the mixing of species from different evolutionary backgrounds due to historical climate oscillations, glacial retreat, and post-glacial recolonization. At high latitudes or extreme elevations, where harsh environmental conditions select for stress-tolerant traits, the phylogenetic clustering tends to increase, as only a limited subset of lineages can persist under such conditions.

These elevational and latitudinal gradients are not merely ecological curiosities, they reflect long-term evolutionary processes that shape biodiversity patterns across scales. Understanding these gradients is crucial for developing conservation strategies that preserve evolutionary potential in the face of climate change [83]. For example, projected warming may push high-elevation and high-latitude species beyond their climatic limits, leading to the loss of unique evolutionary lineages that are unable to migrate further or adapt rapidly. Therefore, documenting and preserving the PD across such wide gradients is essential for not only maintaining species richness but also safeguarding the evolutionary processes that underpin forest ecosystem resilience.

3.3. Case Studies

The Pan-Himalayan region offers a compelling case study of the phylogenetic diversity in forest ecosystems shaped by extreme topographic variation, climatic heterogeneity, and geological history [84]. Spanning from the Eastern Himalayas to the Hindu Kush and Hengduan Mountains, this region supports a high concentration of endemic and relictual species that contribute to elevated values of both PD and PE [85]. Previous studies have revealed that the region contains both paleo-endemics (e.g., species in the Magnoliaceae and Taxaceae families) and neo-endemics, reflecting characteristics associated with both ancient refugia and recent speciation. The presence of such lineages results in high RPD values, particularly in mid- to high-elevation forests, where topographic isolation and climatic buffering have preserved evolutionary history. These forests not only serve as biodiversity hotspots but also as “museums” of evolutionary heritage. Further east, the Tibetan Plateau represents another center of phylogenetic interest, although it remains underrepresented in global biodiversity databases [86]. Despite its harsh climate and relatively low overall species richness, forests on the southeastern edges of the plateau harbor several ancient lineages, particularly those within the Cupressaceae, Ericaceae, and Rosaceae families. These lineages commonly exhibit strong phylogenetic clustering, which indicates adaptation to extreme cold and low-oxygen environments [87]. Similarly, the moist temperate forests of northern Pakistan, particularly in regions such as Swat, Dir, and Gilgit-Baltistan, display patterns of high PD and PE despite there being limited floristic surveys in these areas [88]. Recent data compiled from forest plots in these areas have revealed the co-occurrence of multiple distantly related genera, such as Abies, Quercus, Betula, and Taxus, highlighting the evolutionary richness of these transitional zones between Central Asian and Himalayan flora.

Comparative assessments across forest ecosystems worldwide reveal distinct trends: Tropical forests, such as those in the Amazon and Borneo, exhibit high PD due to deep evolutionary divergence and hyperdiverse lineages. In contrast, recently glaciated temperate zones like Eastern Europe show a lower PD, but they may support rapid post-glacial radiations. Cloud forests in the Andes exhibit both high PD and very high PE due to rapid speciation along elevational gradients. These patterns are summarized in

Table 2. Phylogenetic diversity trends across forest types (case studies).

Region	Forest Type	PD Values	PE Values	Notes	References
Pan-Himalayan region	Mixed coniferous	Moderate	High	Glacial refugia preserve ancient lineages, resulting in relictual endemism	[89,90]
Amazon Basin	Tropical rainforest	High	Moderate	Exceptional diversification, some ancient lineages, others rapidly radiated	[49,91]
Eastern Europe	Temperate deciduous	Low	Low	Reflects recent post-glacial recolonization with few endemic clades	[92,93]
Atlantic Forest (Brazil)	Tropical/subtropical forest	Moderate	High	High levels of both paleo- and neo-endemism; threatened hotspot	[94,95]
California Floristic Prov.	Mediterranean woodland	High	High	Ancient serpentine flora with extreme niche conservatism	[96]
Southeast Asia	Lowland tropical rainforest	Very high	Moderate	Extremely high richness and deep evolutionary history	[97]
Central Africa	Congo rainforest	High	Low	Continuous habitat has allowed diversification, but less spatial isolation	[49]
Northern Scandinavia	Boreal forest	Low	Low	Dominated by a few lineages, cold-filtered communities	[93]
Australia (SW)	Eucalyptus woodlands	Moderate	High	Gondwanan relicts with strong habitat specialization	[98]
Mediterranean Europe	Evergreen sclerophyll	Moderate	Moderate	Diverse genera with moderate endemicity; historical isolation a contributing factor	[99]

, which compares PD and PE trends across various forest types and regions using empirical studies and phylogenetic analyses.

4. Drivers of Phylogenetic Structure

The patterns of phylogenetic diversity observed in forest ecosystems are shaped by a multifaceted interplay of ecological filters (e.g., climate, soil properties), evolutionary history (e.g., speciation, extinction rates), and anthropogenic pressures (e.g., deforestation, land-use change). These interacting forces influence the persistence, diversification, or loss of lineages across spatial and temporal scales, and thereby determine the phylogenetic structures of forest communities [100,101,102,103]. The most influential factors include environmental filters, such as climate and edaphic conditions, and human-induced disturbances, such as land-use change, habitat fragmentation, and the introduction of non-native species [104]. Additionally, deep-time biogeographical processes, such as tectonic shifts, glaciation, and historical dispersal events, continue to exert a lasting influence on contemporary phylogenetic structures. Understanding these drivers can help us to better interpret the assembly mechanisms of forest communities and aid in the development of conservation strategies that preserve not only species but also their evolutionary heritage.

4.1. Environmental Filters

The environment serves as a fundamental filter that influences the establishment and persistence of species and lineages in a given habitat. Among these, the soil pH, precipitation, and temperature are particularly influential in shaping PD. For instance, ecosystems with high precipitation often support a broader range of niches, fostering the coexistence of distantly related taxa. This, in turn, increases the PD and reduces clustering, as indicated by lower NTI values [42]. In contrast, arid or drought-prone environments tend to favor a narrower range of functional traits, such as those that promote drought tolerance, like high water-use efficiency, leading to phylogenetic clustering, as only a few closely related lineages can survive these harsh conditions. This is reflected in higher NTI values and lower MPD values, which indicate that these communities consist of species that are more closely related than would be expected by chance [105].

The soil pH also plays a nuanced role in shaping PD, often exhibiting non-linear effects. Extremely acidic or alkaline soils limit the diversity of root symbioses and microbial interactions, which, in turn, affects plant establishment; as a result, these types of soil act as strong environmental filters. In contrast, neutral to moderately acidic soils may support more diverse symbiotic relationships, facilitating the establishment of a wider variety of lineages. Consequently, the PD may peak at intermediate pH levels, where ecological constraints are relaxed and evolutionary experimentation is maximized. The temperature, particularly in montane or high-latitude forests, exerts a similar influence. By selecting for cold-tolerant or frost-resistant species, these environments tend to increase phylogenetic clustering, as only a subset of lineages possesses the physiological adaptations required for survival.

Table 3. Environmental variables and the hypothesized impacts of increases in each variable on PD and PD metrics.

Environmental Variable	Expected Effect	Impact on PD Metrics	Explanation	References
Precipitation	Increased PD	PD ↑, NTI ↓	Promotes niche heterogeneity and speciation, reducing phylogenetic clustering	[19,64]
Aridity	Phylogenetic clustering	NTI ↑, MPD ↓	Acts as an abiotic filter, allowing survival of only drought-tolerant lineages	[57,106]
Soil pH	Non-linear effect	PD peaks at neutral pH	Influences microbial symbiosis and nutrient availability, affecting clade composition	[107,108]
Elevation	Varies by gradient	PD ↓, NTI ↑ at high altitudes	Harsher conditions restrict the community to more closely related species	[109]
Temperature	Moderate increases → PD ↑	PD ↑, MPD ↑	Warmer zones support diverse taxa but may experience homogenization under extreme conditions	[110]
Nutrient availability	Depends on limitation	MPD varies, NTI ↓ in rich soils	High-nutrient soils can support more distantly related species with varied strategies	[64]
Disturbance regime	Dispersal-driven assembly	PD ↑, NTI ↓ or ↑, depending on context	Can promote the coexistence of disparate lineages or clade filtering, depending on the disturbance type	[108]

Note: →: causal relationship; ↑: increase; ↓: decrease.

summarizes our current knowledge on the relationships between environmental filters and PD, outlining various abiotic factors and their influences on key phylogenetic metrics and community structures.

4.2. Disturbance and Land-Use Change

In addition to natural filters, anthropogenic disturbances have emerged as powerful drivers of the phylogenetic structure in forest ecosystems. Activities such as logging, slash-and-burn agriculture, urban expansion, and the conversion of forests into plantations lead to habitat loss and fragmentation. When combined with climate change, these disturbances worsen the impacts on the phylogenetic structures of ecosystems. Climate change accelerates the loss of evolutionary lineages by isolating species in fragmented habitats, which reduces their ability to migrate or adapt to changing conditions. These processes often result in the selective removal of evolutionarily distinct lineages. As a consequence, the overall PD is typically reduced and the phylogenetic clustering typically increases as more generalized and disturbance-tolerant species, often from a limited number of clades, colonize or dominate the altered landscape [75]. This shift homogenizes the community structure and erodes the evolutionary depth of forest ecosystems, potentially compromising their resilience to future environmental changes [74,111].

One of the most insidious impacts of human activity is the introduction of exotic or invasive species, which can further distort phylogenetic patterns. Introduced species may outcompete native taxa, becoming invasive species, particularly those with narrow ecological niches or limited geographic ranges. In many cases, these species belong to clades that are already well-represented in the local flora, and thereby exacerbate phylogenetic clustering and reducing overall uniqueness [112]. Invasive species may also come from phylogenetically depauperate but highly aggressive clades, further contributing to clustering and limiting evolutionary potential within communities as a result. Furthermore, plantations of economically valuable but phylogenetically narrow genera, such as Eucalyptus, Pinus, and Acacia, can lead to artificially low PDs, even in high-biomass systems. These changes are effectively captured in Figure 3, which illustrates how both natural and human-induced pressures interact to shape key metrics, such as PD, PE, and RPD.

4.3. Historical Biogeography and Speciation

While environmental and anthropogenic factors influence contemporary patterns, the historical context in which forest communities evolved is equally important. Biogeographic processes, such as vicariance, i.e., the geographic separation of populations due to physical barriers, and long-distance dispersal, result in enduring changes in the phylogenetic structure of forests [113]. Tectonic activity, for instance, has played a significant role in the diversification of lineages by isolating populations and enabling allopatric speciation. A prominent example is the uplift of the Himalayas and the Qinghai–Tibetan Plateau, where tectonic forces created a diversity of microclimates and physically separated species pools, which resulted in the emergence of unique lineages found nowhere else [54].

Glaciation cycles during the Pleistocene further influenced phylogenetic patterns by driving species range shifts and extinctions [114]. Forests that served as glacial refugia—such as those in Southeast Asia, the Western Ghats of India, and parts of Central America—tend to have a high PE and harbor ancient lineages that survived periods of climatic instability. In contrast, the post-glacial recolonization of northern latitudes often involved a limited set of pioneer species, which reduced PD and increased clustering. Riverine barriers and mountain ranges also act as evolutionary boundaries, restricting gene flow and promoting local adaptation and speciation. These historical processes help explain why some forests, despite appearing taxonomically similar, can exhibit vastly different phylogenetic compositions [115].

Integrating environmental, anthropogenic, and historical drivers can provide a more comprehensive understanding of the factors that influence phylogenetic structures over time and space. This holistic perspective is crucial for forest conservation, particularly in identifying areas of high evolutionary value and designing management strategies that protect both current biodiversity and the evolutionary processes that sustain it.

5. Phylogenetic Diversity and Conservation Priorities

The recognition of PD as a crucial aspect of biodiversity has prompted a shift in conservation thinking, which has moved from prioritizing species counts to an emphasis on preserving evolutionary history. Phylogenetic diversity offers a broader framework for evaluating the resilience, functionality, and adaptive potential of ecosystems. This perspective is particularly valuable in forest systems, where both ancient and rapidly evolving lineages coexist [42]. Many threatened forests harbor evolutionary relics that represent millions of years of divergence and adaptation [116]. Traditional conservation efforts, which predominantly focus on species richness and endemism, may inadvertently overlook these critical lineages. Integrating PD into conservation planning can facilitate the identification of irreplaceable evolutionary resources and enhance the long-term effectiveness of biodiversity protection efforts. In this section, we explore how PD can be systematically incorporated into conservation strategies, specifically the design of protected areas and the evaluation of ecosystem services.

5.1. Integrating PD into Conservation Planning

Incorporating evolutionary history into conservation planning could allow us to preserve current biodiversity as well as the processes that give rise to it. One of the most widely recognized metrics used for this purpose is EDGE, which combines phylogenetic uniqueness with extinction risk to prioritize species that are both evolutionarily isolated and threatened [63]. For example, forest-dwelling species such as Dipterocarpus lamellatus or Taxus wallichiana score high on the EDGE scale due to their limited number of closely related species and declining populations. However, practical challenges remain in applying PD metrics, such as the difficulty of obtaining robust phylogenies for all taxa in a region and the computational intensity required for large datasets. Moreover, communicating these complex metrics to policymakers can be challenging, which hinders their widespread adoption in conservation efforts. Protecting such species plays a crucial role in preserving evolutionary history. At the community level, metrics such as PD and PE can be incorporated into spatial planning tools to identify forest regions that harbor unique or ancient lineages that species-based metrics alone may fail to capture [117].

A particularly effective tool for this purpose is CANAPE, which classifies areas based on whether their PE arises from ancient lineages (paleo-endemism), recent radiations (neo-endemism), or a combination of both [33]. This classification is crucial in forest conservation because regions that are rich in paleo-endemics may require different management strategies than those dominated by rapidly evolving taxa [99,118]. For instance, paleo-endemic zones may be more vulnerable to climate change due to the narrow ecological tolerances of their resident lineages. A practical workflow for integrating these PD metrics into conservation planning is illustrated in Figure 4. This approach enables more targeted, efficient, and evolutionarily informed forest biodiversity protection.

5.2. Applications in Protected Area Design

Protected areas are the cornerstone of biodiversity conservation, but their effectiveness is often assessed solely based on their species richness or the presence of charismatic fauna. Integrating PD into gap analyses provides a more comprehensive understanding of conservation success and highlights critical evolutionary lineages that remain unprotected [119]. Additionally, several global and regional assessments have demonstrated that a significant portion of global phylogenetic diversity—often more than 30%—lies outside existing protected area networks, a finding with significant implications for forest conservation, which suggests that current efforts may be failing to safeguard unique lineages. The loss of these lineages would result in the significant erosion of evolutionary history [120].

In tropical forest regions such as the Western Ghats of India, the Atlantic Forest of Brazil, and the eastern Himalayas, PD-based assessments have revealed numerous unprotected hotspots of evolutionary distinctiveness [121]. These areas often include relictual taxa that have survived climatic and geological upheavals but now face localized threats from logging, agriculture, and development [122]. Integrating PD into spatial prioritization tools, such as MARXAN or Zonation, enhances the ability of planners to design reserve networks that maximize evolutionary coverage. Such strategies are especially important in biodiversity-rich but data-poor regions, where species-level information may be incomplete but phylogenetic surrogates can still guide effective conservation. Focusing on evolutionary representation in protected areas can help shift the focus beyond species counts, contributing to the long-term resilience and adaptive potential of forest ecosystems as a result [123,124].

5.3. Surrogacy and Ecosystem Services

A key argument for conserving PD is its proposed role as a surrogate for other aspects of biodiversity, including functional diversity and ecosystem services. The rationale for this is that evolutionary distinctiveness often correlates with unique ecological traits, which, in turn, influence key ecosystem functions, such as nutrient cycling, carbon storage, and resilience to disturbance [125]. In forests, plant species are well-known to play critical roles in structuring microhabitats, regulating hydrological cycles, and supporting pollinator networks. Thus, preserving PD may indirectly help maintain these services in forests. Several empirical studies have found strong correlations between high PD and high functional trait diversity, particularly in tropical and temperate forests.

However, the relationship between PD and the functioning of ecosystems is inconsistent. While some communities with high PDs exhibit broad functional roles and stable ecosystem processes, others show weak or no correlation (Table 4). This inconsistency may be attributable to certain key ecological traits evolving convergently in distantly related taxa or remaining conserved within closely related groups, which thereby decouples functional diversity from phylogenetic patterns [18]. Therefore, a combined approach that incorporates PD, functional diversity, and direct measures of ecosystem services is often recommended for robust conservation planning.

Table 4 compares findings from across different regions and study systems from studies that look at the relationships between PD and functional diversity or ecosystem services. For example, Rapacciuolo et al. [126] demonstrated a strong congruence between PD and functional diversity in terrestrial vertebrates across the Americas, highlighting the utility of PD in large-scale conservation efforts. In contrast, Mazel et al. [52] highlighted significant inconsistencies in PD’s ability to capture functional diversity globally, cautioning against relying on PD as a sole metric. Similarly, Wang et al. [127] found that PD and functional diversity jointly regulate ecosystem multifunctionality in semi-arid grasslands, underscoring the importance of integrative biodiversity metrics.

Table 4. Summary of studies assessing PD as a surrogate for functional diversity (FD) and ecosystem services.

Study	Region	PD ↔ FD	PD ↔ Services	Conclusion
Rapacciuolo, et al. [126]	Americas	Strong congruence	Good proxy in terrestrial vertebrates	PD is a useful surrogate for conserving FD and services in large-scale prioritization
Mazel, et al. [52]	Global	Variable (−85% to +92%)	Unreliable overall	PD does not consistently capture FD; risk in assuming surrogate strength
Thompson, et al. [128]	Canada	Positive correlation	Linked to trophic function	Both PD and FD improve ecosystem function across trophic levels
Wang, et al. [33]	China (semi-arid grassland)	Positive relationship	Enhances multifunctionality	Both FD and PD are more predictive than species richness for ecosystem functions
Doxa, et al. [129]	Southern France	Weak congruence	Spatial mismatch	PD and FD vary independently; be cautious if using PD as a sole metric in landscape conservation
Qin, et al. [130]	China (restoration sites)	Consistent congruence	Functional restoration	PD tracks ecosystem recovery, making it useful for restoration assessment
Trindade-Filho, et al. [131]	Brazil	Good alignment (for birds)	Partial	Indicator groups can represent FD and PD, but this varied by taxon
Montaño-Centellas, et al. [132]	Global (raptors)	High congruence	Strong relevance	PD correlates well with functional traits and conservation priority

Table 4. Summary of studies assessing PD as a surrogate for functional diversity (FD) and ecosystem services.

Study	Region	PD ↔ FD	PD ↔ Services	Conclusion
Rapacciuolo, et al. [126]	Americas	Strong congruence	Good proxy in terrestrial vertebrates	PD is a useful surrogate for conserving FD and services in large-scale prioritization
Mazel, et al. [52]	Global	Variable (−85% to +92%)	Unreliable overall	PD does not consistently capture FD; risk in assuming surrogate strength
Thompson, et al. [128]	Canada	Positive correlation	Linked to trophic function	Both PD and FD improve ecosystem function across trophic levels
Wang, et al. [33]	China (semi-arid grassland)	Positive relationship	Enhances multifunctionality	Both FD and PD are more predictive than species richness for ecosystem functions
Doxa, et al. [129]	Southern France	Weak congruence	Spatial mismatch	PD and FD vary independently; be cautious if using PD as a sole metric in landscape conservation
Qin, et al. [130]	China (restoration sites)	Consistent congruence	Functional restoration	PD tracks ecosystem recovery, making it useful for restoration assessment
Trindade-Filho, et al. [131]	Brazil	Good alignment (for birds)	Partial	Indicator groups can represent FD and PD, but this varied by taxon
Montaño-Centellas, et al. [132]	Global (raptors)	High congruence	Strong relevance	PD correlates well with functional traits and conservation priority

Ultimately, although PD alone may not universally predict ecosystem function, its inclusion in conservation assessments offers an essential evolutionary perspective. Additionally, protecting evolutionarily unique species and communities may preserve traits and functions that are not yet fully understood, providing a buffer against future ecological uncertainty. As global change accelerates, incorporating PD into both site-based and landscape-level forest conservation strategies will be increasingly vital for sustaining biodiversity and the essential benefits it provides to humanity.

6. Emerging Trends and Methodological Advances

As the integration of PD into forest biodiversity research advances, technological and methodological advancements are transforming the measurement, mapping, and interpretation of evolutionary patterns [42,133]. Currently, traditional approaches, which have relied on single-gene phylogenies or morphological taxonomies, are giving way to high-throughput sequencing and data-rich modeling frameworks that offer unprecedented resolution and accuracy. These innovations enhance the robustness of phylogenetic trees and facilitate interdisciplinary applications, linking PD to functional traits, spectral data, and environmental variables at large scales. This section highlights three key areas of progress: the advancement of phylogenomics, the integration of remote sensing with phylogenetic data, and the incorporation of trait evolution into community ecology [64].

6.1. Genomic and Phylogenomic Advances

The recent advent of phylogenomics, which involves the construction of large-scale, multi-locus or whole-genome phylogenies using high-throughput sequencing data, is a significant development. In forest biodiversity studies, this approach moves beyond traditional Sanger-based techniques that focus on single or a few genes or regions (e.g., rbcL, matK, and ITS) to sequence entire plastomes or capture from hundreds to thousands of nuclear markers. Whole-plastid genome sequencing, now widely accessible due to reduced sequencing costs, provides deeper resolution across taxonomic levels and improves the accuracy of branch lengths, which is essential for calculating PD. This advancement is particularly beneficial in forest systems where closely related, morphologically cryptic species often coexist [134,135].

New marker systems, such as restriction site-associated DNA sequencing (RAD-seq), the target capture of ultraconserved elements (UCEs), and hybridization-based methods, have gained increasing popularity for the generation of phylogenetic datasets, particularly in non-model taxa. These approaches allow researchers to infer both deep and shallow nodes on the tree of life, enabling a more comprehensive representation of forest community phylogenies [136,137]. Furthermore, these markers are suitable for degraded DNA, making them particularly useful in studies that involve herbarium specimens or ancient forest remains. As a result, researchers can now reconstruct highly resolved phylogenies at local, regional, and global scales, which has led to more accurate estimates of PD, phylogenetic beta-diversity, and community assembly processes. Such advancements have significant implications for conservation, as they improve the identification of evolutionarily unique species and lineages that require protection [138,139].

6.2. Remote Sensing and Phylogenetics

Remote sensing has traditionally been used to assess vegetation structures, land cover, and forest productivity. However, its recent integration with phylogenetic data is unlocking new possibilities in biodiversity research. Tools like the normalized difference vegetation index (NDVI) and light detection and ranging (LiDAR) are now being combined with ground-based biodiversity inventories to model spatial patterns in PD across landscapes. The NDVI, derived from multispectral satellite imagery, provides information on vegetation greenness and productivity, traits that are often correlated with species richness and composition [133,140]. In contrast, LiDAR offers three-dimensional data on the height, structure, and complexity of canopies, all of which influence forest habitat heterogeneity. These factors can act as filters for species with specific ecological traits and evolutionary backgrounds [133,141].

Such remote sensing technologies enable researchers to predict the PD in unsampled areas by correlating remotely sensed environmental variables with phylogenetic metrics derived from field data. This approach is particularly useful in remote or inaccessible forest regions, where traditional sampling is limited. An emerging concept in this field is evolutionary spectral diversity, which attempts to link plant spectral reflectance signatures with evolutionary relatedness. This method assumes that species from different clades exhibit divergent functional traits (e.g., leaf chemistry and pigment concentration) that influence their spectral profiles. Mapping spectral diversity from space may allow for the estimation of the underlying PD in forest ecosystems. Although still in its early stages, this method has the potential to revolutionize biodiversity monitoring. Recent advancements in remote sensing with regard to PD are summarized in

Table 5. Remote sensing applications in phylogenetic research.

Study	Remote Sensing Method	Application	Forest Type	Key Insights
Kamoske, et al. [141]	LiDAR + Hyperspectral (NDVI)	Predict tree PD, FD, and taxonomic diversity	Temperate deciduous forest (USA)	Combined data provides accurate biodiversity mapping across taxa, specifically linking PD to structural and functional diversity.
Bae, et al. [142]	LiDAR + NDVI	Model bird phylogenetic & functional diversity	Temperate forest (North America)	NDVI is linked to productivity; LiDAR captures structural heterogeneity, which affects community traits and PD.
Melin, et al. [140]	LiDAR + RENDVI	Assess vegetation structure–diversity link	Mixed woodlands (UK)	High canopy structural diversity (LiDAR) predicts avian PD more effectively than NDVI alone, emphasizing the connection between canopy structure and PD.
Coverdale and Davies [143]	LiDAR	Structural complexity–diversity theory	Global review	LiDAR is crucial in linking vertical complexity to community assembly and evolutionary history
Dunn and Blesius [144]	LiDAR + Multispectral (NDVI)	Predict PD in montane forests	Temperate montane (California)	Elevation, solar insolation, and NDVI/structure data can be combined to model PD
Lausch, et al. [145]	NDVI + Spectral Time Series	Monitor forest health & structure	Multi-biome/global	NDVI seasonality can be used as a proxy for forest phenology influencing PD estimates, helping to link phenology to evolutionary processes.

, which outlines the application of NDVI and LiDAR variables in assessing forest structure and linking them to phylogenetic community patterns.

6.3. Trait–Phylogeny Integration

The integration of functional trait data with phylogenetic information offers a deeper understanding of the influence of evolutionary history on ecological strategies and community dynamics [56,146]. Traits like the wood density, specific leaf area, root depth, and drought tolerance of an area are closely associated with species’ ecological roles and their ability to survive in diverse forest environments. By mapping these traits onto phylogenetic trees, researchers can identify patterns of trait conservatism or convergence to elucidate how evolutionary history either constrains or facilitates ecological adaptation [147]. For instance, conservative traits such as wood density often exhibit a strong phylogenetic signal, which implies that closely related species tend to share similar values. This relationship has important implications for understanding the carbon storage, mechanical stability, and resistance to disturbance of forests.

Trait–phylogeny integration is also critical for distinguishing between environmental filtering and competitive exclusion mechanisms. When traits and phylogenetic relationships are closely linked, phylogenetic clustering suggests that environmental filters are selecting for conserved traits. Conversely, trait dissimilarity among closely related species may indicate ecological divergence and niche partitioning. This dual perspective is particularly informative in forests, where functional roles are crucial to various ecosystem services, such as water regulation, nutrient cycling, and pollination. The conceptual framework for this integration is illustrated in Figure 5, which links groups of functional traits to phylogenetic branches and highlights how these relationships influence ecosystem-level outcomes.

Combining evolutionary trees, trait databases, and ecological models can allow researchers to expand beyond species diversity and shine a light on the evolutionary mechanisms that shape forest structure and function. This synthesis refines our ecological theories and supports more nuanced and effective conservation strategies that recognize the importance of preserving not merely species numbers, but also the diversity of life’s evolutionary strategies. As these methodologies become more accessible and computationally streamlined, their adoption is expected to increase across the forest ecology, biogeography, and conservation sciences.

7. Future Directions

The integration of PD into forest biodiversity science has advanced significantly over the past two decades. However, considerable challenges remain before PD can be routinely applied to large-scale conservation planning, biodiversity monitoring, and environmental policy [148,149]. As we continue to uncover the evolutionary dimensions of forest ecosystems, it is essential to address the current limitations in data availability, regional representation, and policy integration. Moving forward, the success of PD-centered biodiversity science will depend on our ability to bridge data gaps, promote international collaboration, and embed evolutionary thinking within global conservation frameworks. This section outlines the major future directions in which forest PD research should proceed, emphasizing areas where methodological refinement, interdisciplinary partnerships, and institutional engagement are most urgently needed.

7.1. Data Gaps and Standardization

A fundamental limitation in PD research in forest ecosystems is the lack of comprehensive, high-resolution phylogenies for many plant lineages. Although the advent of next-generation sequencing has improved the coverage for certain taxonomic groups, large clades, particularly those that are rich in tropical forest species, remain underrepresented in global phylogenies. This taxonomic bias is further compounded by limited geographical sampling, particularly in biodiversity hotspots such as the Congo Basin, the Amazon, and Southeast Asia, where access to genomic resources is often limited. Without denser and more representative phylogenies, estimates of PD may be skewed, which reduces their effectiveness in robust conservation planning [150,151].

Standardizing the methodologies for PD assessment are equally critical. Researchers often use different metrics (e.g., PD, MPD, NTI), tree-building techniques, and null models, which makes cross-study comparisons difficult. To address this, the scientific community could organize workshops and develop consensus statements to agree on protocols for tree construction, trait selection, and null model testing. Additionally, the creation of shared platforms for data and methodology exchange could facilitate greater standardization and collaboration across regions and forest types. Establishing a shared analytical framework, which would require consensus on protocols for tree construction, trait selection, and null model testing, would significantly enhance the reproducibility of research findings and facilitate synthesis across regions and forest types. Moreover, there is an urgent need to develop a global forest PD database that integrates phylogenetic, functional, and spatial data across multiple scales. Such a resource would enable macroecologists and conservationists to identify large-scale evolutionary patterns, test hypotheses on lineage diversification, and prioritize forest areas with disproportionately high evolutionary value [152]. The scope of these methodological and data-related challenges is illustrated in Figure 6, which highlights key nodes such as phylogenetic incompleteness, sampling bias, community engagement, and integration with policy agendas.

7.2. Regional Focus and Collaboration

The geographical imbalance in phylogenetic research remains a persistent challenge. Our current understanding of forest PD is largely derived from studies conducted in well-funded, temperate regions, whereas tropical forests, which harbor the majority of the world’s biodiversity, are often underrepresented. Regions such as Southeast Asia, the Andes, East and Central Africa, and parts of Oceania are in urgent need of phylogenetically informed biodiversity assessments [153,154]. These areas are species-rich and harbor ancient and evolutionarily unique lineages that could significantly advance our understanding of global diversification patterns and biogeographic history.

Addressing these imbalances will require a concerted effort to foster international collaboration among institutions, researchers, and governments. Collaborative frameworks should bring together ecologists, taxonomists, molecular biologists, geographers, and conservation planners. Building regional research capacities through training, funding, and shared infrastructure will empower local scientists to lead PD research within their own forest systems. Additionally, engaging indigenous communities and citizen scientists can expand data collection efforts and enhance the cultural relevance and legitimacy of conservation initiatives [155,156]. In the era of open science, the sharing of phylogenetic datasets, environmental layers, and biodiversity metrics will be essential to overcoming geographical and institutional barriers, and collaborative, regionally focused research will be fundamental to addressing existing knowledge gaps and building a globally representative understanding of forest PD.

7.3. Science–Policy Interface

Despite its scientific maturity, PD has yet to be fully integrated into most biodiversity policy frameworks. Key global agreements, such as the Convention on Biological Diversity (CBD), have historically emphasized species richness and endemism, with limited recognition of the evolutionary dimension of biodiversity. However, there is increasing acknowledgement that incorporating PD into planning can enhance the ecological and functional resilience of ecosystems, and that PD, therefore, merits inclusion in conservation target-setting. As new global frameworks, such as the post-2020 Global Biodiversity Framework, are implemented, a critical window of opportunity exists for incorporating PD into national reporting systems, biodiversity action plans, and environmental impact assessments [157].

Integrating PD metrics into ecosystem accounting frameworks, such as the United Nations’ System of Environmental-Economic Accounting (SEEA), and national ecosystem service valuation schemes would strengthen the link between conservation policy and ecosystem functionality. By quantifying the evolutionary value of forest ecosystems, PD can support arguments for conservation funding, habitat restoration, and the development of nature-based climate solutions [18,152]. Furthermore, embedding PD into national biodiversity strategies would help align scientific recommendations with political objectives, and would thus facilitate more holistic and forward-thinking conservation outcomes. To support this transition, scientists must actively engage with policymakers, provide accessible tools and metrics, and demonstrate the practical value of PD in real-world decision-making. Establishing a strong science–policy interface will ensure that evolutionary insights are not confined to academic circles but become a central pillar of global forest conservation efforts.

8. Conclusions

Phylogenetic diversity offers a powerful and nuanced perspective for understanding and conserving the rich tapestry of life within forest ecosystems. Unlike traditional metrics that focus solely on species richness, PD captures the evolutionary depth and divergence present within forest communities, offering insights into the presence of both ancient lineages and recent radiations. This evolutionary context is vital for developing conservation strategies that aim to preserve not only existing biodiversity but also the evolutionary processes that have shaped it over millions of years. As forests worldwide face escalating threats from deforestation, climate change, and habitat fragmentation, it is increasingly important to adopt frameworks that can identify irreplaceable lineages and highlight areas of hidden evolutionary significance.

The integration of phylogenetic perspectives into forest ecology has been greatly accelerated by recent advances in molecular and computational technologies. High-throughput sequencing, phylogenomics, and novel marker systems have improved the resolution and robustness of evolutionary trees, enabling more precise PD analyses across wider spatial and taxonomic scales. Furthermore, combining remote sensing data with phylogenetic metrics presents novel avenues for biodiversity monitoring in data-deficient or inaccessible regions. Coupled with trait-based approaches, these tools now allow ecologists and conservation planners to assess not only the composition of forest communities but also their evolutionary strategies and ecological functions.

As the field advances, it is increasingly evident that PD should no longer be a peripheral consideration in conservation science. It is necessary to move beyond using species counts as the sole biodiversity metric and employ a more integrative, evolution-informed conservation paradigm. Achieving this shift will require addressing critical data gaps, particularly in tropical and understudied forest regions, developing standardized methodologies, and fostering interdisciplinary collaboration. Embedding PD into policy frameworks is equally important, as this will ensure its inclusion in national biodiversity strategies, the design of protected areas, and the planning of global conservation targets.

Ultimately, safeguarding the phylogenetic diversity of forests is not just about protecting evolutionary history, it is about securing the future resilience and adaptability of ecosystems. The grand challenge ahead lies in systematically integrating PD into conservation practices and policy to ensure that future ecosystems retain their evolutionary potential in the face of accelerating environmental change. Recognizing the value of PD now and acting on it can help achieve more impactful, equitable, and enduring conservation efforts.