Exploring Plant Functional Diversity and Ecological Dynamics in Urban Forests: Insights from Metropolitan Manila

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However, rapid urbanization in in megacities such as the Metropolitan Manila has led to the loss and fragmentation of these ecological frontiers, highlighting the urgent need to assess their ecological functions. This study investigates the plant functional diversity and ecological dynamics of two key urban forests in Metro Manila—Arroceros Forest Park and Las Piñas-Parañaque Wetland Park—by analyzing whole-plant and leaf trait-specific indicators to evaluate ecosystem functions and services. Functional diversity indices were employed to identify relationships among plant communities and assess how species' functional traits influence ecosystem stability. Results indicate that while species in both urban forests exhibit similar functions, variations in functional traits are driven by phenotypic plasticity, habitat filtering, and ecological differentiation. These factors influence community-based functional diversity, affecting species adaptability and resilience. The study highlights the importance of maintaining high functional diversity to support ecosystem services, emphasizing the role of urban forests in mitigating environmental challenges in rapidly developing cities. Findings from this research provide valuable insights for urban conservation strategies and reinforce the necessity of integrating functional diversity in urban ecological planning to enhance ecosystem resilience and sustainability but opens more possibilities in overall assessing the ecosystem along with abiotic factors and interactions with other faunal and microbial species that could affect its ecological dynamics. Ecological dynamics Ecosystem resilience Functional diversity Urban forests Urban green spaces Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Study Implications This study highlights the importance of urban forests in sustaining biodiversity and ecosystem health in megacities such as Metropolitan Manila. By examining plant and leaf traits as indicators of ecological functions, we show how species adapt to urban stressors and contribute to ecological stability. Findings suggest that preserving diverse plant functions, represented by these traits, enhances resilience against environmental changes. For city planners and policymakers, this research underscores the need to prioritize green spaces in urban development. Protecting and restoring these areas can improve air quality, reduce heat, and support wildlife, ultimately creating healthier and more livable cities for both people and nature. 1. Introduction The Metropolitan Manila, also known as Manila Megacity, is considered one of the economic centers of the country. However as continuous development occurred, the landscape was transformed significantly, leading to a surge in informal settlements lacking adequate infrastructure and services (Almadrones-Reyes & Dagamac, 2023 ). The rapid urban expansion, driven by increasing urban populations and rural-to-urban migration, resulted in complex socio-economic, health, and environmental challenges (Malaque & Yokohari, 2007 ; Centeno-Canlas et al., 2023 ). Throughout its history, the Metropolitan region experienced numerous unfulfilled urban planning visions, such as Burnham’s 1905 Plan for Manila. These plans envisioned expansive public green spaces that would serve as communal areas for all citizens of all economic classes. Unfortunately, many of these parks were either never realized or were gradually replaced by commercial and residential developments, compromising the availability of much-needed green spaces (Saloma & Akpenodu, 2021). Metro Manila's rapid urbanization and the loss of planned green spaces have resulted in significant environmental challenges, including degraded air quality, increased temperatures, and the decline of biodiversity. As urban sprawl continues to reshape the city, the need for sustainable green infrastructure has become more pressing. Urban green spaces (UGS) are crucial to fostering sustainable cities, serving as vital natural environments within urban settings (Olfato-Parojinog et al., 2024 ). These areas deliver numerous ecological benefits to the city. Among their key functions are the mitigation of noise pollution, improvement of air quality by filtering particulate matter, and provision of urban cooling through carbon storage and sequestration. Additionally, UGS aids in flood control and offers important habitats for diverse plant and animal species, thus enriching urban biodiversity (Nowak et al., 2006; Scott et al., 2016; Margaritis & Kang, 2017; Lee et al., 2015). Beyond these ecological benefits, urban green spaces also contribute to ecosystem stability and resilience through functional diversity—the variety of functional traits within an ecosystem's organisms. Functional diversity is an emerging aspect of biodiversity that emphasizes the role of species' functional traits in ecosystem processes (Diaz & Cabido, 2001; Young & Collier, 2009 ). These traits, which include morphological characteristics like leaf size, seed dispersal, and root depth, can determine how organisms interact with their environment and contribute to functions like nutrient cycling and productivity (Lavorel & Garnier, 2002 ; McGill et al., 2006 ; Lavorel et al., 2010 ). Functional diversity has been shown to be a key indicator of ecosystem stability, resilience, and resource dynamics, often having a greater influence on local ecosystems than taxonomic diversity alone (Tilman, 1999 ; Cardinale et al., 2006 ; Diaz et al., 2007b). By maintaining a wide range of functional traits, ecosystems can better withstand disturbances and avoid undesirable shifts that lead to key ecosystem losses (Folke et al., 2004 ; Leenhardt et al., 2015 ). However, while previous studies have highlighted the importance of functional diversity in ecosystem stability, there remains a gap in understanding how these dynamics operate within highly urbanized settings like Metropolitan Manila. Specifically, there is limited research on how functional traits vary across different urban forest ecosystems and how these variations influence the provision of ecosystem services. This study aims to address these gaps by examining the functional diversity patterns of plant communities in two distinct urban green spaces. In this paper, the biodiversity of two of the last ecological frontiers of Metropolitan Manila, namely Arroceros Forest Park and Las Pinas Paranaque Wetland Park, were investigated by examining whole-plant and leaf trait-specific indicators that primarily provide ecosystem-specific information on the potential ecosystem services and functions these urban forests can offer. Additionally, the study aims to correlate functional diversity indices of plant communities to identify potential relationships and dependencies between various aspects of functional diversity within these communities. The dissimilarity patterns among the common species in these communities were also assessed and explored the underlying factors shaping functional trait variation. Ultimately, this research seeks to identify the dominant axes of trait variation and reveal potential relationships between species and functional traits across the urban forest ecosystems. Through this approach to studying forest diversity, valuable insights into the role of functional diversity in enhancing ecosystem resilience can serve in informing future conservation efforts within these critical urban ecological frontiers. 2. Study Area 2.1 Las Piñas- Parañaque Wetland Park (LPPWP) Las Piñas- Parañaque Critical Habitat and Ecotourism Area (LLPCHEA) (Fig. 1 a) or now known as the Las Piñas- Parañaque Wetland Park, is an established protected ecosystem located at the coasts of the cities of Las Piñas and Parañaque in Metro Manila, Philippines, declared as an area of protection during the year 2007, designated as a wetland of international significance by Ramsar convention in 2013, and now under the expanded National Integrated Protected Areas Act of 2018. Both endangered and endemic bird species inhabit it, and it is a vital habitat for migratory birds. The protected area also comprises multiple ecosystem subtypes: mixed beach, mangrove forests, salt marsh, and grasslands. 2.2 Arroceros Forest Park Located in the heart of Manila, alongside historical structures such as Metropolitan Theater, government offices, local railway, commercial establishments, and universities, lies a 2-hectare riverside park (along Pasig River) named Arroceros forest park (AFP) (Fig. 1 b). It is located on Antonio Villegas Street, formerly Arroceros Street, in Barangay 659-A Zone 71, Ermita, in the fifth District of Manila (14.5942° N, 120.9817° E). The forest park is considered to be the last lung of Manila. The forest has been subjected to significant threats in recent years as developers plan to convert the forest into establishments. However, the park was established as the Local Government’s (LGU) permanent forest park under the protection of the LGU ordinance. Although the forests have been subjected to tree inventory, there are no published taxonomic surveys and ecological studies done in the area, which can further strengthen the protection of the area by supplementing science-based findings and solutions, primarily focusing on the ecosystem services it can provide to the community. 2.3 Taxonomic Assessment In determining the species/ taxonomic composition of the chosen urban forests, five 20m x 20m vegetation plots were established at 20 meters per plot. Prior species identification will be referenced in field guides. It will be further confirmed in Co’s Digital Flora of the Philippines (Pelser et al., 2011 ) and by looking through the original morphological description of the species. This was then recorded along with the number of individuals per species (See species list in supplementary table 1 –3). 2.4 Functional diversity assessment using Whole plant & Leaf Traits 2.4.1 Choice of functional traits As the basis of sampling effort of the study, the measurement of the plant functional traits (whole plant and leaf traits) was in accordance with the standardized protocol established by Cornellissen et al. (2003) First, specific criteria were established in choosing representative individuals per species, such as the robustness of the plant and its location. This is to ensure that the leaf functional traits acquired from the leaf samples will represent the plants' response to light. Whole plant traits of the plants will be classified according to their growth and life form (categorical). The growth form, which is associated with plant strategy and climatic factors, can be determined through the canopy structure and height of the plant. On the other hand, the life form, which primarily describes the relation of the penetrating tissue to the ground surface, indicates a plant's adaptation to climate (Raunkiaer, 1934 ; Whittaker, 1975 ). Plant height, or the shortest distance between the ground and the upper boundary of the primary photosynthetic tissues of the plant, will also be measured since it can indicate environmental stress tolerance or avoidance (Grime, 2001 ). The height will be measured using a telescopic measuring rod. 2.4.2 Sample acquisition, storage, and processing Leaf samples will also be acquired from the field to measure five specific leaf functional traits, namely (1) Specific Leaf Area (SLA), (2) Leaf size, and (3) Leaf dry matter content (LMDC). Five leaves each from 10 individuals per species was acquired for leaf sampling. For the selection of the samples, the leaves must be relatively young, fully expanded, hardened, and acquired from adult plants. In addition, there must be no visible symptoms of pathogen or herbivore attack and without substantial coverages of epiphylls present. Petioles, rachis, and veins must also be included for the standardized measurement of SLA. To represent the variations of the SLA throughout the day, half of the leaf samples will be measured 2–3 hours after sunrise and 3–4 hours before sunset. After the acquisition, leaf samples will be wrapped in moist paper and was placed in sealed plastic bags to remain water saturated. Samples were immediately placed in a cool box for transferring from the field to the laboratory. Consequently, it was placed in the refrigerator (2–6°C) until further processing. For the soft leaves of herbaceous, woody species, leaf rehydration (6 hours) is needed to avoid SLA underestimation. Prior to measurements, the leaves occluding the petiole are rubbed dry, which will then be scanned into a computer image and measured with an image analysis software (ImageJ). The one-sided area of the fresh leaf will be measured with the petiole (for SLA) and without the petiole (Leaf size or lamina area). To ensure the findings' accuracy, the images will also be calibrated. Consequently, the samples will be placed in an oven (60°C for at least 72 hours) prior to weighing the dry mass. The SLA will be computed using the formula below: To measure the leaf dry matter content (LDMC), the rehydrated samples will be weighed for the water-saturated fresh mass, and the oven dried after to weigh the oven-dry mass. The formula for the LDMC content is as stated: 2.4.3 Functional Diversity Indices In order to ensure the avoidance of representation errors in the analysis, seven functional indices were utilized. The indices were mainly divided into three, namely functional richness, functional evenness, and functional divergence. The table below summarizes the indices used for functional diversity analysis. Table 1 Functional diversity indices and descriptions. Functional diversity categories Functional diversity Indices Description Functional richness Functional volume (FRic) trait space volume occupied by species in the community (Villegér et al., 2008). Functional evenness Functional evenness (FEeve) evenness of abundance distribution in a functional trait space (Villegér et al., 2008). Functional divergence Functional divergence index (FDis) Distribution of abundance within the volume of functional trait space occupied by species (Villegér et al., 2008). Multidimensional divergence (FDiv) average weighted distance between each species and the center of gravity in multidimensionalcharacter space, where the center of gravity is the center of gravity of all species (Laliberté & Legendre, 2010 ). Rao’squadratic entropy Multidimensional functional dispersion used to measure diversity and difference within and between populations (Botta-Dukát, 2005). 2.4.4 Statistical analyses In comparing the two forest communities based on functional indices, FD package was utilized (Laliberte & Legendre, 2010) in the form of a pairwise heatmap functional indices matrix. Species-specific leaf trait analyses were also visualized through boxplots. Consequently, to detect if there are correlations between the leaf traits measured, the default package in R was used in computing Pearson correlation and exhibited through pairwise scatterplot diagrams. In determining the similarities and differences of the plant functional traits of the common species between LPPWP and AFP, functional diversity indices were plotted in a Principal Coordinate Analysis (PCoA), exhibiting the functional measures in a multidimensional perspective using the mFD package (Magneville et al., 2021). Lastly, to determine the association of the common species with specific functional traits, a Principal component analysis (PCA) was synthesized. Using PCoA of functional indices from specific plant traits of common species in two urban forests assessed the dissimilarity patterns among species communities and explored the underlying factors shaping functional trait variation. Additionally, PCA is employed to identify dominant trait variation axes and uncover potential relationships between environmental factors and functional traits across urban forest ecosystems. All visualizations made for the analysis were synthesized using the GGplot package in R. For all the aforementioned analyses, indices calculations, statistical tests, and visualizations, R software was used, specifically the fundiversity (Functional Diversity) package (Grenié & Gruson, 2023 ). 3. Results Understanding the community structure and evaluating the changes in biodiversity in ecosystems constitute the fundamental task in the field of ecology (Schneider et al., 2017 ). Aside from the biodiversity looking into the taxonomic and evolutionary measures, the use of functional traits has been a point of interest as physiological characteristics of organisms can reflect their responses to environmental conditions and their role in the ecosystem (Violle et al., 2007 ; Liu et al., 2014 ). Although the urban forests (AFP & LPPWP) were established with human intervention, looking into the ecological functions of the species would assess the efficiency and resilience as the last ecological frontiers in Metropolitan Manila. In this manner, whole plant and leaf traits were utilized as indicators of functional roles namely: (1) Plant height (PH), (2) Life Form (LF), (3) Leaf Size (LS), (4) Specific Leaf Area (SLA) and (5) Leaf Dry Matter Content (LDMC). A wide range of indices were employed in quantifying functional diversity for this study, namely, (1) Rao’s Quadratic Entropy (RaoQ), (2) Functional Dispersion (FDis), (3) Functional Divergence (FDiv), and (4) Functional Evenness (FEve). In comparison to taxonomic diversity indices that measure species according to the vegetation plots established, functional indices measure diversity in the context of multi-dimensional space representing the traits exhibited by the species within the community. Functional divergence (FDiv) measures the degree of niche differentiation, quantifying the degree of abundance of species in the community in terms of the boundaries of occupied functional space (Mason et al., 2005 ). On the other hand, functional evenness (FEve) describes the degree to which the community is distributed in the niche space, evaluating how even distributed the functional traits are represented within the community to allow effective utilization of the resources available (Mason et al., 2005 ; Gioria et al., 2023 ). The dispersion of species within the trait space is quantified using the functional dispersion (FDis) index, addressing how functionally dissimilar the species are from each other (Laliberte & Legendre, 2010). Lastly, an index considering both functional richness and divergence is Rao’s Quadratic Entropy (RaoQ), measuring functional diversity based on the abundance and dissimilarity of species traits within the community (Weigelt et al., 2008 ; Botta-Dukat, 2005 ). To assess if functional diversity indices were independent of each other based on the observations of Villeger et al. (2008), Pearson correlation analysis was conducted (See Fig. 2 ). Although studies have observed that there was no correlation between functional diversity measures (e.g. Villeger et al., 2008; Mouchet et al., 2010; Pakeman, 2011 ), the results have shown correlations between the functional indices. In contrast to what was observed, FEve and FDiv showed a high positive correlation in both forest ecosystems (0.77; 0.76, respectively). This is in coherence with the observations by Morelli et al. ( 2018 ) wherein FEve and FDiv have positive correlation that is independently based on the types of environments, including forests, grasslands, and agricultural areas. Contrasting correlations were also observed between the two urban forests. In terms of the association with RaoQ and Fric, AFP exhibited a moderately positive correlation (0.73), while LPPWP has negligible correlation (0.23). This contrasting trend can also be observed between FDis and Fric (0.38; 0.17), FDiv and Fric (-0.48; 0.57), FEve and Fric (0.11; 0.87), FDis and FDiv (0.19; 0.49), and RaoQ and FDiv (-0.08, 0.58) (See Fig. 2 ). These associations between functional richness, evenness, dispersion, and divergence can change the strength and direction of correlation based on the varying environmental conditions (Morelli et al., 2018 ). Although AFP and LPPWP are both man-made forests, they differ in ecological setting and dominant vegetation. AFP is an urban forest located in the middle of the city along the Pasig River, while LPPWP is a coastal forest situated on the edge of the city along Manila Bay. Thus, abiotic factors can also influence the correlations of the functional indices, as plant physiological characteristics are highly shaped by environmental conditions, which remains to be further explored (Wu et al., 2019). However, in the case of FDis and RaoQ, both urban forests have shown high positive correlation (0.91; 0.99, respectively) as the two indices are closely related to each other as both assess the dispersion of species within the trait space and how functionally dissimilar species are from each other in terms of their functional traits (Laliberte & Legendre, 2010). 3.2 Species-specific functional trait analysis Leaf size, or the individual leaf laminal area is a functional trait serving as an indicator of species’ environmental responses to light and temperature. LS is often a key element of plant functional ecology and is considered as the most accessible for measurements for wide array of species worldwide (Schrader et al., 2021 ). In addition, LS affects the overall leaf temperature which in turn affects vital plant processes such as photosynthesis, transpiration, and respiration rate (Leigh et al., 2016 ). Most species observed having high LS were compound leaves such Leucaena leucophala, Pterocarpus indicus, Delonix regia (AFP), Averrhoa bilimbi and Murray koenegi (LPPWP). The distinguished species with simple leaves to exhibit high relative LS was Terminalia catappa common in both urban forests. Having larger LS is often correlated with higher efficiency in capturing sunlight under shaded canopies (Lusk et al., 2019 ; Li & Wang, 2021 ). Although higher LS can be advantageous in photosynthetic abilities, species with large leaves also have trade-offs such as susceptibility to herbivory and higher within-leaf support cost (Niinemets et al., 2006). Species with smaller LS such as Rivina humilis, Murraya paniculata (for both urban forests), Podocarpus macrophyllus (for AFP), Pithecellobium dulce , and Lumnitzera racemosa , are advantageous in regions with higher temperatures and light intensities as they can regulate leaf temperatures and avoid overheating (Niinemets & Kull, 1994 ; Meier & Leuschner, 2008 ; Tozer et al., 2015 ). Aside from the environmental responses, leaf size also varies based on site-specific features such as water availability, soil fertility, and most especially, phylogenetic differences (Wolfe & Upchurch, 1987 ; Greenwood et al., 2004 ; Peppe et al., 2011 ). SLA, or the area per unit dry mass, is a significant parameter in plant growth and canopy expansion. The functional trait can serve in the determination of leaf area to deploy in relation to the biomass produced (Kimball et al., 2002 ). In addition, SLA influences the total leaf area that is being affected by light use efficiency (LUE) and interception (Kumar et al., 2012 ). In the case of the two urban forests, there are similar species found to have similar impacts on its respective communities. F.ulmifolia resulted in having relatively high SLA while C.inophyllum exhibited lower relative SLA among both communities. Along with F. ulmifolia , the species that showed high relative SLA were D.regia, P. indicus, S.macrophylla, P. parviflora for AFP, and S. diphyllum, G. sepium , and R. humilis for LPPWP. Thus, these species were mainly correlated with having increased light capture capacity and relative growth rates. On the other hand, species such as P.macrophyllus, G. arborea, M. indica (for AFP ), L. leucophala, L. racemosa, and T. catappa (for LPPWP) exhibited lower SLA, which indicates the species’ strengthened ability in resource utilization and preservation of obtained resources in the environment (Delpiano et al., 2020 ; Xu et al., 2023 ). The variations of SLA in species can be determined by several factors, including the genetic variability of the species, environmental variability and responses causing differences in SLA (Wilson et al., 1999 ). LDMC or the ratio of dry mass to fresh mass of leaves serves as a significant variable in studying plant ecology as the trait is associated with the growth and survival of species (Li et al., 2005 ). Specifically, it is being utilized as an indicator of resource strategies such as conservation of resources (water retention), and rapid assimilation and growth trade-off (Wilson et al., 1999 ; Garnier et al., 2001 ; Diaz et al., 2004; Liu & Guan, 2012 ). Exhibited in Figure X are the species-specific LDMC observed in the two urban forests. In AFP, G. arborea, M. indica, F. ulmifolia, and P. longifolia were among the species obtaining the higher ranges of LDMC. Additionally, M. zapota, V. parvifolia, M. koenegi, and T. catappa have high LDMC in the forest composition of LPPWP. Based on the results, the species are involved in the efficient conservation of resources within their respective communities (Poorter & je Dong, 1999; Bao & Liu, 2009 ). Higher LDMC is also correlated with stronger water retention capacity of the leaves (Xu et al., 2023 ). On the other hand, species within the community have exhibited relatively lower LDMC in AFP ( D. regia, C. inophyllum, F. septica and P. indicus ) and LPPWP ( G. sepium, L. racemosa , R. humilis , and M. citrifolia) . Although these species have comparatively lower water retention and resource conservation efficiency, they are mainly involved in rapid biomass production (Li et al., 2005 ). To determine the relationships of the leaf traits with each other (LS, SLA, and LDMC), pairwise correlation analysis was conducted. Although there are graphical associations that can be observed, there were no significant correlations among the traits assessed. In the analysis between LDMC and SLA, both forests (AFP & LPPWP) exhibited inverse but not significant relationships (r 2 = 0.03939, p < 0.05; r 2 = 0.2058, p < 0.01, respectively). Similar observations were seen in the studies of Li et al. ( 2005 ) and Dong et al. ( 2011 ), the SLA values were independent of the changes in LDMC. Although in a species-specific simulation by Zhang et al. ( 2019 ) assessing a single grass species in a controlled environment, they have observed decrease in SLA with increasing LDMC as a physiological response. Similarly, there has been no significant correlation between LS and LDMC (r 2 = 0.009857, p > 0.05; r 2 = 0.0368, p 0.05; r 2 = 0.0003, p > 0.05, respectively). The lack of correlation in LS and SLA were also observed in previous comparative studies (Ackerly & Reich, 1999 ; Fonseca et al., 2000 ; Ackerly et al., 2002 ), suggesting the independence of the two traits with each other, associated with varying environmental aspects and eco-physiological strategies. Although LS and SLA were found to change in parallel to each other, these traits represent different strategies in relation to water and nutrient availability (Mooney & Dunn, 1970 ; Parsons, 1976 ; Cunningham et al. 1999 ; Fonesca et al., 2000). 4.3 Functional diversity of common species among the urban forests Examining the functional traits of similar species across the two urban forests aids in determining the responses of the species, providing insights into the adaptability of the common species to the urban conditions. Additionally, focusing on similar species ensures consistency of comparison. They eliminate confounding factors, such as the unique species that have different functional traits. Lastly, the contribution of the common species can be evaluated in terms of their roles in the varying forest settings. Exhibited in Fig. 21 are the principal coordinates analyses (PCoA) of the functional richness, evenness, divergence, and dispersion of the common plant species from AFP and LPPWP. Through visualization and computation of the PCoA, the functional traits of the species were analyzed in a functional space (Gower, 1966). Figure 7 a shows the FRic, in this manner, the volume of the minimum convex hull representing the community, wherein the vertices of the hull were the species with comparably extreme functional values. Regarding the functional richness, the figure visualizes how much of the niche space is occupied by the species present in the given community considering multiple traits simultaneously (Schleuter et al., 2010; Legras et al., 2018). In the graphical representation through a multidimensional Euclidean trait space, an evident overlapping of traits was observed as the common species from the two urban forests have similarities in function in relation to their respective communities. However, the LPPWP community exhibited higher functional richness (Fric = 0.649) in relation to AFP (0.571), meaning that the LPPWP community has demonstrated a wider range of ecological functions and roles and is described to be more resilient due to higher response diversity (Carturan et al., 2022). Consequently, LPPWP community has more diverse functions than that of the AFP community, exhibited through their FDiv values (FDiv: 0.972, 0.66; respectively). On the other hand, AFP community showed higher FEve than that of LPPWP, meaning that the ecological functions were more distributed among species (FEve:0.545, 0.737; respectively) (Fig. 7 b). A potential factor for the higher functional evenness observed within the AFP community may be attributed to the phenomenon of functional redundancy. This phenomenon denotes the presence of multiple species fulfilling analogous ecological roles or functions within the ecosystem, thereby fostering a more even distribution across the functional space. Such redundancy is frequently associated with heightened functional stability, wherein the ecosystem exhibits resilience and maintains its essential functions even amidst environmental fluctuations (Jurburg & Salles, 2015). In terms of the dispersion of the functions (FDis), Fig. 7 d exhibits the average distance of species from the community centroid in a multidimensional trait space (Cordova- Tapia et a., 2017). This functional measure combines the regularity of the abundance distribution and the functional similarity of dominant species within the communities (Laliberte & Legendre, 2010). Although the two urban forests vary in terms of functional richness, evenness, and divergence, the dispersion of the traits was highly similar for AFP and LPPWP (FDis = 0.394, 0.37, respectively). The presence of common species assessed suggests that these urban forests likely occupy similar ecological niches within the landscape, leading to comparable patterns of functional trait distribution among the species present. To further specify the specific functional roles that the species specialize in, Fig. 7 exhibits Principal Component Analysis (PCA) based on the functional traits present in species common between (a) AFP and (b) LPPWP. In the multivariate visualization of the species and their functional traits, the species functional dynamics of the community can be described, wherein the points that cluster together represent the species with similar ecological strategies or functional roles. The patterns in the distribution of these points undermines the community structure, niche differentiation, and even adaptation to certain environmental conditions. First, a functional trait that was exhibited as one of the leaf traits that best reflect the overall growth of the plant was SLA, which also plays a role in ecological process such as linking plant carbon and water cycle as the ratio depicts carbon gain in relation to water loss within the canopy (Pierce et al., 1994; Gunn et al., 1999; Cornelissen et al., 2003 ; Cheng et al., 2016). A common trend seen in both forests are shrub species M. paniculata and R. humilis and small arbor F.ulmifolia were clustered in the axis of SLA. Interestingly, similar observation was found by Gong & Gao (2019), wherein shrubs exhibited relatively high SLA, in their studies’ case, it was correlated to latitudinal gradients. In addition, as shrubs and small arbors are oftentimes shade-induced due to canopies of trees with greater plant height, Liu et al. (2016) observed that when plants are shaded, there is an increase in SLA. As high SLA is known to contribute to biomass homeostasis, this adaptation of shrubs might simply be a passive response to their environment. There are also other species that clustered towards SLA such as A. indica (exclusively in LPPWP individuals), L. leucophala (exclusively in LPPWP), and V. parviflora (exclusively in AFP individuals), wherein the correlations were site-specific as the relationships were not similarly observed in both urban forests. The species’ plant height serves as a key characteristic for species in terms of important functions for survival such as carbon storage and overall biomass (Conti & Diaz, 2012; Ruiz-Jaen & Potvin, 2011; Mensah et al., 2016). Additionally, this functional trait can dictate the species’ adaptation when competing for light resources and can be correlated with resource availability at competitive environments (Westoby et al., 2002 ). The mesophanerophytes L.leucophala, T.catappa, A. indica ) and megaphanerophyte ( V. parviflora ) in both the urban forest were clustered in the PH axis, indicating that these species mainly contribute to the functional space mainly due to their height. This trait is advantageous as being taller than adjacent individuals in the forest ecosystem equates to greater access to light for photosynthetic processes. However, having higher plant height has numerous tradeoffs such as the expense of energy for structural support (stems and vasculature), and nutrient transport. Individuals from the species T. catappa in LPPWP, however, was not directly associated with PH, which can be due to the interspecific competition as the forest is dominated by other tree species. Additionally, the T. catappa observed nearby coasts were shorter in PH and has disease symptoms such as chlorosis in most leaves, indicating growth limiting factors such as nutrient deficiency and herbivory (Hershey, 2003; Schowalter, 2006). Additionally, the species that are advantageous in terms of PH and its functions, such as C. inophyllum, L leucophala, and T catappa, were also clustered near the axis for LS, which also a competitive advantage in light acquisition, resource utilization, and even carbon sequestration. In a general sense, trees have larger leaves in comparison to small arbors and shrubs, but the taxonomic patterning of the species is a major factor as it undermines evolutionary adaptation (Wright et al., 2004 ). In terms of LDMC, larger woody plants tend to exhibit higher values of LDMC as these species invest nutrients for tissue construction and maintenance—offering resilience in adapting to unfavorable environmental conditions (Ricklefs & Lathan, 1992; Zhou et al., 2020; Wang et al., 2020; An et al., 2021). Based on the PCA, there are variations in terms of species that are related to LDMC. In LPPWP, V. parviflora, C. inophyllum, T. catappa, F. ulmifolia shown to favor the LDMC axis. On the other hand, only A. indica was located near the LDMC axis in AFP. The leaves of these species exhibiting a correlation to LDMC can indicate longer leaf span, relatively tough structure, and high resistance to physical hazards such as herbivory and wind. While the majority of species did not demonstrate a strong correlation with LDMC, those exhibiting relatively low LDMC values were found to be linked with productive yet highly disturbed environments (Perez- Harguindeguy et al, 2013). This observation aligns with the context of the assessed forests situated in harsh environments characterized by significant human disturbances. 4. Discussion Although species trends have exhibited similar functions in the two urban forests, there is still variability wherein species function or adapt differently in the community based on the utilized whole-plant and leaf trait indicators. These variations, or lack thereof, can be undermined by various ecological phenomena, namely (i) phenotypic plasticity, (ii) habitat filtering, and (iii) ecological differentiation, leading to variation in community-based functional diversity. The variations in functional traits can result from a single genotype producing different phenotypic characteristics as a response to environmental conditions, otherwise known as phenotypic plasticity—allowing species to adjust physiologically and morphologically to optimize and survive under different circumstances. In terms of leaf traits, phenotypic plasticity can be exhibited through heterophylly, which occurs as leaves are altered due to varying light intensity, water availability, or even the ambient temperature of its habitat (Goliber & Feldman, 1990; Sicard et al., 2014; Nakayama et al., 2017). The alterations in these functional traits are generally vital for plants in order to adapt to their respective environments through modification morphology, indicating changes in the species' biomass allocation (Xie et al., 2015; Rolhauser & Pucheta, 2016; Freschet et al., 2018; Liu et al., 2022). However, these changes in the vegetative traits of plant species can be adaptive, neutral, or even maladaptive, as observed in studies that conducted field manipulation of abiotic factors (Welker et al., 1993; Ptratt & Mooney, 2013; Song et al., 2016; Navarro et al., 2022). Habitat filtering can also serve as drivers of these functional trait variations and similarities among the species assessed, as environmental conditions, interspecific interactions, or disturbance regimes selectively favor phenotypic traits, leading to preferential establishment of even persistence of individuals with specific functional traits. As a result, spatial segregation can occur within the functional space. The constriction of the niche volume in the form of habitat filtering is a widespread process observed, serving as a driving pattering of functional niche occupancy across different plant communities, in this case, the two urban forests. As observed in the PCA graph, some species cluster in specific functional traits, which is in coherence with the observations by Li et al. (2017), wherein the coexisting species tend to be functionally similar rather than functionally specialized. Additionally, the variations in the functions of the similar species across the two urban forest communities can be affected by the surrounding landscape, as the placement of the habitats is found to affect the functional diversity of plant species, similar to the observations done by Czortek & Pielech (2020) in urban parks. Based on their assessment of community-level coexistence patterns, plant species can be affected by settlements and the level of fragmentation of the urban forests, which decreases functional dispersion. These functional similarities among the plant communities can also indicate resilience so that if one species is removed from the community, it can be buffered by functionally alike species. However, in a long-term perspective, the lowering range of functional diversity and its corresponding plant strategies would be a limiting factor to the adaptation and survival of the community to future changes in the environment (Diaz & Cabido, 2001; Brica et al., 2021). Thus, the conservation of urban forest parks should prioritize maintaining a wider variety of pioneer habitat conditions, yielding a more functionally diverse and resilient community (Czortek & Pielech, 2020). Lastly, ecological differentiation can result in variation in community-based functional diversity due to each species' differing adaptations and strategies to exploit niche opportunities and respond to environmental gradients. This variation can enhance or restrict the range of functional traits present within the community, thereby increasing or decreasing its capacity to fulfill diverse ecological roles and functions. Although similar species can occur in both urban forests, intraspecific variations were detected, as some vary based on their functional characteristics. This claim can be supported by the study conducted by Albert et al. (2010), wherein they quantified intraspecific functional trait variability from 16 plant species subjected to different climatic gradients in an alpine valley and observed large variability of traits within species along with significant discrepancies between functional traits and species—greatly affected by radiation and temperature. While the current study has not investigated the influence of climatic factors and environmental gradients on urban forest ecosystems, considerable potential exists for further exploration in this area. Understanding how climatic variations and environmental gradients shape the structure and function of urban forests can provide valuable insights into their ecological dynamics and resilience. As challenges in sustaining biodiversity continuously arise along with environmental changes, sustained, synoptic, and comparative quantitative forms of measurements are needed (Pacheco-Labrador et al., 2023 ). Assessing functional diversity can help evaluate how ecosystems cope with the changing environment and the organisms' resilience in continuing their services to the community (Jactel et al., 2017 ; Espelta et al., 2020 ). In addition, studying plant functional traits also substantially contributes to strengthening the links between community structure and ecosystem functioning, aside from considering species richness alone (Diaz & Cabido, 2001). Similar to other natural ecosystems, urban forests' ecosystem functioning also depends on the species composition, as having a species- and trait-diverse community tends to have increased stability, which supports the provisioning of ecosystem services (Yachi & Loreau, 1999 ; Balvanera et al., 2006 ; Wood & Dupras, 2021 ). An increased number of functions of diverse species can provide ecological insurance in coping with disturbances and change their responses to stress depending on the community the species belongs to (Messier et al., 2019 ; Espelta et al., 2020 ). Thus, studies have suggested that increasing the diversity of plant species within a forest can improve the functioning rates of the ecosystem through trait complementarity—a phenomenon wherein the combined outcomes of varying traits interact together, resulting in increased ecosystem process rates (Loreau & Hector, 2001 ). However, the ecosystem resilience of forests is not just constricted to the effects of species composition. However, it also encompasses several factors, such as genetic diversity, forest management history, forest size, and even the overall condition of the surrounding landscape (Peterson et al., 1998 ; Thompson et al., 2009 ; Walker et al., 2004 ). Thus, looking into the overall condition of the ecosystem, including the abiotic and anthropogenic factors, can undermine further information regarding the metabolism and behavior of species comprising urban forests. This pioneering research on forest functional diversity in the Metropolitan Region of the Philippines study not only underscores the importance of the preservation and enhancement of green spaces within urban environments but also emphasizes the need for more holistic approaches that consider the ecological factors in urban planning and integration of urban green spaces (see review of Olfato-Parojinog & Dagamac, 2024 ). Through further assessing the ecological aspect of these last ecological frontiers of the megacity, we can contribute valuable knowledge to the ongoing discourse on sustainable urban development, providing a foundation for more informed decision-making and policy formulation aimed at fostering resilient and livable cities in the Philippines and beyond. Declarations Acknowledgments A.O.P. would like to thank the Department of Science and Technology- Science Education Institute (DOST-SEI) Accelerated Science and Technology Human Resource Development Program - National Science Consortium (ASTHRDP- NSC) for the scholarship and funding the research. Sincere thanks are extended to the City of Manila, Parks Development Office, headed by Engr. Gideon Navarro and Forester Gerardo S. Montecillo, for approving the research at Arroceros Forest Park. AOP also expresses gratitude to the Department of Environment and Natural Resources – National Capital Region (DENR-NCR), Las Piñas Parañaque Wetland Park, led by Sir Christopher C. Villarin and Sir Diego Montesclaros, for their support during the field assessments at the protected area. P.C.E.R, J.M.B., C.J.R. would also like to thank DOST-SEI and ASTHRDP-NSC for master’s degree scholarship. The authors are grateful to the three manuscript reviewers for the comments and suggestions that improved this manuscript and for the technical assistance extended by the authors’ family and friends. Competing Interest The authors have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the conception and design of the study. The initial draft of the manuscript was prepared by Anne Olfato-Parojinog, with all co-authors—Christian Elmarc Ocenar-Bautista, Paul Cervin Evangelista-Rivera, Jean-Matthew Bate, Christon Jairus Racoma, Jayson G. Chavez, and Nikki Heherson A. Dagamac—providing critical feedback and revisions to previous versions. All authors have reviewed and approved the final manuscript. 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Palaeogeography, Palaeoclimatology, Palaeoecology , 61 , 33–77. https://doi.org/10.1016/0031-0182(87)90040-x Wood, S. L. R., & Dupras, J. (2021). Increasing functional diversity of the urban canopy for climate resilience: Potential tradeoffs with ecosystem services? Urban Forestry & Urban Greening , 58 , 126972. https://doi.org/10.1016/j.ufug.2020.126972 Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont, B. B., Lee, T., Lee, W., Lusk, C., & Midgley, J. J. (2004). The worldwide leaf economics spectrum. Nature , 428 (6985), 821–827. https://doi.org/10.1038/nature02403 Xu, L., Zhang, N., Wei, T., Liu, B., Shen, L., Liu, Y., & Liu, D. (2023). Adaptation strategies of leaf traits and leaf economic spectrum of two urban garden plants in China. BMC Plant Biology , 23 (1). https://doi.org/10.1186/s12870-023-04301-z Yachi, S., & Loreau, M. (1999). Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis. Proceedings of the National Academy of Sciences , 96 (4), 1463–1468. https://doi.org/10.1073/pnas.96.4.1463 Young, R. G., & Collier, K. J. (2009). Contrasting responses to catchment modification among a range of functional and structural indicators of river ecosystem health. Freshwater Biology , 54 (10), 2155–2170. https://doi.org/10.1111/j.1365-2427.2009.02239.x Zhang, D., Zhang, M., Tong, S., Qi, Q., Wang, X., & Lu, X. (2019). Growth and physiological responses of Carex schmidtii to water-level fluctuation. Hydrobiologia , 847 (3), 967–981. https://doi.org/10.1007/s10750-019-04159-z Additional Declarations No competing interests reported. Supplementary Files OlfatoParojinog2025Supplementarytable.docx Cite Share Download PDF Status: Published Journal Publication published 30 Sep, 2025 Read the published version in Urban Ecosystems → Version 1 posted Editorial decision: Revision requested 09 Jun, 2025 Reviews received at journal 09 Jun, 2025 Reviews received at journal 18 May, 2025 Reviewers agreed at journal 26 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers agreed at journal 19 Apr, 2025 Reviewers invited by journal 14 Apr, 2025 Editor assigned by journal 02 Apr, 2025 Submission checks completed at journal 01 Apr, 2025 First submitted to journal 21 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6281039","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447686410,"identity":"dfd43d1f-4756-484b-9100-fc52e296f0b0","order_by":0,"name":"Anne Olfato-Parojinog","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYPACC34gwfgASPDwEalFQrKBgYHZAKSFjRQtbBIgJkEt/LN7Dz5gqJCQMGc/+6zya46dDBsD88NHN/AZf+dcsgHDGQkJy550s9uy25KBDmMzNs7BZ82NHDMJxjaJOoMDaWy3JbcxA7XwsEnj0yJ/I8f8B1CLhMH5Z2zFktvqCWsxANrCANZyI42N8eO2w4S1GN7IMZZIAPllxjNmacZtx3nYmAn4Re5GjuGHDxU2Eub8aYwff26rtudnb374GK/3QSAB5EIgZuYB8ZgJKYd7CogZfxCrehSMglEwCkYUAADysj4p1NXpgQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":true,"prefix":"","firstName":"Anne","middleName":"","lastName":"Olfato-Parojinog","suffix":""},{"id":447686411,"identity":"7831a894-8e82-41ee-9bc5-4562c5aaa225","order_by":1,"name":"Christian Elmarc Ocenar-Bautista","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"Elmarc","lastName":"Ocenar-Bautista","suffix":""},{"id":447686415,"identity":"84f5fd78-5b25-4f72-8b91-62bca6b99282","order_by":2,"name":"Paul Cervin Evangelista-Rivera","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"Cervin","lastName":"Evangelista-Rivera","suffix":""},{"id":447686417,"identity":"185142d2-f1d2-46ac-962c-943431cb4061","order_by":3,"name":"Jean-Matthew Bate","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Jean-Matthew","middleName":"","lastName":"Bate","suffix":""},{"id":447686418,"identity":"bdcc2e0d-3bd4-4ce6-96fa-9fe02296bfd2","order_by":4,"name":"Christon Jairus Racoma","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Christon","middleName":"Jairus","lastName":"Racoma","suffix":""},{"id":447686422,"identity":"f744cefd-0247-4259-8f1c-7c7e7619324d","order_by":5,"name":"Jayson G. Chavez","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Jayson","middleName":"G.","lastName":"Chavez","suffix":""},{"id":447686424,"identity":"56e31c7e-a4a0-4e15-9e16-7111f02cb60a","order_by":6,"name":"Nikki Heherson A. Dagamac","email":"","orcid":"","institution":"University of Santo Tomas","correspondingAuthor":false,"prefix":"","firstName":"Nikki","middleName":"Heherson A.","lastName":"Dagamac","suffix":""}],"badges":[],"createdAt":"2025-03-22 02:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6281039/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6281039/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11252-025-01804-5","type":"published","date":"2025-09-30T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81372440,"identity":"cf8f251d-9ecc-43af-ba5d-ccdb5ab76c7b","added_by":"auto","created_at":"2025-04-25 10:51:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":500822,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the(a) Las Piñas- Parañaque Wetland Park and (b) Arroceros Forest Park.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/bda27ce5f42a6ddd99236c46.png"},{"id":81372167,"identity":"02e6e819-3c37-4696-a17c-5b142d80aa1c","added_by":"auto","created_at":"2025-04-25 10:43:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":134375,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation matrix of functional diversity indices in AFP and LPPWP.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/48cd4d8ed4021ca12e102ab8.png"},{"id":81371254,"identity":"fd490b45-e166-4f64-a448-a144be9a3c8a","added_by":"auto","created_at":"2025-04-25 10:35:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":146052,"visible":true,"origin":"","legend":"\u003cp\u003eVariability of Leaf Size (LS) between species (in cm\u003csup\u003e2\u003c/sup\u003e) in (a) AFP and (b) LPPWP.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/b06e34c2d8251e1f6156643c.png"},{"id":81371253,"identity":"94631955-49f2-40db-98e7-82ee045867f7","added_by":"auto","created_at":"2025-04-25 10:35:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":182288,"visible":true,"origin":"","legend":"\u003cp\u003eVariability of Specific Leaf Area (SLA) between species (in cm\u003csup\u003e2\u003c/sup\u003eg\u003csup\u003e-1\u003c/sup\u003e) in (a) Arroceros Forest Park and (b) Las Piñas- Parañaque Wetland Park.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/3b14d4d0714cb525ac17b650.png"},{"id":81372170,"identity":"051a5896-f157-4648-ad18-c07905c283fe","added_by":"auto","created_at":"2025-04-25 10:43:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":117390,"visible":true,"origin":"","legend":"\u003cp\u003eVariability of Leaf Dry Matter Content (LDMC) between species (in gg\u003csup\u003e-1\u003c/sup\u003e) in (a) Arroceros Forest Park and (b) Las Piñas- Parañaque Wetland Park.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/edd590d1638030e8e8acbdae.png"},{"id":81371257,"identity":"58fd857e-2832-403f-aa97-dd80b2ee2b04","added_by":"auto","created_at":"2025-04-25 10:35:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":176225,"visible":true,"origin":"","legend":"\u003cp\u003ePairwise correlation analysis of leaf traits of plant species from (a) Arroceros Forest Park and (b) Las Piñas- Parañaque Wetland Park.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/53faf4482705247889bc8089.png"},{"id":81372174,"identity":"bf58f884-54d4-46ee-9a4a-13e8e193112b","added_by":"auto","created_at":"2025-04-25 10:43:05","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":149130,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinates Analysis (PCoA) of Alpha Functional diversity namely: (a) Functional richness, (b) Functional evenness, (c) Functional divergence, and (d) Functional dispersion of the common plant species from AFP and LPPWP.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/e1c9052d1713572957d93a19.png"},{"id":81372168,"identity":"efc926e4-2a4c-4c62-be36-adc1cd73bc3e","added_by":"auto","created_at":"2025-04-25 10:43:04","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":173318,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of the plant functional traits of the species that are found in both AFP and LPPWP. \u003cem\u003eVarying colors indicate different species, and the ellipses primarily define the confidence intervals (0.95).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/603436a5ab8c39eee6f4af8c.png"},{"id":92884373,"identity":"c6acd382-6c21-4d19-b12e-b0f0872ddc1f","added_by":"auto","created_at":"2025-10-06 16:12:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2432677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/a95d7d10-307f-470f-b89f-39df79a63d71.pdf"},{"id":81372166,"identity":"16bfa059-6023-48c1-92b7-2652e441fd69","added_by":"auto","created_at":"2025-04-25 10:43:04","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19782,"visible":true,"origin":"","legend":"","description":"","filename":"OlfatoParojinog2025Supplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-6281039/v1/d8c49fb03e619eff7dd95249.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Plant Functional Diversity and Ecological Dynamics in Urban Forests: Insights from Metropolitan Manila","fulltext":[{"header":"Study Implications","content":"\u003cp\u003eThis study highlights the importance of urban forests in sustaining biodiversity and ecosystem health in megacities such as Metropolitan Manila. By examining plant and leaf traits as indicators of ecological functions, we show how species adapt to urban stressors and contribute to ecological stability. Findings suggest that preserving diverse plant functions, represented by these traits, enhances resilience against environmental changes. For city planners and policymakers, this research underscores the need to prioritize green spaces in urban development. Protecting and restoring these areas can improve air quality, reduce heat, and support wildlife, ultimately creating healthier and more livable cities for both people and nature.\u003c/p\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe Metropolitan Manila, also known as Manila Megacity, is considered one of the economic centers of the country. However as continuous development occurred, the landscape was transformed significantly, leading to a surge in informal settlements lacking adequate infrastructure and services (Almadrones-Reyes \u0026amp; Dagamac, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The rapid urban expansion, driven by increasing urban populations and rural-to-urban migration, resulted in complex socio-economic, health, and environmental challenges (Malaque \u0026amp; Yokohari, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Centeno-Canlas et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThroughout its history, the Metropolitan region experienced numerous unfulfilled urban planning visions, such as Burnham\u0026rsquo;s 1905 Plan for Manila. These plans envisioned expansive public green spaces that would serve as communal areas for all citizens of all economic classes. Unfortunately, many of these parks were either never realized or were gradually replaced by commercial and residential developments, compromising the availability of much-needed green spaces (Saloma \u0026amp; Akpenodu, 2021).\u003c/p\u003e \u003cp\u003eMetro Manila's rapid urbanization and the loss of planned green spaces have resulted in significant environmental challenges, including degraded air quality, increased temperatures, and the decline of biodiversity. As urban sprawl continues to reshape the city, the need for sustainable green infrastructure has become more pressing. Urban green spaces (UGS) are crucial to fostering sustainable cities, serving as vital natural environments within urban settings (Olfato-Parojinog et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These areas deliver numerous ecological benefits to the city. Among their key functions are the mitigation of noise pollution, improvement of air quality by filtering particulate matter, and provision of urban cooling through carbon storage and sequestration. Additionally, UGS aids in flood control and offers important habitats for diverse plant and animal species, thus enriching urban biodiversity (Nowak et al., 2006; Scott et al., 2016; Margaritis \u0026amp; Kang, 2017; Lee et al., 2015).\u003c/p\u003e \u003cp\u003eBeyond these ecological benefits, urban green spaces also contribute to ecosystem stability and resilience through functional diversity\u0026mdash;the variety of functional traits within an ecosystem's organisms. Functional diversity is an emerging aspect of biodiversity that emphasizes the role of species' functional traits in ecosystem processes (Diaz \u0026amp; Cabido, 2001; Young \u0026amp; Collier, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These traits, which include morphological characteristics like leaf size, seed dispersal, and root depth, can determine how organisms interact with their environment and contribute to functions like nutrient cycling and productivity (Lavorel \u0026amp; Garnier, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; McGill et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Lavorel et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Functional diversity has been shown to be a key indicator of ecosystem stability, resilience, and resource dynamics, often having a greater influence on local ecosystems than taxonomic diversity alone (Tilman, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Cardinale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Diaz et al., 2007b). By maintaining a wide range of functional traits, ecosystems can better withstand disturbances and avoid undesirable shifts that lead to key ecosystem losses (Folke et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Leenhardt et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, while previous studies have highlighted the importance of functional diversity in ecosystem stability, there remains a gap in understanding how these dynamics operate within highly urbanized settings like Metropolitan Manila. Specifically, there is limited research on how functional traits vary across different urban forest ecosystems and how these variations influence the provision of ecosystem services. This study aims to address these gaps by examining the functional diversity patterns of plant communities in two distinct urban green spaces.\u003c/p\u003e \u003cp\u003eIn this paper, the biodiversity of two of the last ecological frontiers of Metropolitan Manila, namely Arroceros Forest Park and Las Pinas Paranaque Wetland Park, were investigated by examining whole-plant and leaf trait-specific indicators that primarily provide ecosystem-specific information on the potential ecosystem services and functions these urban forests can offer. Additionally, the study aims to correlate functional diversity indices of plant communities to identify potential relationships and dependencies between various aspects of functional diversity within these communities. The dissimilarity patterns among the common species in these communities were also assessed and explored the underlying factors shaping functional trait variation. Ultimately, this research seeks to identify the dominant axes of trait variation and reveal potential relationships between species and functional traits across the urban forest ecosystems. Through this approach to studying forest diversity, valuable insights into the role of functional diversity in enhancing ecosystem resilience can serve in informing future conservation efforts within these critical urban ecological frontiers.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Las Pi\u0026ntilde;as- Para\u0026ntilde;aque Wetland Park (LPPWP)\u003c/h2\u003e\n \u003cp\u003eLas Pi\u0026ntilde;as- Para\u0026ntilde;aque Critical Habitat and Ecotourism Area (LLPCHEA) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea) or now known as the Las Pi\u0026ntilde;as- Para\u0026ntilde;aque Wetland Park, is an established protected ecosystem located at the coasts of the cities of Las Pi\u0026ntilde;as and Para\u0026ntilde;aque in Metro Manila, Philippines, declared as an area of protection during the year 2007, designated as a wetland of international significance by Ramsar convention in 2013, and now under the expanded National Integrated Protected Areas Act of 2018. Both endangered and endemic bird species inhabit it, and it is a vital habitat for migratory birds. The protected area also comprises multiple ecosystem subtypes: mixed beach, mangrove forests, salt marsh, and grasslands.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Arroceros Forest Park\u003c/h2\u003e\n \u003cp\u003eLocated in the heart of Manila, alongside historical structures such as Metropolitan Theater, government offices, local railway, commercial establishments, and universities, lies a 2-hectare riverside park (along Pasig River) named Arroceros forest park (AFP) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). It is located on Antonio Villegas Street, formerly Arroceros Street, in Barangay 659-A Zone 71, Ermita, in the fifth District of Manila (14.5942\u0026deg; N, 120.9817\u0026deg; E). The forest park is considered to be the last lung of Manila. The forest has been subjected to significant threats in recent years as developers plan to convert the forest into establishments. However, the park was established as the Local Government\u0026rsquo;s (LGU) permanent forest park under the protection of the LGU ordinance. Although the forests have been subjected to tree inventory, there are no published taxonomic surveys and ecological studies done in the area, which can further strengthen the protection of the area by supplementing science-based findings and solutions, primarily focusing on the ecosystem services it can provide to the community.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Taxonomic Assessment\u003c/h2\u003e\n \u003cp\u003eIn determining the species/ taxonomic composition of the chosen urban forests, five 20m x 20m vegetation plots were established at 20 meters per plot. Prior species identification will be referenced in field guides. It will be further confirmed in Co\u0026rsquo;s Digital Flora of the Philippines (Pelser et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e) and by looking through the original morphological description of the species. This was then recorded along with the number of individuals per species (See species list in supplementary table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;3).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Functional diversity assessment using Whole plant \u0026amp; Leaf Traits\u003c/h2\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.1 Choice of functional traits\u003c/h2\u003e\n \u003cp\u003eAs the basis of sampling effort of the study, the measurement of the plant functional traits (whole plant and leaf traits) was in accordance with the standardized protocol established by Cornellissen et al. (2003) First, specific criteria were established in choosing representative individuals per species, such as the robustness of the plant and its location. This is to ensure that the leaf functional traits acquired from the leaf samples will represent the plants\u0026apos; response to light.\u003c/p\u003e\n \u003cp\u003eWhole plant traits of the plants will be classified according to their growth and life form (categorical). The growth form, which is associated with plant strategy and climatic factors, can be determined through the canopy structure and height of the plant. On the other hand, the life form, which primarily describes the relation of the penetrating tissue to the ground surface, indicates a plant\u0026apos;s adaptation to climate (Raunkiaer, \u003cspan class=\"CitationRef\"\u003e1934\u003c/span\u003e; Whittaker, \u003cspan class=\"CitationRef\"\u003e1975\u003c/span\u003e). Plant height, or the shortest distance between the ground and the upper boundary of the primary photosynthetic tissues of the plant, will also be measured since it can indicate environmental stress tolerance or avoidance (Grime, \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e). The height will be measured using a telescopic measuring rod.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.2 Sample acquisition, storage, and processing\u003c/h2\u003e\n \u003cp\u003eLeaf samples will also be acquired from the field to measure five specific leaf functional traits, namely (1) Specific Leaf Area (SLA), (2) Leaf size, and (3) Leaf dry matter content (LMDC). Five leaves each from 10 individuals per species was acquired for leaf sampling. For the selection of the samples, the leaves must be relatively young, fully expanded, hardened, and acquired from adult plants. In addition, there must be no visible symptoms of pathogen or herbivore attack and without substantial coverages of epiphylls present. Petioles, rachis, and veins must also be included for the standardized measurement of SLA. To represent the variations of the SLA throughout the day, half of the leaf samples will be measured 2\u0026ndash;3 hours after sunrise and 3\u0026ndash;4 hours before sunset.\u003c/p\u003e\n \u003cp\u003eAfter the acquisition, leaf samples will be wrapped in moist paper and was placed in sealed plastic bags to remain water saturated. Samples were immediately placed in a cool box for transferring from the field to the laboratory. Consequently, it was placed in the refrigerator (2\u0026ndash;6\u0026deg;C) until further processing. For the soft leaves of herbaceous, woody species, leaf rehydration (6 hours) is needed to avoid SLA underestimation.\u003c/p\u003e\n \u003cp\u003ePrior to measurements, the leaves occluding the petiole are rubbed dry, which will then be scanned into a computer image and measured with an image analysis software (ImageJ). The one-sided area of the fresh leaf will be measured with the petiole (for SLA) and without the petiole (Leaf size or lamina area). To ensure the findings\u0026apos; accuracy, the images will also be calibrated. Consequently, the samples will be placed in an oven (60\u0026deg;C for at least 72 hours) prior to weighing the dry mass. The SLA will be computed using the formula below:\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\" width=\"481\" height=\"41\"\u003e\u003c/p\u003e\n \u003cp\u003eTo measure the leaf dry matter content (LDMC), the rehydrated samples will be weighed for the water-saturated fresh mass, and the oven dried after to weigh the oven-dry mass. The formula for the LDMC content is as stated:\u003c/p\u003e\n \u003cp\u003e\u003cimg 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\" height=\"63\" width=\"503\"\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.3 Functional Diversity Indices\u003c/h2\u003e\n \u003cp\u003eIn order to ensure the avoidance of representation errors in the analysis, seven functional indices were utilized. The indices were mainly divided into three, namely functional richness, functional evenness, and functional divergence. The table below summarizes the indices used for functional diversity analysis.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFunctional diversity indices and descriptions.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFunctional diversity categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFunctional diversity Indices\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional richness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFunctional volume (FRic)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrait space volume occupied by species in the community (Villeg\u0026eacute;r et al., 2008).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional evenness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFunctional evenness (FEeve)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eevenness of abundance distribution in a functional trait space (Villeg\u0026eacute;r et al., 2008).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunctional divergence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFunctional divergence index (FDis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistribution of abundance within the volume of functional trait space occupied by species (Villeg\u0026eacute;r et al., 2008).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultidimensional divergence (FDiv)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaverage weighted distance between each species and the center of gravity in multidimensionalcharacter space, where the center of gravity is the center of gravity of all species (Lalibert\u0026eacute; \u0026amp; Legendre, \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRao\u0026rsquo;squadratic entropy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultidimensional functional dispersion used to measure diversity and difference within and between populations (Botta-Duk\u0026aacute;t, 2005).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003e2.4.4 Statistical analyses\u003c/h2\u003e\n \u003cp\u003eIn comparing the two forest communities based on functional indices, FD package was utilized (Laliberte \u0026amp; Legendre, 2010) in the form of a pairwise heatmap functional indices matrix. Species-specific leaf trait analyses were also visualized through boxplots. Consequently, to detect if there are correlations between the leaf traits measured, the default package in R was used in computing Pearson correlation and exhibited through pairwise scatterplot diagrams.\u003c/p\u003e\n \u003cp\u003eIn determining the similarities and differences of the plant functional traits of the common species between LPPWP and AFP, functional diversity indices were plotted in a Principal Coordinate Analysis (PCoA), exhibiting the functional measures in a multidimensional perspective using the mFD package (Magneville et al., 2021). Lastly, to determine the association of the common species with specific functional traits, a Principal component analysis (PCA) was synthesized. Using PCoA of functional indices from specific plant traits of common species in two urban forests assessed the dissimilarity patterns among species communities and explored the underlying factors shaping functional trait variation. Additionally, PCA is employed to identify dominant trait variation axes and uncover potential relationships between environmental factors and functional traits across urban forest ecosystems. All visualizations made for the analysis were synthesized using the GGplot package in R.\u003c/p\u003e\n \u003cp\u003eFor all the aforementioned analyses, indices calculations, statistical tests, and visualizations, R software was used, specifically the fundiversity (Functional Diversity) package (Greni\u0026eacute; \u0026amp; Gruson, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eUnderstanding the community structure and evaluating the changes in biodiversity in ecosystems constitute the fundamental task in the field of ecology (Schneider et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Aside from the biodiversity looking into the taxonomic and evolutionary measures, the use of functional traits has been a point of interest as physiological characteristics of organisms can reflect their responses to environmental conditions and their role in the ecosystem (Violle et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e; Liu et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Although the urban forests (AFP \u0026amp; LPPWP) were established with human intervention, looking into the ecological functions of the species would assess the efficiency and resilience as the last ecological frontiers in Metropolitan Manila. In this manner, whole plant and leaf traits were utilized as indicators of functional roles namely: (1) Plant height (PH), (2) Life Form (LF), (3) Leaf Size (LS), (4) Specific Leaf Area (SLA) and (5) Leaf Dry Matter Content (LDMC). A wide range of indices were employed in quantifying functional diversity for this study, namely, (1) Rao\u0026rsquo;s Quadratic Entropy (RaoQ), (2) Functional Dispersion (FDis), (3) Functional Divergence (FDiv), and (4) Functional Evenness (FEve).\u003c/p\u003e\n\u003cp\u003eIn comparison to taxonomic diversity indices that measure species according to the vegetation plots established, functional indices measure diversity in the context of multi-dimensional space representing the traits exhibited by the species within the community. Functional divergence (FDiv) measures the degree of niche differentiation, quantifying the degree of abundance of species in the community in terms of the boundaries of occupied functional space (Mason et al., \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). On the other hand, functional evenness (FEve) describes the degree to which the community is distributed in the niche space, evaluating how even distributed the functional traits are represented within the community to allow effective utilization of the resources available (Mason et al., \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e; Gioria et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The dispersion of species within the trait space is quantified using the functional dispersion (FDis) index, addressing how functionally dissimilar the species are from each other (Laliberte \u0026amp; Legendre, 2010). Lastly, an index considering both functional richness and divergence is Rao\u0026rsquo;s Quadratic Entropy (RaoQ), measuring functional diversity based on the abundance and dissimilarity of species traits within the community (Weigelt et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e; Botta-Dukat, \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTo assess if functional diversity indices were independent of each other based on the observations of Villeger et al. (2008), Pearson correlation analysis was conducted (See Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Although studies have observed that there was no correlation between functional diversity measures (e.g. Villeger et al., 2008; Mouchet et al., 2010; Pakeman, \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e), the results have shown correlations between the functional indices. In contrast to what was observed, FEve and FDiv showed a high positive correlation in both forest ecosystems (0.77; 0.76, respectively). This is in coherence with the observations by Morelli et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) wherein FEve and FDiv have positive correlation that is independently based on the types of environments, including forests, grasslands, and agricultural areas. Contrasting correlations were also observed between the two urban forests. In terms of the association with RaoQ and Fric, AFP exhibited a moderately positive correlation (0.73), while LPPWP has negligible correlation (0.23). This contrasting trend can also be observed between FDis and Fric (0.38; 0.17), FDiv and Fric (-0.48; 0.57), FEve and Fric (0.11; 0.87), FDis and FDiv (0.19; 0.49), and RaoQ and FDiv (-0.08, 0.58) (See Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). These associations between functional richness, evenness, dispersion, and divergence can change the strength and direction of correlation based on the varying environmental conditions (Morelli et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although AFP and LPPWP are both man-made forests, they differ in ecological setting and dominant vegetation. AFP is an urban forest located in the middle of the city along the Pasig River, while LPPWP is a coastal forest situated on the edge of the city along Manila Bay. Thus, abiotic factors can also influence the correlations of the functional indices, as plant physiological characteristics are highly shaped by environmental conditions, which remains to be further explored (Wu et al., 2019). However, in the case of FDis and RaoQ, both urban forests have shown high positive correlation (0.91; 0.99, respectively) as the two indices are closely related to each other as both assess the dispersion of species within the trait space and how functionally dissimilar species are from each other in terms of their functional traits (Laliberte \u0026amp; Legendre, 2010).\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003e3.2 Species-specific functional trait analysis\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eLeaf size, or the individual leaf laminal area is a functional trait serving as an indicator of species\u0026rsquo; environmental responses to light and temperature. LS is often a key element of plant functional ecology and is considered as the most accessible for measurements for wide array of species worldwide (Schrader et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition, LS affects the overall leaf temperature which in turn affects vital plant processes such as photosynthesis, transpiration, and respiration rate (Leigh et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Most species observed having high LS were compound leaves such \u003cem\u003eLeucaena leucophala, Pterocarpus indicus, Delonix regia\u003c/em\u003e (AFP), \u003cem\u003eAverrhoa bilimbi and Murray koenegi\u003c/em\u003e (LPPWP). The distinguished species with simple leaves to exhibit high relative LS was \u003cem\u003eTerminalia catappa\u003c/em\u003e common in both urban forests. Having larger LS is often correlated with higher efficiency in capturing sunlight under shaded canopies (Lusk et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e; Li \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although higher LS can be advantageous in photosynthetic abilities, species with large leaves also have trade-offs such as susceptibility to herbivory and higher within-leaf support cost (Niinemets et al., 2006). Species with smaller LS such as \u003cem\u003eRivina humilis, Murraya paniculata\u003c/em\u003e (for both urban forests), \u003cem\u003ePodocarpus macrophyllus\u003c/em\u003e (for AFP), \u003cem\u003ePithecellobium dulce\u003c/em\u003e, and \u003cem\u003eLumnitzera racemosa\u003c/em\u003e, are advantageous in regions with higher temperatures and light intensities as they can regulate leaf temperatures and avoid overheating (Niinemets \u0026amp; Kull, \u003cspan class=\"CitationRef\"\u003e1994\u003c/span\u003e; Meier \u0026amp; Leuschner, \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e; Tozer et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Aside from the environmental responses, leaf size also varies based on site-specific features such as water availability, soil fertility, and most especially, phylogenetic differences (Wolfe \u0026amp; Upchurch, \u003cspan class=\"CitationRef\"\u003e1987\u003c/span\u003e; Greenwood et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e; Peppe et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eSLA, or the area per unit dry mass, is a significant parameter in plant growth and canopy expansion. The functional trait can serve in the determination of leaf area to deploy in relation to the biomass produced (Kimball et al., \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e). In addition, SLA influences the total leaf area that is being affected by light use efficiency (LUE) and interception (Kumar et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). In the case of the two urban forests, there are similar species found to have similar impacts on its respective communities. \u003cem\u003eF.ulmifolia\u003c/em\u003e resulted in having relatively high SLA while \u003cem\u003eC.inophyllum\u003c/em\u003e exhibited lower relative SLA among both communities. Along with \u003cem\u003eF. ulmifolia\u003c/em\u003e, the species that showed high relative SLA were \u003cem\u003eD.regia, P. indicus, S.macrophylla, P. parviflora\u003c/em\u003e for AFP, and \u003cem\u003eS. diphyllum, G. sepium\u003c/em\u003e, and \u003cem\u003eR. humilis\u003c/em\u003e for LPPWP. Thus, these species were mainly correlated with having increased light capture capacity and relative growth rates. On the other hand, species such as \u003cem\u003eP.macrophyllus, G. arborea, M. indica\u003c/em\u003e (for AFP\u003cem\u003e), L. leucophala, L. racemosa, and T. catappa\u003c/em\u003e (for LPPWP) exhibited lower SLA, which indicates the species\u0026rsquo; strengthened ability in resource utilization and preservation of obtained resources in the environment (Delpiano et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xu et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). The variations of SLA in species can be determined by several factors, including the genetic variability of the species, environmental variability and responses causing differences in SLA (Wilson et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eLDMC or the ratio of dry mass to fresh mass of leaves serves as a significant variable in studying plant ecology as the trait is associated with the growth and survival of species (Li et al., \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e). Specifically, it is being utilized as an indicator of resource strategies such as conservation of resources (water retention), and rapid assimilation and growth trade-off (Wilson et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e; Garnier et al., \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e; Diaz et al., 2004; Liu \u0026amp; Guan, \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). Exhibited in Figure X are the species-specific LDMC observed in the two urban forests. In AFP, \u003cem\u003eG. arborea, M. indica, F. ulmifolia, and P. longifolia\u003c/em\u003e were among the species obtaining the higher ranges of LDMC. Additionally, \u003cem\u003eM. zapota, V. parvifolia, M. koenegi, and T. catappa\u003c/em\u003e have high LDMC in the forest composition of LPPWP. Based on the results, the species are involved in the efficient conservation of resources within their respective communities (Poorter \u0026amp; je Dong, 1999; Bao \u0026amp; Liu, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). Higher LDMC is also correlated with stronger water retention capacity of the leaves (Xu et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the other hand, species within the community have exhibited relatively lower LDMC in AFP (\u003cem\u003eD. regia, C. inophyllum, F. septica\u003c/em\u003e and \u003cem\u003eP. indicus\u003c/em\u003e) and LPPWP (\u003cem\u003eG. sepium, L. racemosa\u003c/em\u003e, \u003cem\u003eR. humilis\u003c/em\u003e, and \u003cem\u003eM. citrifolia)\u003c/em\u003e. Although these species have comparatively lower water retention and resource conservation efficiency, they are mainly involved in rapid biomass production (Li et al., \u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eTo determine the relationships of the leaf traits with each other (LS, SLA, and LDMC), pairwise correlation analysis was conducted. Although there are graphical associations that can be observed, there were no significant correlations among the traits assessed. In the analysis between LDMC and SLA, both forests (AFP \u0026amp; LPPWP) exhibited inverse but not significant relationships (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.03939, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.2058, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively). Similar observations were seen in the studies of Li et al. (\u003cspan class=\"CitationRef\"\u003e2005\u003c/span\u003e) and Dong et al. (\u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e), the SLA values were independent of the changes in LDMC. Although in a species-specific simulation by Zhang et al. (\u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) assessing a single grass species in a controlled environment, they have observed decrease in SLA with increasing LDMC as a physiological response. Similarly, there has been no significant correlation between LS and LDMC (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.009857, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0368, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively), as well as in SLA and LS (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0049, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0003, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, respectively). The lack of correlation in LS and SLA were also observed in previous comparative studies (Ackerly \u0026amp; Reich, \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e; Fonseca et al., \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ackerly et al., \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e), suggesting the independence of the two traits with each other, associated with varying environmental aspects and eco-physiological strategies. Although LS and SLA were found to change in parallel to each other, these traits represent different strategies in relation to water and nutrient availability (Mooney \u0026amp; Dunn, \u003cspan class=\"CitationRef\"\u003e1970\u003c/span\u003e; Parsons, \u003cspan class=\"CitationRef\"\u003e1976\u003c/span\u003e; Cunningham et al. \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e; Fonesca et al., 2000).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3 Functional diversity of common species among the urban forests\u003c/h2\u003e\n \u003cp\u003eExamining the functional traits of similar species across the two urban forests aids in determining the responses of the species, providing insights into the adaptability of the common species to the urban conditions. Additionally, focusing on similar species ensures consistency of comparison. They eliminate confounding factors, such as the unique species that have different functional traits. Lastly, the contribution of the common species can be evaluated in terms of their roles in the varying forest settings. Exhibited in Fig. 21 are the principal coordinates analyses (PCoA) of the functional richness, evenness, divergence, and dispersion of the common plant species from AFP and LPPWP.\u003c/p\u003e\n \u003cp\u003eThrough visualization and computation of the PCoA, the functional traits of the species were analyzed in a functional space (Gower, 1966). Figure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea shows the FRic, in this manner, the volume of the minimum convex hull representing the community, wherein the vertices of the hull were the species with comparably extreme functional values. Regarding the functional richness, the figure visualizes how much of the niche space is occupied by the species present in the given community considering multiple traits simultaneously (Schleuter et al., 2010; Legras et al., 2018).\u003c/p\u003e\n \u003cp\u003eIn the graphical representation through a multidimensional Euclidean trait space, an evident overlapping of traits was observed as the common species from the two urban forests have similarities in function in relation to their respective communities. However, the LPPWP community exhibited higher functional richness (Fric\u0026thinsp;=\u0026thinsp;0.649) in relation to AFP (0.571), meaning that the LPPWP community has demonstrated a wider range of ecological functions and roles and is described to be more resilient due to higher response diversity (Carturan et al., 2022). Consequently, LPPWP community has more diverse functions than that of the AFP community, exhibited through their FDiv values (FDiv: 0.972, 0.66; respectively).\u003c/p\u003e\n \u003cp\u003eOn the other hand, AFP community showed higher FEve than that of LPPWP, meaning that the ecological functions were more distributed among species (FEve:0.545, 0.737; respectively) (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eb). A potential factor for the higher functional evenness observed within the AFP community may be attributed to the phenomenon of functional redundancy. This phenomenon denotes the presence of multiple species fulfilling analogous ecological roles or functions within the ecosystem, thereby fostering a more even distribution across the functional space. Such redundancy is frequently associated with heightened functional stability, wherein the ecosystem exhibits resilience and maintains its essential functions even amidst environmental fluctuations (Jurburg \u0026amp; Salles, 2015).\u003c/p\u003e\n \u003cp\u003eIn terms of the dispersion of the functions (FDis), Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ed exhibits the average distance of species from the community centroid in a multidimensional trait space (Cordova- Tapia et a., 2017). This functional measure combines the regularity of the abundance distribution and the functional similarity of dominant species within the communities (Laliberte \u0026amp; Legendre, 2010). Although the two urban forests vary in terms of functional richness, evenness, and divergence, the dispersion of the traits was highly similar for AFP and LPPWP (FDis\u0026thinsp;=\u0026thinsp;0.394, 0.37, respectively). The presence of common species assessed suggests that these urban forests likely occupy similar ecological niches within the landscape, leading to comparable patterns of functional trait distribution among the species present. To further specify the specific functional roles that the species specialize in, Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e exhibits Principal Component Analysis (PCA) based on the functional traits present in species common between (a) AFP and (b) LPPWP.\u003c/p\u003e\n \u003cp\u003eIn the multivariate visualization of the species and their functional traits, the species functional dynamics of the community can be described, wherein the points that cluster together represent the species with similar ecological strategies or functional roles. The patterns in the distribution of these points undermines the community structure, niche differentiation, and even adaptation to certain environmental conditions. First, a functional trait that was exhibited as one of the leaf traits that best reflect the overall growth of the plant was SLA, which also plays a role in ecological process such as linking plant carbon and water cycle as the ratio depicts carbon gain in relation to water loss within the canopy (Pierce et al., 1994; Gunn et al., 1999; Cornelissen et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Cheng et al., 2016).\u003c/p\u003e\n \u003cp\u003eA common trend seen in both forests are shrub species \u003cem\u003eM. paniculata\u003c/em\u003e and \u003cem\u003eR. humilis\u003c/em\u003e and small arbor \u003cem\u003eF.ulmifolia\u003c/em\u003e were clustered in the axis of SLA. Interestingly, similar observation was found by Gong \u0026amp; Gao (2019), wherein shrubs exhibited relatively high SLA, in their studies\u0026rsquo; case, it was correlated to latitudinal gradients. In addition, as shrubs and small arbors are oftentimes shade-induced due to canopies of trees with greater plant height, Liu et al. (2016) observed that when plants are shaded, there is an increase in SLA. As high SLA is known to contribute to biomass homeostasis, this adaptation of shrubs might simply be a passive response to their environment. There are also other species that clustered towards SLA such as \u003cem\u003eA. indica\u003c/em\u003e (exclusively in LPPWP individuals), \u003cem\u003eL. leucophala\u003c/em\u003e (exclusively in LPPWP), and \u003cem\u003eV. parviflora\u003c/em\u003e (exclusively in AFP individuals), wherein the correlations were site-specific as the relationships were not similarly observed in both urban forests.\u003c/p\u003e\n \u003cp\u003eThe species\u0026rsquo; plant height serves as a key characteristic for species in terms of important functions for survival such as carbon storage and overall biomass (Conti \u0026amp; Diaz, 2012; Ruiz-Jaen \u0026amp; Potvin, 2011; Mensah et al., 2016). Additionally, this functional trait can dictate the species\u0026rsquo; adaptation when competing for light resources and can be correlated with resource availability at competitive environments (Westoby et al., \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e). The mesophanerophytes \u003cem\u003eL.leucophala, T.catappa, A. indica\u003c/em\u003e) and megaphanerophyte (\u003cem\u003eV. parviflora\u003c/em\u003e) in both the urban forest were clustered in the PH axis, indicating that these species mainly contribute to the functional space mainly due to their height. This trait is advantageous as being taller than adjacent individuals in the forest ecosystem equates to greater access to light for photosynthetic processes. However, having higher plant height has numerous tradeoffs such as the expense of energy for structural support (stems and vasculature), and nutrient transport. Individuals from the species \u003cem\u003eT. catappa\u003c/em\u003e in LPPWP, however, was not directly associated with PH, which can be due to the interspecific competition as the forest is dominated by other tree species. Additionally, the \u003cem\u003eT. catappa\u003c/em\u003e observed nearby coasts were shorter in PH and has disease symptoms such as chlorosis in most leaves, indicating growth limiting factors such as nutrient deficiency and herbivory (Hershey, 2003; Schowalter, 2006). Additionally, the species that are advantageous in terms of PH and its functions, such as C. inophyllum, L leucophala, and T catappa, were also clustered near the axis for LS, which also a competitive advantage in light acquisition, resource utilization, and even carbon sequestration. In a general sense, trees have larger leaves in comparison to small arbors and shrubs, but the taxonomic patterning of the species is a major factor as it undermines evolutionary adaptation (Wright et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn terms of LDMC, larger woody plants tend to exhibit higher values of LDMC as these species invest nutrients for tissue construction and maintenance\u0026mdash;offering resilience in adapting to unfavorable environmental conditions (Ricklefs \u0026amp; Lathan, 1992; Zhou et al., 2020; Wang et al., 2020; An et al., 2021). Based on the PCA, there are variations in terms of species that are related to LDMC. In LPPWP, \u003cem\u003eV. parviflora, C. inophyllum, T. catappa, F. ulmifolia\u003c/em\u003e shown to favor the LDMC axis. On the other hand, only \u003cem\u003eA. indica\u003c/em\u003e was located near the LDMC axis in AFP. The leaves of these species exhibiting a correlation to LDMC can indicate longer leaf span, relatively tough structure, and high resistance to physical hazards such as herbivory and wind. While the majority of species did not demonstrate a strong correlation with LDMC, those exhibiting relatively low LDMC values were found to be linked with productive yet highly disturbed environments (Perez- Harguindeguy et al, 2013). This observation aligns with the context of the assessed forests situated in harsh environments characterized by significant human disturbances.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAlthough species trends have exhibited similar functions in the two urban forests, there is still variability wherein species function or adapt differently in the community based on the utilized whole-plant and leaf trait indicators. These variations, or lack thereof, can be undermined by various ecological phenomena, namely (i) phenotypic plasticity, (ii) habitat filtering, and (iii) ecological differentiation, leading to variation in community-based functional diversity.\u003c/p\u003e \u003cp\u003eThe variations in functional traits can result from a single genotype producing different phenotypic characteristics as a response to environmental conditions, otherwise known as phenotypic plasticity\u0026mdash;allowing species to adjust physiologically and morphologically to optimize and survive under different circumstances. In terms of leaf traits, phenotypic plasticity can be exhibited through heterophylly, which occurs as leaves are altered due to varying light intensity, water availability, or even the ambient temperature of its habitat (Goliber \u0026amp; Feldman, 1990; Sicard et al., 2014; Nakayama et al., 2017). The alterations in these functional traits are generally vital for plants in order to adapt to their respective environments through modification morphology, indicating changes in the species' biomass allocation (Xie et al., 2015; Rolhauser \u0026amp; Pucheta, 2016; Freschet et al., 2018; Liu et al., 2022). However, these changes in the vegetative traits of plant species can be adaptive, neutral, or even maladaptive, as observed in studies that conducted field manipulation of abiotic factors (Welker et al., 1993; Ptratt \u0026amp; Mooney, 2013; Song et al., 2016; Navarro et al., 2022).\u003c/p\u003e \u003cp\u003eHabitat filtering can also serve as drivers of these functional trait variations and similarities among the species assessed, as environmental conditions, interspecific interactions, or disturbance regimes selectively favor phenotypic traits, leading to preferential establishment of even persistence of individuals with specific functional traits. As a result, spatial segregation can occur within the functional space. The constriction of the niche volume in the form of habitat filtering is a widespread process observed, serving as a driving pattering of functional niche occupancy across different plant communities, in this case, the two urban forests. As observed in the PCA graph, some species cluster in specific functional traits, which is in coherence with the observations by Li et al. (2017), wherein the coexisting species tend to be functionally similar rather than functionally specialized. Additionally, the variations in the functions of the similar species across the two urban forest communities can be affected by the surrounding landscape, as the placement of the habitats is found to affect the functional diversity of plant species, similar to the observations done by Czortek \u0026amp; Pielech (2020) in urban parks. Based on their assessment of community-level coexistence patterns, plant species can be affected by settlements and the level of fragmentation of the urban forests, which decreases functional dispersion. These functional similarities among the plant communities can also indicate resilience so that if one species is removed from the community, it can be buffered by functionally alike species. However, in a long-term perspective, the lowering range of functional diversity and its corresponding plant strategies would be a limiting factor to the adaptation and survival of the community to future changes in the environment (Diaz \u0026amp; Cabido, 2001; Brica et al., 2021). Thus, the conservation of urban forest parks should prioritize maintaining a wider variety of pioneer habitat conditions, yielding a more functionally diverse and resilient community (Czortek \u0026amp; Pielech, 2020).\u003c/p\u003e \u003cp\u003eLastly, ecological differentiation can result in variation in community-based functional diversity due to each species' differing adaptations and strategies to exploit niche opportunities and respond to environmental gradients. This variation can enhance or restrict the range of functional traits present within the community, thereby increasing or decreasing its capacity to fulfill diverse ecological roles and functions. Although similar species can occur in both urban forests, intraspecific variations were detected, as some vary based on their functional characteristics. This claim can be supported by the study conducted by Albert et al. (2010), wherein they quantified intraspecific functional trait variability from 16 plant species subjected to different climatic gradients in an alpine valley and observed large variability of traits within species along with significant discrepancies between functional traits and species\u0026mdash;greatly affected by radiation and temperature. While the current study has not investigated the influence of climatic factors and environmental gradients on urban forest ecosystems, considerable potential exists for further exploration in this area. Understanding how climatic variations and environmental gradients shape the structure and function of urban forests can provide valuable insights into their ecological dynamics and resilience.\u003c/p\u003e \u003cp\u003eAs challenges in sustaining biodiversity continuously arise along with environmental changes, sustained, synoptic, and comparative quantitative forms of measurements are needed (Pacheco-Labrador et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Assessing functional diversity can help evaluate how ecosystems cope with the changing environment and the organisms' resilience in continuing their services to the community (Jactel et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Espelta et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, studying plant functional traits also substantially contributes to strengthening the links between community structure and ecosystem functioning, aside from considering species richness alone (Diaz \u0026amp; Cabido, 2001). Similar to other natural ecosystems, urban forests' ecosystem functioning also depends on the species composition, as having a species- and trait-diverse community tends to have increased stability, which supports the provisioning of ecosystem services (Yachi \u0026amp; Loreau, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Balvanera et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Wood \u0026amp; Dupras, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). An increased number of functions of diverse species can provide ecological insurance in coping with disturbances and change their responses to stress depending on the community the species belongs to (Messier et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Espelta et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thus, studies have suggested that increasing the diversity of plant species within a forest can improve the functioning rates of the ecosystem through trait complementarity\u0026mdash;a phenomenon wherein the combined outcomes of varying traits interact together, resulting in increased ecosystem process rates (Loreau \u0026amp; Hector, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). However, the ecosystem resilience of forests is not just constricted to the effects of species composition. However, it also encompasses several factors, such as genetic diversity, forest management history, forest size, and even the overall condition of the surrounding landscape (Peterson et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Thompson et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Walker et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Thus, looking into the overall condition of the ecosystem, including the abiotic and anthropogenic factors, can undermine further information regarding the metabolism and behavior of species comprising urban forests.\u003c/p\u003e \u003cp\u003eThis pioneering research on forest functional diversity in the Metropolitan Region of the Philippines study not only underscores the importance of the preservation and enhancement of green spaces within urban environments but also emphasizes the need for more holistic approaches that consider the ecological factors in urban planning and integration of urban green spaces (see review of Olfato-Parojinog \u0026amp; Dagamac, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Through further assessing the ecological aspect of these last ecological frontiers of the megacity, we can contribute valuable knowledge to the ongoing discourse on sustainable urban development, providing a foundation for more informed decision-making and policy formulation aimed at fostering resilient and livable cities in the Philippines and beyond.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.O.P. would like to thank the Department of Science and Technology- Science Education Institute (DOST-SEI) Accelerated Science and Technology Human Resource Development Program - National Science Consortium (ASTHRDP- NSC) for the scholarship and funding the research. Sincere thanks are extended to the City of Manila, Parks Development Office, headed by Engr. Gideon Navarro and Forester Gerardo S. Montecillo, for approving the research at Arroceros Forest Park. AOP also expresses gratitude to the Department of Environment and Natural Resources \u0026ndash; National Capital Region (DENR-NCR), Las Pi\u0026ntilde;as Para\u0026ntilde;aque Wetland Park, led by Sir Christopher C. Villarin and Sir Diego Montesclaros, for their support during the field assessments at the protected area.\u003c/p\u003e\n\u003cp\u003eP.C.E.R, J.M.B., C.J.R. would also like to thank DOST-SEI and ASTHRDP-NSC for master\u0026rsquo;s degree scholarship. The authors are grateful to the three manuscript reviewers for the comments and suggestions that improved this manuscript and for the technical assistance extended by the authors\u0026rsquo; family and friends.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the conception and design of the study. The initial draft of the manuscript was prepared by Anne Olfato-Parojinog, with all co-authors\u0026mdash;Christian Elmarc Ocenar-Bautista, Paul Cervin Evangelista-Rivera, Jean-Matthew Bate, Christon Jairus Racoma, Jayson G. Chavez, and Nikki Heherson A. Dagamac\u0026mdash;providing critical feedback and revisions to previous versions. All authors have reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Department of Science and Technology - Science Education Institute (DOST-SEI) through the Accelerated Science and Technology Human Resource Development Program (ASTHRDP), under the scholarship grant of Olfato-Parojinog.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAckerly, D. D., \u0026amp; Reich, P. B. (1999). Convergence and correlations among leaf size and function in seed plants: a comparative test using independent contrasts. \u003cem\u003eAmerican Journal of Botany\u003c/em\u003e, \u003cem\u003e86\u003c/em\u003e(9), 1272\u0026ndash;1281. https://doi.org/10.2307/2656775\u003c/li\u003e\n\u003cli\u003eAckerly, D., Knight, C., Weiss, S., Barton, K., \u0026amp; Starmer, K. (2002). 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Growth and physiological responses of Carex schmidtii to water-level fluctuation. \u003cem\u003eHydrobiologia\u003c/em\u003e, \u003cem\u003e847\u003c/em\u003e(3), 967\u0026ndash;981. https://doi.org/10.1007/s10750-019-04159-z\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"urban-ecosystems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ueco","sideBox":"Learn more about [Urban Ecosystems](https://www.springer.com/journal/11252)","snPcode":"11252","submissionUrl":"https://submission.nature.com/new-submission/11252/3","title":"Urban Ecosystems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ecological dynamics, Ecosystem resilience, Functional diversity, Urban forests, Urban green spaces","lastPublishedDoi":"10.21203/rs.3.rs-6281039/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6281039/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrban green spaces (UGS) play a critical role in enhancing biodiversity, mitigating environmental stressors, and promoting ecosystem resilience within highly urbanized areas. However, rapid urbanization in in megacities such as the Metropolitan Manila has led to the loss and fragmentation of these ecological frontiers, highlighting the urgent need to assess their ecological functions. This study investigates the plant functional diversity and ecological dynamics of two key urban forests in Metro Manila—Arroceros Forest Park and Las Piñas-Parañaque Wetland Park—by analyzing whole-plant and leaf trait-specific indicators to evaluate ecosystem functions and services. Functional diversity indices were employed to identify relationships among plant communities and assess how species' functional traits influence ecosystem stability. Results indicate that while species in both urban forests exhibit similar functions, variations in functional traits are driven by phenotypic plasticity, habitat filtering, and ecological differentiation. These factors influence community-based functional diversity, affecting species adaptability and resilience. The study highlights the importance of maintaining high functional diversity to support ecosystem services, emphasizing the role of urban forests in mitigating environmental challenges in rapidly developing cities. Findings from this research provide valuable insights for urban conservation strategies and reinforce the necessity of integrating functional diversity in urban ecological planning to enhance ecosystem resilience and sustainability but opens more possibilities in overall assessing the ecosystem along with abiotic factors and interactions with other faunal and microbial species that could affect its ecological dynamics.\u003c/p\u003e","manuscriptTitle":"Exploring Plant Functional Diversity and Ecological Dynamics in Urban Forests: Insights from Metropolitan Manila","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-25 10:34:59","doi":"10.21203/rs.3.rs-6281039/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-09T05:32:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-09T04:37:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-18T19:54:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218220090766653580511359709513029473223","date":"2025-04-26T10:16:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"250295323820234933331509520766741825037","date":"2025-04-24T22:18:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69514366642588175106563806460486255508","date":"2025-04-19T23:01:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-15T03:03:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-03T01:48:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-01T12:01:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Urban Ecosystems","date":"2025-03-22T02:39:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"urban-ecosystems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ueco","sideBox":"Learn more about [Urban Ecosystems](https://www.springer.com/journal/11252)","snPcode":"11252","submissionUrl":"https://submission.nature.com/new-submission/11252/3","title":"Urban Ecosystems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"69c0c803-c45b-4a9a-bcd3-0d6fb6925abc","owner":[],"postedDate":"April 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T16:08:20+00:00","versionOfRecord":{"articleIdentity":"rs-6281039","link":"https://doi.org/10.1007/s11252-025-01804-5","journal":{"identity":"urban-ecosystems","isVorOnly":false,"title":"Urban Ecosystems"},"publishedOn":"2025-09-30 15:58:17","publishedOnDateReadable":"September 30th, 2025"},"versionCreatedAt":"2025-04-25 10:34:59","video":"","vorDoi":"10.1007/s11252-025-01804-5","vorDoiUrl":"https://doi.org/10.1007/s11252-025-01804-5","workflowStages":[]},"version":"v1","identity":"rs-6281039","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6281039","identity":"rs-6281039","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}