Composition and Tree Structure of a Dry Forest Fragment in the Ecuadorian Coast

Introduction

Dry forests are ecosystems with a high level of endemism and have a wide variety of species (Manrique-Ascencio et al., 2025; Howard et al., 2024; Rivas et al., 2020; Sosa et al., 2018; Moonlight et al., 2020; Espinosa et al., 2012). Their main characteristic is their presence in areas with a prolonged dry season (Hasnat and Hossain, 2020) where the clay soils form mudflats during the rainy season that crack in the dry season (Aguirre, 2012). These forests are primarily dominated by species with adaptations to adverse climatic conditions (Preece et al., 2018; Singh and Chaturvedi, 2017; Banda et al., 2016; Brunner et al., 2015; Pennington et al., 2009). One of the most common strategies is deciduousness, where trees shed their leaves to withstand seasonal drought (Allen et al., 2017; Hubbell, 1979).

Despite their ecological importance, dry forests are among the most vulnerable and threatened ecosystems worldwide (Manchego et al., 2017). They face severe degradation due to land-use change, particularly for activities such as extensive cattle ranching and agriculture areas (Quintana et al., 2019) which has significantly impacted biodiversity (Ballesteros et al., 2019). In Ecuador, these forests are found in the provinces of Esmeraldas, Manabí, Guayas, El Oro, and Loja, extending into northwestern Peru along the coastal region west of the Andes (Linares-Palomino, 2010; Aguirre and Geada-Lopez. 2017; Quintana et al., 2017). Despite their vulnerability, they receive less protection and conservation efforts compared to evergreen forests on the Ecuadorian coast (Rivas et al., 2020; Muñoz et al., 2019).

Beyond their biodiversity, dry forests play a crucial role in providing ecosystem services. These include carbon sequestration, soil stabilization, water regulation, and biodiversity conservation (Aguirre-Padilla et al., 2018; Quintana et al., 2019). Additionally, they offer provisioning services by supplying timber, fuelwood, fodder, and non-timber forest products essential for local livelihoods (Aguirre and Erazo, 2017). However, the overexploitation of these resources, coupled with insufficient knowledge about their composition, structure, and ecological functions, can lead to resource scarcity, negatively impacting surrounding communities (Uslar et al., 2004; Aguirre et al., 2018; Palma, 2016; Jiménez et al., 2017).

In this context, vegetation studies provide critical insights into species composition, structure, and endemism, allowing for biodiversity assessments and a better understanding of forest conservation status. Such information is essential for ecosystem management and sustainable planning, ensuring that dry forests continue to deliver key ecological and socio-economic benefits (Quintana et al., 2017; Aguirre, 2013).

Materials and Methods

The study area lies in Los Bajos, a sector of Montecristi, a canton of Manabí, Ecuador, located in the southeastern region of the province. It has a total area of 734.2 km² and has a tropical dry subhumid climate, with rainfall concentrated between January and March. However, due to consistently high temperatures, with an annual average of 24°C, evapotranspiration rates exceed monthly precipitation throughout the year, resulting in a negative humidity coefficient (Ouyang et al., 2021). The sampling plots were established in a dry forest under the management of the Los Bajos de Pechiche community in Montecristi. This area represents a typical Ecuadorian dry forest characterized by seasonal water limitations and floristic adaptation to arid conditions.

The methodology follows the protocol proposed by Moonlight et al. (2020), which randomly establishes a 50 × 100-meter sampling plot using a random sampling approach. To ensure objectivity in plot selection, we utilized Geographic Information Systems (GIS) to randomly assign the sampling location within the study area. The plot was then subdivided into 10 × 10 m subplots, where we recorded the diameter at breast height (DBH) for all trees with a DBH of 5 cm or greater. Using these data, we conducted the structural study, which includes the following variables:

Abundance: It refers to the number of individuals per species; two types of abundance are considered:

Absolute abundance (Aab) = number of individuals per species

Relative abundance (Ar) = number of individuals per species concerning the total number of individuals found in the study area (ni)

Ar = (ni/N) × 100

Where: ni = number of individuals of the i species. N = number of total individuals in the sample.

Frequency: This allows us to determine the number of plots in which a particular species appears; we use two frequencies:

Absolute frequency (Fab) = Presence/absence of a particular species in the plots.

Relative frequency (Fr) = number of plots where a particular species appears concerning the inventoried plots.

Fr= (Fab i / Fab t) × 100

Where: Fabi = Absolute frequency of the i species. Fabt= Total of the frequencies in the sample.

Dominance: Represents the space they occupy or the sum of the horizontal projections of the trees on the ground. Sometimes, this determination is somewhat complicated by the vertical structure of some types of forests, which is represented by the relationship between the basal area of the individuals of a species and the sampled area. Differentiating between two types of dominance.

Absolute dominance (Dab)

Dab = Gi/Gt

Where: Gi = Basal area in m2 for the ith species. Gt= Basal area in m2 of all species

Relative dominance (Dr)

Dr = (Dab i / Dab t) × 100

Where: Dai = Absolute dominance of the i species. Dat = Absolute dominance of all species.

Importance value index (IVI): The IVI is calculated for each species as the sum of its relative abundance, frequency, and dominance, following the methodology proposed by Curtis and McIntosh (1951). This index provides a comprehensive measure of the ecological significance of species within a forest ecosystem, integrating structural and functional attributes (Mori et al., 1983). The IVI is widely used in vegetation studies to identify dominant and keystone species, aiding in conservation and management decisions (Lamprecht, 1989; Magurran, 2021).

IVI = Ar + Fr + Dr

Where: Ar= Relative abundance, Fr= relative frequency, Dr= Relative dominance

By incorporating multiple ecological parameters, the IVI allows for a more robust interpretation of species composition and forest structure, making it a valuable tool in ecological and biodiversity assessments (Kent and Coker, 2012).

Results

We identified 156 individuals, divided into 16 genera and 17 species within 13 families (Table 1). Boraginaceae was the most abundant family (67 individuals), followed by Malvaceae (25 individuals) and Capparaceae (18 individuals).

Regarding dominance, C. trischistandra, E. ruizii, and C. lutea occupy around 95% of the study area in terms of the space used by the species (Figure 1). It is possible to observe that the most abundant species is C. lutea, followed by E. ruizii, with 66 and 18 individuals, respectively. The species with less presence in the sampled area are Cordia sp. and B. graveolens, with only one individual each. Similarly, C. lutea and E. ruizii are the most frequent species in the sampling plots, adding P. excelsum to this variable. In this same sense, it is possible to note that Cordia sp., B. granveolens, and A. arborescens do not have a notable frequency.

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