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SPECIES DIVERSITY IN TROPICAL DRY FORESTS OF ECUADOR:

HOW EFFECTIVE ARE REGENERATED ECOSYSTEMS?

Grover A. García-Saltos

Maestría en Ingeniería Agrícola con mención en Agroecología y Cambio Climático

Facultad de Posgrado. Universidad Técnica de Manabí. Portoviejo, Ecuador

ggarcia0360@utm.edu.ec

https://orcid.org/0000-0002-9924-1415

Ezequiel Zamora-Ledezma

Laboratory of Agroecosystems Functioning and Climate Change – FAGROCLIM.

Department of Agriculture Science, Faculty of Agriculture Engineering

Universidad Técnica de Manabí. Santa Ana, Lodana, Ecuador

ezequiel.zamora@utm.edu.ec

https://orcid.org/0000-0002-5315-2708

Juan M. Moreira-Castro

Jardín Botánico. Universidad Técnica de Manabí. Vía Portoviejo-Crucita,

Portoviejo, Ecuador

juan.moreira@utm.edu.ec

https://orcid.org/0009-0005-3558-7272

Karime Montes-Escobar

Departamento de Matemáticas y Estadística. Facultad de Ciencias Básicas

Universidad Técnica de Manabí, Portoviejo, Ecuador

karime.montes@utm.edu.ec

https://orcid.org/0000-0002-9555-0392

Josselyn Muentes-Vélez

Carrera de Ingeniería Ambiental. Facultad de Ciencias Naturales y de la

Agricultura. Universidad Estatal del Sur de Manabí. Jipijapa, Ecuador

josellyn.muentes@unesum.edu.ec

https://orcid.org/0000-0002-5362-8008

Carlos A. Salas-Macias

Laboratory of Agroecosystems Functioning and Climate Change - FAGROCLIM

Departamento de Ciencias Agronómicas. Facultad de Ingeniería Agronómica

Universidad Técnica de Manabí. Lodana, Ecuador

carlos.salas@utm.edu.ec

https://orcid.org/0000-0002-1641-1571

Autor para correspondencia: ezequiel.zamora@utm.edu.ec

Recibido: 17/03/2025 Aceptado: 30/06/2025 Publicado: 07/07/2025

RESUMEN

Los bosques secos tropicales son ecosistemas altamente vulnerables a la

degradación, cuya restauración requiere estrategias efectivas de conservación.

Este estudio evaluó la biodiversidad de un bosque seco tropical en estado natural

y un bosque en regeneración asistida, comparando riqueza de especies, equidad y

estructura comunitaria. Se establecieron cuatro parcelas de muestreo, de 20 x 50

metros cada una, en ambos ecosistemas y se analizaron índices de diversidad

utilizando iNEXT.4steps y el software PAST. Los resultados muestran que el bosque

natural presenta una mayor riqueza de especies (54) en comparación con el bosque

regenerado (28), así como una distribución más equitativa de las abundancias. La

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dominancia de especies pioneras en el bosque regenerado indica que aún se

encuentra en una etapa temprana de sucesión ecológica. La extrapolación de

diversidad sugiere que el ecosistema restaurado difícilmente alcanzará la

complejidad del bosque natural en el mediano plazo. Estos hallazgos resaltan la

importancia de estrategias de restauración complementarias, como la introducción

de especies tardío-sucesionales, para acelerar la convergencia estructural y

funcional. El estudio subraya la necesidad de monitoreos a largo plazo para evaluar

la efectividad de la regeneración asistida en bosques secos tropicales y sugiere que

enfoques de restauración más integrales podrían mejorar la resiliencia y

estabilidad de estos ecosistemas.

Palabras clave: Bosque seco tropical, regeneración asistida, biodiversidad,

sucesión ecológica, restauración ecológica

DIVERSIDAD DE ESPECIES EN BOSQUES SECOS TROPICALES

DEL ECUADOR: ¿QUÉ TAN EFECTIVOS SON LOS

ECOSISTEMAS REGENERADOS?

ABSTRACT

Tropical dry forests are ecosystems highly vulnerable to degradation, whose

restoration requires effective conservation strategies. This study assessed the

biodiversity of a tropical dry forest in its natural state and a forest under assisted

regeneration, comparing species richness, equity, and community structure. Four

sample plots of 20 x 50 meters each were established in ecosystems, and diversity

indices were analyzed using iNEXT.4steps and PAST software. The results show that

the natural forest has a higher species richness (54) than the regenerated forest

(28) and a more even abundance distribution. The predominance of fast-growing,

light-demanding pioneer species in the regenerating forest indicates an early-to-

mid successional stage, while the balanced distribution of functional groups in the

natural forest reflects greater ecological complexity and resilience. These findings

highlight the importance of complementary restoration strategies. The study

underscores the need for long-term monitoring to assess the effectiveness of

assisted regeneration in tropical dry forests. More holistic restoration approaches

could improve the resilience and stability of these ecosystems.

Keywords: Tropical dry forest, assisted regeneration, biodiversity, ecological

succession, ecological restoration.

1. INTRODUCTION

Tropical dry forests harbor high biological diversity and play a crucial role in

ecological stability (Miles et al., 2006; Murphy & Lugo, 2012). However, these

ecosystems have experienced accelerated degradation due to human activities

such as agricultural expansion, deforestation, and the effects of climate change

(Blackie et al., 2014). Faced with this problem, assisted regeneration has emerged

as a key strategy for ecological restoration, facilitating the recovery of biodiversity

and ecosystem functionality through interventions such as planting native species,

controlling invasive species, and protecting recovering areas. (Oluwajuwon et al.,

2024; Holl & Aide, 2011; Chazdon et al., 2020)

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Knowledge about the differences in biodiversity between natural dry forests and

those undergoing assisted regeneration remains limited (Mesa-Sierra et al., 2024;

Oliveira et al., 2024; Reid et al., 2015). In particular, few studies evaluate the

effectiveness of assisted regeneration over the medium term, which hinders

understanding the ecological processes that determine the recovery of these

ecosystems (Elliott et al., 2013). Assessing biodiversity in this context allows for

identifying patterns of convergence or divergence in the composition and structure

of biological communities compared to natural forests, providing fundamental

information for improving restoration strategies. (Letcher & Chazdon, 2009; Meli

et al., 2017)

Likewise, understanding these differences is essential for designing effective

conservation and restoration strategies to optimize natural area management. This

improved management takes on greater relevance, as the composition and

structure of biological communities directly influence the capacity of ecosystems

to provide services such as hydrological cycle regulation, carbon sequestration,

pollination, and erosion control (Poorter et al., 2016). Thus, the restoration of

these services represents a tangible benefit to local communities by improving

their food security, access to water, and sustainable economic opportunities (Kumi

et al., 2024; Gao et al., 2024; Aryee et al., 2024; Rath et al., 2024). Additionally,

it strengthens the socioecological resilience of these communities to extreme

climate events. (Cantarello et al., 2024; Mahjoubi et al., 2022; Hong & Chongjian,

2024)

The main objective of this study is to compare biodiversity indicators between a

natural dry forest and one undergoing assisted regeneration. To this end, species

richness and abundance were assessed in both ecosystems and species composition

and distribution within the community. Furthermore, differences in dominance,

evenness, and functional diversity in forest structure were analyzed to determine

the recovery status of the regenerated ecosystem relative to the natural forest. It

is hypothesized that the regenerated forest will have lower species richness and

composition than the natural dry forest but with a tendency toward convergence

in structure and ecological functionality.

2. MATERIALS AND METHODS

2.1. Study area

The study was conducted in two nature reserves located in northwestern Ecuador:

the Lalo Loor Dry Forest Reserve, which houses the dry forest plots (TDF), and the

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Jama-Coaque Nature Reserve, where the forest regenerated 10 years ago is

located (ESF). The Jama-Coaque Reserve, managed by the nonprofit Third

Millennium Alliance (TMA), protects 850 hectares of forest in the coastal mountain

range of the same name and is part of the Tumbes-Chocó-Magdalena biodiversity

hotspot. Located less than 8 kilometers from the Pacific Ocean, it presents an

altitudinal gradient in which the tropical moist evergreen forest of the lowlands

transforms into cloud forest at higher altitudes. Its climate is tropical monsoon,

with a rainy season from December to May, recording between 1,000 and 1,500

mm of annual precipitation, while the cloud forest zone can exceed 2,000 mm.

The Lalo Loor Dry Forest Reserve is located less than 2 kilometers west of the

Jama-Coaque Reserve, to which it is connected via the Three Forest Trail

ecotourism trail. This reserve protects 201 hectares of lowland forest and is

managed by its owner and the Ceiba Foundation for Tropical Conservation. Its

altitude ranges from 41 to 414 meters above sea level, less than 1.4 kilometers

from the Pacific Ocean. The lowland areas are dominated by tropical dry deciduous

forests, transforming into semi-deciduous forests with increasing altitude. The

reserve's climate is tropical monsoon, with an average annual rainfall of 1,000 mm

or less. The field sampling was conducted in October and November of 2022.

2.2. Sampling Design

Four sampling plots were established for each vegetation type to capture the

structural and compositional variability of the studied ecosystems. Each plot was

20 x 50 meters in size. Within these plots, all individuals of tree species with a

diameter at breast height (DBH) equal to or greater than 5 cm were recorded. The

location of the plots was randomly determined within each forest, ensuring a

representative spatial distribution that would capture the environmental and

ecological heterogeneity present in both ecosystems. Additionally, the plots were

georeferenced using a high-precision GPS to facilitate their location in future

monitoring.

2.3. Species Identification

Each species was identified with the support of experts from the Botanical Garden

of the Technical University of Manabí, who provided specialized taxonomic advice.

The initial identification was made in situ, based on key morphological

characteristics such as the shape of the leaves, bark, flowers, and fruits. To ensure

the accuracy of the determinations, records were cross-referenced with

recognized international taxonomic databases, such as The World Flora Online

(WFO), the International Plant Names Index (IPNI), and Tropicos (Missouri Botanical

257

Garden). In cases where identification could not be confirmed in the field due to

the lack of reproductive structures or similarity between species, botanical

samples (leaves, flowers, or fruits) were collected following standardized

protocols. These samples were pressed, dried, and transported to the laboratory

for detailed analysis under controlled conditions using specialized taxonomic keys

and comparisons with herbarium specimens.

2.4. Biodiversity Analysis

To comprehensively assess biological diversity, the Shannon (H'), Simpson

dominance (D), and Pielou evenness (J) indices were calculated using PAST version

5.1 software (Hammer et al., 2001). These indices allowed for the analysis of

different dimensions of biodiversity: species richness, defined as the total number

of species recorded in the community; evenness, which measures how evenly

individuals are distributed among species; and dominance, which indicates the

degree to which one or a few species predominate in abundance within the

ecosystem (Table 1).

Table 1. Indices and equations used to estimate biodiversity at each study site.

Index

Equation

Description

Abr.

Shannon

  















Measures the unpredictability in

identifying a randomly chosen

individual's species. It is

particularly responsive to

changes in the abundance of

uncommon species.

H’

Simpson











󰇛



󰇜





󰇛 󰇜

Assesses the likelihood that two

randomly selected individuals

belong to the same species. It is

particularly sensitive to changes

in the abundance of common

species.

Pielou

 



󰇛󰇜

The equivalence among species

in a community

Source: Shannon 1948, Simpson 1949, Pielou 1966.

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Additionally, to ensure a more accurate and representative assessment of

biodiversity, the iNEXT.4steps software (Chao & Hu, 2023; Chao et al., 2020) was

used. This tool is based on Hill numbers and integrates a four-step approach to

biological diversity analysis.

This software allowed for estimating sample completeness, assessing whether the

sampling effort was sufficient to capture the true diversity of the analyzed system.

Furthermore, it facilitated the interpolation and extrapolation of observed

diversity, allowing for standardized comparisons between the studied ecosystems,

even in situations where sample size or sampling effort varied between sites.

3. RESULTS AND DISCUSSIONS

A total of 72 species were recorded, comprising 39 families and 63 genera; 54 of

these were found in the natural forest and 28 in the regenerated forest (Table 2).

The observed richness indicates that the natural ecosystem hosts a greater

diversity of tree species, suggesting that, despite restoration efforts, the

regenerated forest assemblage still differs significantly from the reference

ecosystem.

Table 2. Species and abundance information recorded at each of the sampling sites

Species

Family

Abundance

ESF

TDF

Acnistus arborescens (L.) Schltdl.

Solanaceae

Agonandra silvatica Ducke

Opiliaceae

Alseis eggersii Standl.

Rubiaceae

Ambelania occidentalis Zarucchi

Apocynaceae

Annona manabiensis Saff. ex R.E. Fr.

Annonaceae

Arbutus unedo L.

Ericaceae

Baccharis latifolia (Ruiz & Pav.) Pers.

Asteraceae

Bauhinia aculeata L.

Fabaceae

Brosimum alicastrum Sw.

Moraceae

Brownea multijuga Britton & Killip

Fabaceae

Caesalpinia glabrata Kunth

Fabaceae

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Calophyllum brasiliense Cambess.

Calophyllaceae

Calycolpus surinamensis McVaugh

Myrtaceae

Carapa grandiflora Sprague

Meliaceae

Caryocar glabrum (Aubl.) Pers.

Caryocaraceae

Cassia moschata Kunth

Fabaceae

Castilla elastica Sessé ex Cerv.

Moraceae

Celtis iguanaea (Jacq.) Sarg.

Cannabaceae

Centrolobium ochroxylum Rose ex Rudd

Fabaceae

Chromolucuma baehniana Monach.

Sapotaceae

Chrysochlamys dependens Planch. & Triana

Clusiaceae

Clusia stenophylla Standl.

Clusiaceae

Cochlospermum vitifolium (Willd.) Spreng.

Bixaceae

Cordia alliodora (Ruiz & Pav.) Oken

Cordiaceae

Cordia hebeclada I.M. Johnst.

Cordiaceae

Cordia macrantha Chodat

Cordiaceae

Croton eggersii Pax

Euphorbiaceae

Cupania vernalis Cambess.

Sapindaceae

Faramea occidentalis (L.) A. Rich.

Rubiaceae

Ficus insipida Willd.

Moraceae

Ficus obtusifolia Kunth

Moraceae

Ficus trigonata L.

Moraceae

Grias peruviana Miers

Lecythidaceae

Guazuma ulmifolia Lam.

Malvaceae

Guettarda acreana K. Krause

Rubiaceae

Humiriastrum procerum (Little) Cuatrec.

Humiriaceae

Inga chocoensis Killip ex T.S. Elias

Fabaceae

Inga jaunechensis A.H. Gentry

Fabaceae

Inga sapindoides Willd.

Fabaceae

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Ladenbergia pavonii (Lamb.) Standl.

Rubiaceae

Leucaena trichodes (Jacq.) Benth.

Fabaceae

Machaerium millei Standl.

Fabaceae

Malouetia albiflora Miq.

Apocynaceae

Mora oleifera (Triana ex Hemsl.) Ducke

Fabaceae

Myrcia fallax (Rich.) DC.

Myrtaceae

Nectandra obtusata Rohwer

Lauraceae

Neoptychocarpus chocoensis A.H. Gentry & Forero

Salicaceae

Phyllanthus juglandifolius Willd.

Phyllanthaceae

Piper corrugatum Kuntze

Piperaceae

Piper eriopodon (Miq.) C. DC.

Piperaceae

Pisonia aculeata L.

Nyctaginaceae

Pisonia floribunda Hook. f.

Nyctaginaceae

Pseudobombax millei (Standl.) A. Robyns

Malvaceae

Pseudolmedia eggersii Standl.

Moraceae

Pseudosamanea guachapele (Kunth) Harms

Fabaceae

Psidium guajava L.

Myrtaceae

Rauvolfia littoralis Rusby

Apocynaceae

Siparuna muricata (Ruiz & Pav.) A. DC.

iparunaceae

Spondias mombin L.

Anacardiaceae

Stryphnodendron porcatum D.A. Neill & Occhioni f.

Fabaceae

Stryphnodendron pulcherrimum (Willd.) Hochr.

Fabaceae

Swartzia polita (R.S. Cowan) Torke

Fabaceae

Tabebuia sp.

Bignoniaceae

Tapura angulata Little

Dichapetalaceae

Trichillia sp.

Meliaceae

Triplaris cumingiana Fisch. & C.A. Mey.

Polygonaceae

Turpinia paniculata Vent.

Staphyleaceae

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Vismia baccifera (L.) Triana & Planch.

Hypericaceae

Vitex gigantea Kunth

Lamiaceae

Vochysia guatemalensis Donn. Sm.

Vochysiaceae

Ximenia americana L.

Ximeniaceae

Zanthoxylum sp.

Rutaceae

TDF = Tropical dry forest, ESF = Early successional forest

The results of the calculated diversity indices are shown in Table 3. The Shannon

index (H') showed higher values in the natural forest (H' = 3.25) compared to the

regenerated forest (H' = 2.39), indicating higher species diversity and a more

equitable distribution of abundances in the uninterrupted ecosystem.

Simpson's dominance (D) was higher in the regenerated forest (D = 0.1433),

suggesting that some species dominate the community. In comparison, in the

natural forest (D = 0.0639) the dominance was lower, reflecting a more diverse

and equitable community. These results agree with previous studies indicating that

regenerating forests may present a more homogeneous community structure in

their first decades of recovery. (Arroyo-Rodríguez et al., 2017)

Table 3. Diversity indices calculated for each sampling site

ESF

TDF

Taxa_S

Individuals

392

404

Dominance_D

0,1433

0,0639

Shannon_H

2,391

3,25

Equitability_J

0,7072

0,7982

TDF = Tropical dry forest, ESF = Early successional forest

Pielou's evenness (J) was higher in the natural forest (J = 0.7982) than in the

regenerated forest (J = 0.7072), indicating that species distribution in the restored

ecosystem is less even. This could be because certain pioneer species dominate

regeneration in the early stages of the successional process, while evenness

increases as the ecosystem matures. (Ma et al., 2024)

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The results of the sample completeness analysis with iNEXT.4steps showed a

sampling coverage of 0.982 in the regenerated forest and 0.958 in the natural

forest. The sample completeness profile (Figure 1a) showed that the proportion of

diversity captured varied according to the q order. For q = 0 (species richness),

completeness was lower, suggesting that not all species, especially rare ones, were

detected.

Figure 1. Biodiversity analysis using iNEXT.4steps. a) Sample completeness profile.

b) Size-based rarefaction and extrapolation curves. c) Asymptotic and empirical

diversity profiles. d) Coverage-based rarefaction and extrapolation curves. e)

Evenness profiles. TDF = Tropical dry forest, ESF = Early successional forest

This finding is consistent with previous studies that highlight the difficulty of

sampling rare species in tropical ecosystems, where environmental heterogeneity

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and low density of individuals can limit their detection. (Chao et al., 2020; Hortal

et al., 2015)

On the other hand, for q = 1 (Shannon diversity) and q = 2 (Simpson diversity),

completeness was high, indicating that the most abundant or frequent species

were well represented in the sample. This reflects that, although species richness

may be underestimated, the functional and structural diversity of the ecosystem,

based on dominant species, is adequately captured (Chao & Jost, 2015).

Size-based rarefaction and extrapolation curves (Figure 1b) confirmed these

findings. For q = 0, the curve did not reach a plateau, suggesting that species

richness was not fully captured, a typical result in biodiversity studies where

sampling effort is limited (Gotelli & Colwell, 2011). In contrast, the curves

stabilized for q = 1 and 2, reflecting a reasonable Shannon and Simpson diversity

estimate. This indicates that the most common species contribute significantly to

biomass and ecosystem processes and are well represented in the sample (Chao et

al., 2014). Furthermore, asymptotic and empirical diversity profiles (Figure 1c)

showed that, although species richness could be underestimated, diversity

estimates for higher orders were accurate. This fact highlights the importance of

using approaches that consider multiple dimensions of diversity, such as Hill numbers, to

obtain a more complete view of community structure (Chao et al., 2020).

Coverage-based rarefaction and extrapolation curves (Figure 1d) allowed for

standardized comparisons between samples, ensuring that differences in sampling

effort did not bias the results. This approach is instrumental in comparative

studies, where sampling effort can vary significantly between sites (Chao & Jost,

2012). Finally, the evenness profiles (Figure 1e) indicated a relatively balanced

distribution of abundances among species, with high values for q = 1 and 2. This

suggests that the studied communities have a lower dominance of a few species,

which could be associated with greater resilience to environmental disturbances.

(Chao & Ricotta, 2019)

The results underscore the importance of considering multiple dimensions of

diversity (richness, diversity, and evenness) to understand biological communities'

structure comprehensively. The lower sample completeness for q = 0 suggests that

rare, yet ecologically important, species are challenging to detect with

conventional sampling methods. This could affect conservation, as these species

are often more vulnerable to environmental disturbances (Hortal et al., 2015). On

the other hand, the high completeness for q = 1 and 2 reflects that the dominant

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species are well represented, which is relevant to maintaining the stability of the

ecosystem and the associated ecosystem services. (Chao & Jost, 2015)

The stabilization of the rarefaction and extrapolation curves for higher orders

(Figure 1b) confirms that the sampling effort was adequate to capture the diversity

of the most common species but also highlights the need to increase the sampling

effort or employ complementary techniques to improve the detection of rare

species (Gotelli & Colwell, 2011). The observed evenness suggests that the studied

communities have a relatively balanced distribution of abundance, which could

indicate a lower dominance of a few species and, therefore, greater resilience to

disturbances (Chao & Ricotta, 2019). However, it is important to consider that

these patterns could vary depending on environmental factors, such as climate,

resource availability, or land-use history, which opens new lines of research to

explore the mechanisms underlying the structure of these communities. (Chao et

al., 2020)

The results reinforce the importance of considering long-term ecological processes

in restoring tropical dry forests. Although assisted regeneration has favored the

establishment of a diverse tree community, the species composition and structure

of the regenerated forest continue to differ from that of the natural forest. The

lower evenness and greater dominance of certain species in the regenerated forest

suggest that this ecosystem is still in its early recovery phase. Longer-term

assessments are needed to determine whether the regenerated forest converges

with the natural ecosystem in terms of biodiversity and community structure.

Complementary restoration strategies, such as facilitating seed dispersal or

enriching late-successional species, could accelerate this process and improve the

resilience of the restored ecosystem. (Holl & Aide, 2011)

4. CONCLUSIONS

This study compared biodiversity between a natural tropical dry forest and one

undergoing a 10-year assisted regeneration process, revealing significant

differences in species richness, evenness, and community structure. Greater

diversity was recorded in the natural forest. Furthermore, the Pielou index

reflected a more equitable species distribution in the natural ecosystem, while the

regenerated forest presented greater species dominance. The observed patterns

indicate that assisted regeneration has facilitated the establishment of a tree

community, but with less evenness and a structure dominated by few species,

suggesting that the ecosystem is in an early stage of ecological succession.

Extrapolation of diversity suggests that, even with a more significant sampling

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effort, the richness of the regenerated forest would not reach that of the natural

forest in the medium term.

This study contributes to the knowledge of regeneration processes in tropical dry

forests, providing empirical evidence on the differences in biodiversity between

natural and restored ecosystems. The findings support theoretical models of

ecological succession, highlighting that recovering forests can remain structurally

distinct from mature ecosystems for decades. Furthermore, the information

obtained can be used to refine theories about the resilience of these ecosystems

and the factors that influence their recovery trajectories.

From an applied perspective, the results underscore the need for complementary

restoration strategies to accelerate the convergence of regenerated forests toward

a state more similar to the natural ecosystem. Actions such as introducing late-

successional species and promoting seed dispersal can improve the resilience of

the restored ecosystem. Furthermore, the findings can be used in designing

conservation policies to restore tropical dry forests and mitigate biodiversity loss.

The recovery of these ecosystems also has implications for local communities,

given their role in providing essential ecosystem services, such as water regulation

and carbon sequestration.

Our results strongly support the development of public policies that integrate a

longer time horizon for tropical dry forest restoration projects. Specifically,

policymakers should establish regulatory frameworks that require post-restoration

monitoring for at least 15-20 years, implement financial incentives for landowners

who maintain assisted regeneration areas beyond the typical 5-10 year funding

cycles, and develop cross-sectoral coordination mechanisms between forestry,

agriculture, and environmental departments. Such policies would recognize that

ecological recovery requires sustained intervention and support, particularly in the

crucial transition from early to late-successional stages, thereby enhancing

biodiversity conservation and ecosystem service provision in these threatened

ecosystems.

While this study provides valuable information, it has certain methodological

limitations. The analysis's sample size and time scale may not fully capture the

recovery dynamics of regenerated forests. Long-term monitoring studies assessing

biodiversity evolution in these ecosystems are recommended. Future research

could include the analysis of key ecological interactions, such as seed dispersal by

fauna and competition among species. Furthermore, integrating ecological

266

modeling tools would allow for predicting the recovery trajectory of regenerated

forests under different management and climate change scenarios.

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