Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-27T11:17:39.149Z Has data issue: false hasContentIssue false

Revisiting the phenology of El Triunfo cloud forest, Mexico, 30 years later

Published online by Cambridge University Press:  23 September 2024

Allen Wootton*
Affiliation:
Departamento de Conservación de la Biodiversidad, El Colegio de la Frontera Sur. Carretera Panamericana y Periférico Sur, San Cristóbal de las Casas, Mexico
Paula L. Enríquez
Affiliation:
Departamento de Conservación de la Biodiversidad, El Colegio de la Frontera Sur. Carretera Panamericana y Periférico Sur, San Cristóbal de las Casas, Mexico
Guadalupe Williams-Linera
Affiliation:
Red de Ecología Funcional, Instituto de Ecología, A.C., Xalapa, Mexico
Esteban Pineda-Diez de Bonilla
Affiliation:
Instituto de Ciencias Biológicas, Universidad de Ciencias y Artes de Chiapas. 29035, Tuxtla Gutiérrez, Mexico
*
Corresponding author: Allen Wootton; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Climatic conditions have changed within the cloud forests of southern Mexico, but the effects of these changes on tree phenology are not well understood. Our study aimed to determine relationships between seasonal patterns of flowering and fruiting and the annual and long-term changes in temperature and rainfall in El Triunfo Biosphere Reserve, Mexico. Flowering and ripe fruiting intensity and fruit number were recorded for 158 trees of 21 zoochorous species during 17 months in 2019–2021. Circular statistics, synchronization calculations, and generalized linear mixed models were used to determine phenological patterns and relationships between phenophases and temperature, rainfall, and solar radiation. Flowering was most closely associated (negatively) with rainfall, whereas ripe fruiting was positively associated with solar radiation. We compared recent fruiting seasonality with phenological data collected in 1991–1993. The mean date of community fruiting in 2019–2020 was earlier (April 4) than in 1992 (May 1) and 1993 (May 13). Community fruit number in 2020–2021 decreased in comparison to 2019–2020. Our results suggest that decadal trends of increasing minimum daily temperature and an earlier and wetter wet season influenced the timing of community fruiting phenology, and fruit numbers varied greatly between years, possibly impacting resource availability for frugivores in El Triunfo.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Introduction

Yearly and long-term changes in temperature and rainfall affect flowering and fruiting patterns in tropical forests (Barnes Reference Barnes2015, Chapman et al. Reference Chapman, Chapman, Struhsaker, Zanne, Clark and Poulsen2005, Du et al. Reference Du, Li, Yang, Peng, Tang, Liu, Li, Hong and Song2020). However, long-term or comparative phenological studies are rare in higher elevation tropical cloud forests, especially in the Neotropics (Mendoza et al. Reference Mendoza, Peres and Morellato2017). Cloud forests provide important refuge and reproductive habitats for flora and fauna (Rojas-Soto et al. Reference Rojas-Soto, Sosa and Ornelas2012) and contain a high diversity of endemic species (González-Espinosa et al. Reference González-Espinosa, Meave, Lorea-Hernández, Ibarra-Manríquez and Newton2011). The timing of fruit presence could affect the reproduction and migration of animal species in these forests (Bustamante et al. Reference Bustamante, Barrios and Juárez2010).

In the ecologically and climatically complex systems of wet tropical forests, factors that influence the phenology of tree communities, species or individuals of a species can be both biotic and abiotic. Biotic factors include the timing of interactions between flower production and the seasonal fluctuations in abundance of pollinators (Xu & Servedio Reference Xu and Servedio2021), niche partitioning between fruit production characteristics and frugivore dispersers (Todeschini et al. Reference Todeschini, Toledo, Rosalino and Hilario2020), changes in the allocation of resources between growth and reproduction (Wheelwright Reference Wheelwright, Estrada and Flemming1986), and the time between flower pollination and fruit production (Bendix et al. Reference Bendix, Homeier, Ortiz, Emck, Breckle, Richter and Beck2006). Biotic factors often influence the numbers of fruits produced and length of fruiting period (Brito et al. Reference Brito, Maia, Silveira, Fracasso, Lemos-Filho, Fernandes, Goldenberg, Morellato, Sazima and Staggemeier2017, Oshima et al. Reference Oshima, Tokumoto and Nakagawa2015), whereas abiotic factors influence the timing of phenological patterns (Mendoza et al. Reference Mendoza, Peres and Morellato2017, Van Schaik et al. Reference Van Schaik, Terborgh and Wright1993).

Abiotic factors include both environmental conditions where intra-annual changes are consistent between years (e.g., solar radiation and daylength; Numata et al. Reference Numata, Yasuda, Okuda, Kachi and Noor2003) or vary over longer time periods (e.g., temperature, rainfall, and relative humidity; Bendix et al. Reference Bendix, Homeier, Ortiz, Emck, Breckle, Richter and Beck2006, Dunham et al. Reference Dunham, Razafindratsima, Rakotonirina and Wright2018). Pau et al. (Reference Pau, Wolkovich, Cook, Davies, Kraft, Bolmgren, Rodríguez Betancourt and Cleland2011) discussed the possibility that species with similar phenological patterns from year to year are influenced by factors that change little between years. Species with changes in the timing of phenological patterns between years may be more influenced by factors with yearly variation such as temperature and rainfall (Pau et al. Reference Pau, Cordell, Ostertag, Inman and Sack2020).

The causes of changing phenological patterns within a tropical tree community may be difficult to determine, as species with different life histories can have varying phenological responses to the same climatic factors (Boyle & Bronstein Reference Boyle and Bronstein2012). The diversity of species and phenological patterns in the cloud forests of southern Mexico (Solórzano et al. Reference Solórzano, Ávila, Castillo, Meave, Ibarra-Manríquez, Pérez Farrera, Tejeda Cruz and Silva Rivera2010) indicate that climatic factors may have different influences on individual species within a forest community in areas like the El Triunfo Biosphere Reserve.

El Triunfo is located in the Sierra Madre de Chiapas, in southern Mexico. It was established in 1990 with the goal to conserve endemic species and biodiversity of the region, especially within the higher elevation cloud forests. These forests are important reproductive habitats for bird and mammal species, which share fruit species as their feeding resources in this area (Ávila et al. Reference Ávila, Hernandez and Velarde1996, González-García et al. Reference González-García, Santana-C, Barbudo, Rico-Gray and Moliner2017, Lira-Torres et al. Reference Lira-Torres, Naranjo-Piñera, Güiris-Andrade and Cruz-Aldán2004).

In the years after the establishment of the Reserve, Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000) recorded the number of fruits present in a community of trees producing the feeding resources of quetzals (Pharomachrus mocinno) in 1991–1993. The patterns of some tree species observed within this study indicate phenological influences from variable climatic conditions. For example, two species within the avocado family Lauraceae, Nectandra rudis and Ocotea chiapensis, showed different monthly patterns of fruit occurrence in 1992 and 1993.

In our study, we revisited the same area of El Triunfo nearly 30 years later to determine if phenological patterns had changed. Like Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000), we focused on the fruits consumed by quetzals (Figure 1), which were the majority of the common tree species producing fleshy animal dispersed fruits (subsequently referred to as zoochorous community; Figure 1, Table S1). As climate trends occur, changes in the timing of flower and fruit production of some tree species may cause shifts in the overall phenological patterns of this community.

Figure 1. Photos of the 21 tree species included in this study in the cloud forest of polygon 1 of El Triunfo, Mexico. Species shown are as follows: (1) Ocotea chiapensis, (2) Nectandra rudis, (3) Licaria excelsa, (4) Ocotea acuminatissima, (5) Cinnamomum zapatae, (6) Saurauia madrensis, (7) Saurauia yasicae, (8) Conostegia volcanalis, (9) Citharexylum mocinnii, (10) Hedyosmum mexicanum, (11) Ardisia compressa, (12) Ardisia verapazensis, (13) Morus insignis, (14) Trophis cuspidata, (15) Frangula capreifolia, (16) Symplococarpun purpusii, (17) Dendropanax arboreus, (18) Clusia salvinii, (19) Prunus brachybotrya, (20) Prunus tetradenia, and (21) Eugenia capuli.

Climate seasonality can be less distinct in tropical mountain environments, where high humidity continues throughout the year from fog and orographic rainfall (Bruijnzeel et al. Reference Bruijnzeel, Mulligan and Scatena2011, Loope & Giambelluca Reference Loope and Giambelluca1998). However, in the higher elevations of the Sierra Madre, seasonal climatic differences are evident, most notably in rainfall and minimum daily temperatures (CONAGUA (Comisión Nacional del Agua) 2021). Since 1990, there have been significant trends in temperature and rainfall in the Sierra Madre (Wootton et al. Reference Wootton, Enríquez and Navarrete-Gutiérrez2023). Within El Triunfo, the wet season has trended earlier in the year and has become wetter. The dry season has also trended earlier in the year, and rainfall has decreased from October to December during the transition to the dry season. In the higher elevation areas of El Triunfo, minimum daily temperatures have increased, particularly in the colder months of January and February, and maximum daily temperatures have decreased (Wootton et al. Reference Wootton, Enríquez and Navarrete-Gutiérrez2023).

In addition to yearly climatic influences, extreme weather conditions (e.g., strong wind and hail) could affect short-term phenology through the destruction of flowers and fruits (Bustamante et al. Reference Bustamante, Barrios and Juárez2010, Butt et al. Reference Butt, Seabrook, Maron, Law, Dawson, Syktus and McAlpine2015). Hurricane winds are rare in the Sierra Madre (Tejeda-Cruz & Sutherland Reference Tejeda-Cruz and Sutherland2005). However, during the study period from 2019 to 2021, Hurricane Eta hit the west coast of Southern Mexico, bringing maximum wind speeds of 124–170 km/hr to the study area between October 31 and November 6, 2020.

The objectives of this study were to determine (a) the seasonality and synchronization of flower and fruit presence in the zoochorous tree species community; (b) the relations between these phenophases and climatic variables (temperature, rainfall, and solar radiation); (c) changes in the timing of seasonal fruiting between periods separated by ∼30 years, 1992–1993 and 2019–2020; and (d) changes in the timing of seasonal fruiting and number of fruits produced between 2019–2020 and 2020–2021.

Methods

Study area

The study area is in the central zone of Polygon 1 in the El Triunfo Biosphere Reserve, Chiapas, Mexico (15º 39′ 23.8″N, 92º 48′ 29.3″ W; Figure S1), within a valley at the higher elevations of the Sierra Madre de Chiapas. Phenological observation points were established along 3 km sections of four trails within the valley, mountain crests, and the higher elevation Pacific coastal slope of this area (Figure S1). These trails range in elevation between 1970 and 2100 m a.s.l., where forest composition and diversity vary greatly among riparian, sheltered, and higher wind-exposed areas (Breedlove Reference Breedlove1981, Long & Heath Reference Long and Heath1991, Solórzano Reference Solórzano1995).

Four climate variables, linked to phenological patterns in other wet tropical forests (Pau et al. Reference Pau, Cordell, Ostertag, Inman and Sack2020, Zimmerman et al. Reference Zimmerman, Wright, Calderón, Pagan and Paton2007), were included in this study. These were monthly rainfall, average monthly minimum (Tmin) and maximum (Tmax) daily temperature, and monthly averages of daily solar radiation. Temperature and rainfall data were obtained from the automated El Triunfo weather station at 1972 m a.s.l. located at the central camp in Polygon 1 (CONAGUA (Comisión Nacional del Agua) 2021). Solar radiation was estimated using the Hargreaves-Samani temperature-based model (Hargreaves & Samani Reference Hargreaves and Samani1985), which has been determined to provide an accurate estimate of solar radiation where direct measurements are not available (Almorox et al. Reference Almorox, Bocco and Willington2013). This method uses inputs of day of the year and latitude to estimate daily total extraterrestrial radiation and daily temperature range to account for cloud cover and atmospheric transmittance of radiation in the model (Quej et al. Reference Quej, Almorox, Ibrakhimov and Saito2016).

In the study area, during the period from 2019 to 2021, Tmin was the lowest during December to February (6 ºC) and the highest during June (12 ºC). Tmax is less variable throughout the year and ranges from 23 ºC in January to 25 ºC in May. Rainfall is the greatest during June (600 mm) with another peak in September (550 mm) and the lowest (100 mm or less) during December to April (Figure S2), and solar radiation is the greatest during March–April (21–22 MJm−2day−1) and the lowest during October–January (15–16 MJm−2day−1), depending on cloud cover conditions.

Phenological surveys

Phenological observations were done around the third week of each month from March 2019 to March 2020 (excluding July and November 2019) and were meant to continue throughout 2020. However, due to pandemic travel restrictions, observations were postponed until December 2020 (the month after hurricane Eta) and continued monthly until May 2021. A total of 158 individual trees were selected under the criteria of being: 1) mature trees (similar tree sizes to those of the same species observed producing fruits) of 21 fleshy-fruit producing species, and 2) trees that could be observed from the trails (near to the trail and also further away) based on the visibility of the crown of the tree to observe flower and fruit presence (Figure 1, Tables S1 and S2).

The number of trees per species was selected based on the estimated proportion of each species within the community, following the methods used by Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000). However, the number of tagged trees per species and the species included differed from Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000) due to differences in estimated species compositions between the early 1990s and 2020s and differences in the species of fruits observed to be consumed by quetzals in more recent years (detailed composition results in Wootton Reference Wootton2022). For some rarer species in the study area, we tagged less than the five trees per species recommended by Frankie et al. (Reference Frankie, Baker and Opler1974) (Table S1). However, these species were included in the community analysis because a high diversity of fruit species may be important for frugivores in El Triunfo (González-García et al. Reference González-García, Santana-C, Barbudo, Rico-Gray and Moliner2017, Solórzano et al. Reference Solórzano, Castillo, Valverde and Ávila2000) and provided a better understanding of community patterns.

Phenological observations focused on reproductive phenophases. These were intensity of flowering (flowers in anthesis), fruiting (unripe and ripe), and the number of ripe fruits per tree. Intensity observations were done by estimating the percentage of the crown of each tree surveyed with flowers, unripe fruits, and ripe fruits. These percentages represented intensity scores of 0 (0%), 1 (1–20%), 2 (21–40%), 3 (41–60%), 4 (61–80%), and 5 (81–100%) (Fournier Reference Fournier1974).

The number of ripe fruits on each tree surveyed was estimated by counting the number of fruits in the entire tree with the use of binoculars. Where the entire crown was not visible or there were large amounts of fruits in the tree, the number of fruits in a portion of the tree, usually one branch, was counted, and this number was multiplied by the estimated remainder of the tree. Some species, such as Citharexylum mocinnii, produced large amounts of fruits in bunches. In this case, the average number of fruits was estimated for each bunch, and this was multiplied by the estimation of the number of bunches in each tree.

Calculations of overall zoochorous community values of flowering, unripe fruiting, and ripe fruiting intensity were done by adding monthly intensity scores of all trees in the study for each phenophase. Community fruit number values were the sum of logarithmically transformed fruit counts/estimations of all trees. Fruit number values were logarithmically transformed to avoid large fruit number biases from some species within the community values. To determine differences in fruit number between years, monthly sums of fruit number without the transformation were used.

To compare fruiting patterns between 1992, 1993, and 2019–2020, the monthly number of ripe fruits at the community level was calculated by logarithmically transforming the average number of fruits of each species each month and then adding these values to obtain a community value. This was done to standardize the number of fruits per tree per species between the 1992–1993 and 2019–2021 studies, which had different numbers of trees observed per species. For these comparisons, we only included those tree species that were observed both in 1992–1993 and 2019–2021. For the months when observations could not be obtained (July and November 2019), phenophase values of the tagged trees were estimated from the mean values of the logarithmically transformed fruit number data for each tree from the adjacent months. Fruit number data from months without observations in 1992 (January, May, July, and October) and 1993 (May, August, and September) were estimated from the mean values of adjacent months of the logarithmically transformed fruit number data for each tree species.

Statistical analysis

Circular statistics were used to determine the seasonality of each of the observed phenophases during April 2019–March 2020. Months with phenological data were converted to angles around a circle, with January converted to 15º and each month after at 30º intervals. The following calculations and tests of seasonality were done in R version 4.2 (R Core Team 2022) using scripts adapted from Mendoza (Reference Mendoza2020): (a) the average angle (date) of the distribution of data; and r vector, which is a proxy of the degree of seasonality of flowering and fruiting with a range of 0 to 1, where 0 is without seasonality with the presence of flowers and fruits distributed uniformly during the year and 1 is very seasonal with all the presence in one month (Cox Reference Cox2004, Morellato et al. Reference Morellato, Alberti, Hudson, Hudson and Keatley2010).

Phenophase synchronization in populations of 12 species with greater than five trees observed and in the overall zoochorous community was calculated using the following index developed by Freitas & Bolmgren (Reference Freitas and Bolmgren2008).

$${d_i} ={{1}\over{{{T_i}}}}\;{{1}\over{{N - 1}}}\;\mathop \sum \limits_{j = 1t}^N .\mathop \sum \limits_{t = 1}^T \sqrt {{f_{i,t}}\;{f_{j,t}}} \;,\;j \ne i$$

Where:

${d_i} = \;$ Individual tree synchronization in relation to other trees of the same species included in the observations ( $j$ )

$f = \;$ Phenophase intensity converted to a scale from $0\;to\;1$

${T_i} = \;$ Number of times during the 17 months of observations where ${f_i} \gt 0$ (months when there were flowers or fruits on the tree)

$N = \;$ Number of trees observed per species

$j = \;$ Individual tree in a species population

$t = \;$ Month observation number (1–17)

$T = \;$ Number of months when there were flowers/fruits on any tree per species (when ${f_j} \gt 0$ )

$$S = \;\sum {{{{d_i}}}\over{N}}$$

$S = \;$ Species synchronization

The above calculation was also used to determine community synchronization by including all 158 trees observed. This index ranges from 0 (no synchronization) to 1 (full population or community synchronization) using phenophase intensity values of individual trees observed. The calculation of the index was done using Java programming language (Arnold et al. Reference Arnold, Gosling and Holmes2005).

Relations between climatic variables (rainfall, Tmin, Tmax, and solar radiation) and phenophases (flowering, unripe and ripe fruiting intensity, and log-transformed fruit number) recorded between March 2019 and May 2021 were analyzed using generalized linear mixed models (GLMMs) to determine the best fit models. GLMMs were performed with the glmer function of lme4 (version 1.1-30) library in R (Bates et al. Reference Bates, Mächler, Bolker and Walker2015). Models with an Akaike information criterion (AIC) less than or equal to 2 from the top-ranked model were considered significantly best fit. Climatic variables and phenophases were defined as fixed factors and individual tree as a random factor. The family distribution was defined as negative binomial due to the overdispersion of count data (Finch et al. Reference Finch, Power, Welbergen and Cook2021). Climate variables that were significantly correlated (Spearman correlation, p < 0.05) were not included as covariates in models (similarly to Chapman et al. Reference Chapman, Valenta, Bonnell, Brown and Chapman2018, Finch et al. Reference Finch, Power, Welbergen and Cook2021). These included rainfall with Tmin, Tmin with Tmax, and Tmax with solar radiation.

The Watson-Wheeler test (Batschelet Reference Batschelet1981, Mendoza Reference Mendoza2020) was used to determine significant differences in the mean date (angle) of seasonal ripe fruit production between adjacent years and periods separated by ∼30 years. Fruiting seasonality of two years in the 1990s, February–December 1992 and January–December 1993 (Solórzano et al. Reference Solórzano, Castillo, Valverde and Ávila2000), were compared with our observations from April 2019–March 2020 in the program Oriana 4.02 (Kovach Computing Services 2013).

To compare fruiting characteristics between adjacent years, we used observations from the same months in 2019–2020 and 2020–2021: April, May, and December 2019, January, February, and March 2020 (2019–2020), and December 2020 to May 2021 (2020–2021). Seasonal differences in the timing of ripe fruit production between these half-year periods were also determined using the Watson-Wheeler test. A paired sample t-test was used to determine if there were differences in fruit numbers between the years.

Results

Seasonality and synchronization of flowering and fruiting

During the year-long observation period (April 2019–March 2020), trees within the zoochorous community displayed a mean date of flowering on February 6 (r = 0.46), unripe fruiting on November 10 (r = 0.11), and ripe fruiting on March 9 (r = 0.25) (Figure 2). The mean date of community fruiting (using the circular mean of the logarithmically transformed fruit number) was also March 9 (r = 0.22) (Table S3, Figure 3). All flowering and fruiting patterns were significantly seasonal (p < 0.05). Community ripe fruiting peaks (the circular mode) were greatest at the end of the drier period in El Triunfo during March (Figure 3).

Figure 2. Circular histograms of flowering, unripe fruiting, and ripe fruiting intensity in the zoochorous community in El Triunfo, Mexico, during April 2019–March 2020. Months without observations but including estimated flowering and fruiting values are shown with an E. Arrows indicate the degree of seasonality (r value). Numbers in histograms are the sums of intensity scores for all trees observed in the study.

Figure 3. Circular histograms of number of ripe fruits in the zoochorous tree community in El Triunfo, Mexico, during: (1992) January–December 1992, (1993) January–December 1993 (Solórzano et al. Reference Solórzano, Castillo, Valverde and Ávila2000), and April 2019–March 2020 (2019–2020) in the upper row; and April, May, and December 2019 and January–March 2020 (2020), and December–May 2021 (2021) in the lower row. Months without observations but including estimated flowering and fruiting values are shown with an E. Arrow length indicate the degree of seasonality (significant r value; Table S3). Numbers in histograms are sums of the logarithmically transformed number of ripe fruits estimated monthly in all trees observed.

Community synchronization of ripe (0.47) and unripe (0.47) fruiting was greater than flowering (0.30). Community synchronization was generally greater than that at the species population level. The species with the greatest synchronization of flowering was Ardisia compressa (0.41) and of unripe fruiting was Conostegia volcanalis (0.40). These species produced flowers and unripe fruits during a longer period throughout the year. In contrast, species with the highest synchronization of ripe fruiting, Citharexylum mocinnii (0.34) and Morus insignis (0.36), had short fruit production periods of higher intensity, whereas Nectandra rudis (0.31) had a longer period of fruit production (Table 1). Overall, there was low synchronization at the population level of flowering and fruiting (Table 1).

Table 1. Synchronization of flowering, unripe fruiting, and ripe fruiting in 12 species and the overall zoochorous community in El Triunfo, Mexico. Values range from 0 representing no synchronization of phenophases and 1 full synchronization

Relations between climatic variables and phenological patterns

Based on the AIC, the best fitting models (∆AIC > 2) for the relation between a climate variable and community flowering included both rainfall (negative) and rainfall (negative) with solar radiation (positive). For unripe fruiting, this included only Tmax (negative), and for ripe fruiting intensity, this included solar radiation (positive) with rainfall (negative). The best fitting model with fruit number included solar radiation (positive) with Tmin (negative) (Table 2).

Table 2. Results of the best-fitting models for the relations between phenophases (flowering, unripe fruiting, ripe fruiting, and number of fruits) and climate variables in El Triunfo, Mexico, using generalized linear mixed model analysis. Climate variables are monthly rainfall (rain), minimum daily temperature (Tmin), maximum daily temperature (Tmax), and monthly averages of daily solar radiation (solar). * Models with a ∆AIC > 2.0 were considered significant for the best fit

Seasonality differences between years and 30-year periods

When only the 16 species observed in both Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000) and our study were included, the mean date of ripe fruit presence was May 1 in 1992 (r = 0.13), May 13 in 1993 (r = 0.19), and April 4 in 2019–2020 (r = 0.24) (Figure 3). Mean dates of seasonal fruiting phase were marginally different between both 2019–2020 and 1992 (Watson-Wheeler W = 5.04, p = 0.08) and 2019–2020 and 1993 (Watson-Wheeler W = 4.96, p = 0.084). Mean dates of fruiting were not significantly different between 1992 and 1993 (Watson-Wheeler W = 0.11, p = 0.95). Of the species that produced fruits in all the observation years, seven had earlier mean dates of seasonal fruiting phase in 2019–2020 than in 1992 or 1993, whereas six species had later or similar mean dates (Table S4).

The mean date of community fruiting (number of ripe fruits) estimated during the December–May half-year period in 2019–2020 was March 8 (r = 0.69) and in 2020–2021 was March 20 (r = 0.70) (Figure 3). Mean dates of community fruiting between 2019–2020 and 2020–2021 were significantly different (Watson-Wheeler W = 14.4, p < 0.01). There was a significant difference in community fruit number between the periods in 2019–2020 (monthly mean = 71674 ± 39016) and 2020–2021 (monthly mean = 20683 ± 15512) (t (5) = −3.28, p = 0.02).

Discussion

Phenological patterns

An overall community peak in ripe fruiting occurred during the end of the dry/beginning of the wet season in the cloud forest of El Triunfo between 2019 and 2021. This pattern contrasted with most community fruit peaks in the lower elevation tropical rainforests of the Neotropics, which often occur during the wet season (Mendoza et al. Reference Mendoza, Peres and Morellato2017). These temporal phenological differences may be related to the different climatic conditions according to elevation (Hu & Riveros-Iregui Reference Hu and Riveros-Iregui2016, Mendoza et al. Reference Mendoza, Peres and Morellato2017) and to the different composition of tree species of temperate and tropical origin in the higher elevation cloud forests (Borchert et al. Reference Borchert, Robertson, Schwartz and Williams-Linera2005, González-Espinosa et al. Reference González-Espinosa, Meave, Lorea-Hernández, Ibarra-Manríquez and Newton2011). In Mesoamerican cloud forests, community fruiting peaks at the end of the dry season were also recorded in El Triunfo, Chiapas, 30 years earlier (Solórzano et al. Reference Solórzano, Castillo, Valverde and Ávila2000), in Jalisco, Mexico (Zárate-Cuevas et al. Reference Zárate-Cuevas, Núñez-López, Cuevas-Guzmán, Morales-Arias, Sánchez-Rodríguez, Guzmán-Hernández and Solís Magallanes2022), and in the Cordillera de Talamanca, Costa Rica (Camacho & Orozco Reference Camacho and Orozco1998). In contrast, two distinct peaks (during both dry and wet periods) were recorded in Veracruz, Mexico (Williams-Linera Reference Williams-Linera1997) and in Monteverde, Costa Rica (Dinerstein Reference Dinerstein1986).

Cloud forests have some unique characteristics and conditions that may influence community fruiting patterns. These include a high diversity of endemic tree species, animal dispersers of fruit that migrate altitudinally throughout the year (Boyle Reference Boyle2010), and a longer duration of humidity and water availability from cloud cover, which could also influence solar radiation (Jarvis & Mulligan Reference Jarvis and Mulligan2011). Cloud forests also receive some of the largest quantities of rainfall in Mexico, which in the Sierra Madre has been increasing at a greater rate than the adjacent lower elevation regions (Wootton et al. Reference Wootton, Enríquez and Navarrete-Gutiérrez2023). Fruit ripening peaked just before the wettest period began, when solar radiation was the highest, and after a period of flower production during the time of the year when Tmin was the lowest. Fruiting was also the highest during the reproductive and resident period of many bird species in El Triunfo when altitudinal migrants are in the cloud forest (Gómez de Silva et al. Reference Gómez de Silva, González-García and Casillas-Trejo1999).

In addition to climatic influences, various tree species within the zoochorous community showed phenological characteristics influenced by biotic interactions. Some species, such as Ardisia compressa, had low synchronization among individuals and low overall seasonality, which may be a strategy to disperse seeds throughout the year by a specialized animal disperser (Van Schaik et al. Reference Van Schaik, Terborgh and Wright1993). The distinct seasonal peaks in ripe fruiting of eight species in our study may be linked to the arrival times of migratory bird (Gómez de Silva et al. Reference Gómez de Silva, González-García and Casillas-Trejo1999) or mammal (González-Zamora et al. Reference González-Zamora, Arroyo-Rodríguez, Chaves, Sánchez-López, Stoner and Riba-Hernández2009) species. For example, Trophis cuspidata had an average fruiting phase date in September, four months later than the overall community dates. Some bird species (e.g., White-throated Thrush Turdus assimilis, Highland Guan Penelopina nigra) migrate to higher elevations during autumn in El Triunfo and have been observed consuming this fruit species (Gómez de Silva et al. Reference Gómez de Silva, González-García and Casillas-Trejo1999), possibly due to its fruit production patterns (Boyle Reference Boyle2010). Climate-influenced changes in tree species’ fruiting patterns could affect seasonal migration and composition of animal species in the reserve (Ramos-Robles et al. Reference Ramos-Robles, Andresen and Díaz-Castelazo2016).

Ocotea chiapensis produced various peaks in ripe fruiting throughout the year. This may be important for food availability for animals that stay year-round in the cloud forest, during the summer wet season when fruit is scarcer in this forest, and can facilitate seed dispersal when there is less competition for frugivore dispersers (Wheelwright Reference Wheelwright1985). Most of the species produced many fruits one year and few or no fruits the next year. These included the species in the Lauraceae family, which Wheelwright (Reference Wheelwright, Estrada and Flemming1986) suggested was a strategy to allocate resources between reproduction and vegetative growth between years.

There were some limitations to recording phenological patterns due to the natural conditions of the study area. The timing of greatest fruiting in El Triunfo coincided with the breeding season of several frugivore species (Ávila et al. Reference Ávila, Hernandez and Velarde1996, González-García et al. Reference González-García, Santana-C, Barbudo, Rico-Gray and Moliner2017), when fruit consumption needs are the greatest (Ávila et al. Reference Ávila, Hernandez and Velarde1996). The consumption of these ripe fruits before they could be observed could affect the apparent fruiting seasonality of some tree species.

Climatic-influenced flowering and fruiting patterns

Community flowering was greatest during the driest part of the year (January–April), which may coincide with a higher abundance of pollinators and lower potential for storm damage (Van Schaik et al. Reference Van Schaik, Terborgh and Wright1993, Xu & Servedio Reference Xu and Servedio2021). Flowering mainly occurred during the months of the year with the lowest temperatures (January–March), although in 2021, there was also high flower presence in April, which is a warmer month. Ramírez & Davenport (Reference Ramírez and Davenport2016) discussed that some species within tropical regions that are related to species in temperate regions, such as Prunus sp., may require a dormant period during cooler temperatures to initiate flower production. We also observed this in Prunus brachybotrya trees in the studied community.

Unripe fruiting was most associated (negatively) with Tmax. The development of unripe fruits is dependent on the timing of flowering patterns, so the timing of fruit development may be due more to flowering times (Bendix et al. Reference Bendix, Homeier, Ortiz, Emck, Breckle, Richter and Beck2006) than Tmax patterns, which do not change drastically throughout the year. Rainfall was the climate variable least associated with unripe fruiting intensity. This may be related to the lower seasonality of unripe fruit presence, which lasts throughout both the dry and wet periods.

Community ripe fruiting was most associated (positively) with solar radiation. Solar radiation is an important factor influencing plant transpiration (Turc Reference Turc1961), which increases water and nutrient flow through the tree (Montanaro et al. Reference Montanaro, Dichio and Xiloyannis2010) and can influence fruit development (de Azevedo et al. Reference de Azevedo, de Souza, da Silva and da Silva2007). It also has been shown to be directly an important factor in fruit ripening in other tropical forests (Chapman et al. Reference Chapman, Valenta, Bonnell, Brown and Chapman2018, Zimmerman et al. Reference Zimmerman, Wright, Calderón, Pagan and Paton2007).

Some tree species showed high variation within populations in synchronization and the timing of fruit presence, and some species had fruiting peaks during the wettest period of the year. Community patterns may be due to individual tree patterns rather than species composition (although some species, such as Morus insignis, had high seasonality and synchronization between individuals). Therefore, climatic factors may be affecting the tree community patterns independently from individual species phenological behaviors.

Effects of climate on long term and yearly phenological patterns

Between 1990 and 2020, there was a 30-year trend of increasing Tmin and decreasing Tmax in El Triunfo (Wootton et al. Reference Wootton, Enríquez and Navarrete-Gutiérrez2023). Rainfall patterns shifted earlier in the year: the start and end of the wet season trended earlier in the year, and rainfall peaks shifted from late in the wet season (September) to early (June). These changes in temperature and rainfall seem to have influenced the earlier shift in the overall seasonal patterns of zoochorous community fruiting between 1992–1993 and 2019–2020, although this was variable amongst species.

Warmer and wetter trends have also been recorded in parts of Africa where there have been longer term phenological observations. In Uganda, Chapman et al. (Reference Chapman, Chapman, Struhsaker, Zanne, Clark and Poulsen2005) determined that as these climate trends occurred, a higher proportion of trees produced fruits, but some species rarely produced fruits in the later years. We observed few fruits during 2019–2021 in comparison to records from the 1990s in some species such as Symplococarpun purpusii, although this species seems to have interannual variability in fruit production and production may be higher in years outside of our observations. Fruit production also increased greatly between 1992–1993 and 2019–2020 in two of the most common Lauraceae species in El Triunfo, Ocotea chiapensis and Nectandra rudis.

Increasing rainfall trends have also been linked to the number of species with fruits and timing of fruiting within tropical tree communities. Dunham et al. (Reference Dunham, Razafindratsima, Rakotonirina and Wright2018) recorded a higher richness of species producing fruits and a greater intensity of fruiting in Madagascar during a period of increasing rainfall. In this area, after dry seasons receiving less rainfall than normal, there was a later shift in fruiting patterns in the next year (Dunham et al. Reference Dunham, Razafindratsima, Rakotonirina and Wright2018). 1990 and 1991 were exceptionally dry years in Chiapas and around the world (Murray-Tortarolo et al. Reference Murray-Tortarolo, Jaramillo, Maass, Friedlingstein and Sitch2017). This drought may have influenced the later fruiting patterns observed in 1992–1993 in El Triunfo than in 2019–2021.

Changes in air temperature may have also affected fog conditions. Solórzano et al. (Reference Solórzano, Castillo, Valverde and Ávila2000) described months during their phenological observations when it was not possible to count fruits due to heavy fog. But there were no months during our observations when fog was so thick that fruits could not be observed. Less fog cover could increase the amounts of solar radiation reaching the forest and decrease available water during the dryer period of the year (Giambelluca et al. Reference Giambelluca, DeLay, Nullet, Scholl and Gingerich2011). This may have influenced the higher seasonality of ripe fruit in comparison to 1992–1993, with peaks in March and April before increased cloud cover during the wet season would have resulted in decreased solar radiation reaching the forest canopy.

Solar radiation was estimated at the site of the El Triunfo weather station. However, the actual solar radiation affecting each tree observed could vary from this estimation due to local factors such as cloud and fog cover, slope aspect, and forest canopy conditions. These conditions change greatly throughout the valleys and slopes of the study area and between tree species heights.

The reduction in fruit number between December–May in 2019–2020 and 2020–2021 shows the variation in seasonal patterns during the period when the greatest fruit production occurs. Strong wind and rain from Hurricane Eta may have caused flowers and unripe fruits to fall, disrupting the patterns of ripe fruit production and lowering the number of fruits present in the zoochorous community during 2020–2021. This reduction in community fruiting is like what occurred after Hurricane Hugo in Puerto Rico (Wunderle Reference Wunderle1995) and Hurricane Karl in Veracruz, Mexico (Williams-Linera et al. Reference Williams-Linera, Alvarez-Aquino and Tolome2021). The production of flowers once again after Hurricane Eta may have resulted in a later ripe fruit development in comparison to earlier years. Changes between years in fruit number may also be due to natural cycles between reproductive and vegetative growth of some species (Wheelwright Reference Wheelwright, Estrada and Flemming1986).

Ecological implications for the El Triunfo Biosphere Reserve

Shifts in phenological patterns related to climate trends show changing ecological conditions within cloud forests. Some of the factors influencing climate trends in the Sierra Madre de Chiapas since 1990 are cyclical over longer time periods (Fuentes-Franco et al. Reference Fuentes-Franco, Coppola, Giorgi, Pavia, Diro and Graef2015), so their effects on fruiting patterns during the next 30 years may be different than the past 30 years. However, severe weather events like tropical storms and droughts are expected to occur more frequently in the next decades in Mexico (Murray-Tortarolo Reference Murray-Tortarolo2021). Our results suggest that climate trends have influenced shifts in the timing and seasonality of fruit production, and fruit number fluctuated greatly between years possibly due to extreme weather, both conditions having long- and short-term consequences for the availability of fruit for wildlife in the reserve.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/S0266467424000191

Acknowledgements

We thank Marco Domínguez for his contribution to the field observations, Rubén Martínez for help with tree species identification, Fabiola Martinez for data analysis requiring Java, and to the directors, managers, and park rangers of the El Triunfo Biosphere Reserve for their help with species identification and field logistics. The authors thank Dr. Liang Song, associate editor, and anonymous reviewers for helpful suggestions that improved the manuscript. Field work in El Triunfo received permission from CONANP and fruit collection from SEMARNAT (No. SGPA/DGVS/8055/19).

Financial support

This project received funds from El Colegio de la Frontera Sur Department of Biodiversity Conservation, and the first author received a CONACyT doctoral scholarship (No. 884660).

Competing interests

The authors declare none.

Ethical statement

None.

References

Almorox, J, Bocco, M and Willington, E (2013) Estimation of daily global solar radiation from measured temperatures at Cañada de Luque, Córdoba, Argentina. Renewable Energy 60, 382387.CrossRefGoogle Scholar
Arnold, K, Gosling, J and Holmes, D (2005) The Java Programming Language. Reading, USA: Addison Wesley Professional.Google Scholar
Ávila, ML, Hernandez, VH and Velarde, E (1996) The diet of resplendent quetzal (Pharomachrus moncinno mocinno: Trogonidae) in a Mexican cloud forest. Biotropica 28, 720727.Google Scholar
Barnes, J (2015). Phenological and altitudinal changes in plants responding to drying Neotropical Cloud Forests (Bachelor Thesis). Retrieved from University of Colorado, University Libraries. https://scholar.colorado.edu/concern/undergraduate_honors_theses/tb09j621h Google Scholar
Bates, D, Mächler, M, Bolker, B and Walker, S (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67, 148. https://doi:10.18637/jss.v067.i01 CrossRefGoogle Scholar
Batschelet, E (1981) Circular Statistics in Biology. New York, NY: Academic Press.Google Scholar
Bendix, J, Homeier, J, Ortiz, EC, Emck, P, Breckle, SW, Richter, M and Beck, E (2006) Seasonality of weather and tree phenology in a tropical evergreen mountain rain forest. International Journal of Biometeorology 50, 370384. https://doi.org/10.1007/s00484-006-0029-8 CrossRefGoogle Scholar
Borchert, R, Robertson, K, Schwartz, MD and Williams-Linera, G (2005) Phenology of temperate trees in tropical climates. International Journal of Biometeorology 50, 5765. https://doi.org/10.1007/s00484-005-0261 CrossRefGoogle ScholarPubMed
Boyle, WA (2010) Does food abundance explain altitudinal migration in a tropical frugivorous bird? Canadian Journal of Zoology 88, 204213. https://doi.org/10.1139/Z09-133 CrossRefGoogle Scholar
Boyle, WA and Bronstein, JL (2012) Phenology of tropical understory trees: patterns and correlates. Revista de Biología Tropical 60, 14151430.CrossRefGoogle ScholarPubMed
Breedlove, DE (1981) Flora of Chiapas. Part 1. Introduction to the Flora of Chiapas. San Francisco, USA: California Academy of Sciences.Google Scholar
Brito, VL, Maia, FR, Silveira, FA, Fracasso, CM, Lemos-Filho, JP, Fernandes, GW, Goldenberg, R, Morellato, LPC, Sazima, M and Staggemeier, VG (2017) Reproductive phenology of Melastomataceae species with contrasting reproductive systems: contemporary and historical drivers. Plant Biology 19, 806817. https://doi.org/10.1111/plb.12591 CrossRefGoogle ScholarPubMed
Bruijnzeel, LA, Mulligan, M and Scatena, FN (2011) Hydrometeorology of tropical montane cloud forests: emerging patterns. Hydrological Processes 25, 465498. https://doi.org/10.1002/hyp.7974 CrossRefGoogle Scholar
Bustamante, M, Barrios, M and Juárez, D (2010) Fenología de las plantas nutricias del quetzal (Pharomachrus mocinno mocinno de La Llave) y su efecto sobre la abundancia de quetzales en el Biotopo del Quetzal y corredor Biológico del Bosque Nuboso, Baja Verapaz. Informe final de Investigación. Centro de Estudios Conservacionistas – Dirección General de Investigación, Universidad de San Carlos de Guatemala.Google Scholar
Butt, N, Seabrook, L, Maron, M, Law, BS, Dawson, TP, Syktus, J and McAlpine, CA (2015) Cascading effects of climate extremes on vertebrate fauna through changes to low-latitude tree flowering and fruiting phenology. Global Change Biology 21, 32673277.CrossRefGoogle ScholarPubMed
Camacho, M and Orozco, L (1998) Patrones fenológicos de doce especies arbóreas del bosque montano de la Cordillera de Talamanca, Costa Rica. Revista de Biología Tropical 46, 533542.Google Scholar
Chapman, CA, Chapman, LJ, Struhsaker, TT, Zanne, AE, Clark, CJ and Poulsen, JR (2005) A long-term evaluation of fruiting phenology: importance of climate change. Journal of Tropical Ecology 21, 3145. https://doi.org/10.1017/S0266467404001993 CrossRefGoogle Scholar
Chapman, CA, Valenta, K, Bonnell, TR, Brown, KA and Chapman, LJ (2018) Solar radiation and ENSO predict fruiting phenology patterns in a 15-year record from Kibale National Park, Uganda. Biotropica 50, 384395. https://doi.org/10.1111/btp.12559 CrossRefGoogle Scholar
CONAGUA (Comisión Nacional del Agua) (2021) Estaciones Meteorológicas Automáticas (EMAS). Available at https://smn.conagua.gob.mx/es/observando-el-tiempo/estaciones-meteorologicas-automaticas-ema-s (accessed 2021 July 20).Google Scholar
Cox, NJ (2004). Circular statistics in Stata, revisited. In Proceedings of the 10th UK Users Group Meeting, London, UK.Google Scholar
de Azevedo, PV, de Souza, CB, da Silva, BB and da Silva, VP (2007) Water requirements of pineapple crop grown in a tropical environment, Brazil. Agricultural Water Management 88, 201208. https://doi.org/10.1016/j.agwat.2006.10.021 CrossRefGoogle Scholar
Dinerstein, E (1986) Reproductive ecology of fruit bats and the seasonality of fruit production in a Costa Rican cloud forest. Biotropica 18, 307318.CrossRefGoogle Scholar
Du, Y, Li, D, Yang, X, Peng, D, Tang, X, Liu, H, Li, D, Hong, X and Song, X (2020) Reproductive phenology and its drivers in a tropical rainforest national park in China: implications for Hainan gibbon (Nomascus hainanus) conservation. Global Ecology and Conservation 24, e01317. https://doi.org/10.1016/j.gecco.2020.e01317 CrossRefGoogle Scholar
Dunham, AE, Razafindratsima, OH, Rakotonirina, P and Wright, PC (2018) Fruiting phenology is linked to rainfall variability in a tropical rain forest. Biotropica 50, 396404. https://doi.org/10.1111/btp.12564 CrossRefGoogle Scholar
Finch, JT, Power, SA, Welbergen, JA and Cook, JM (2021) Staying in touch: how highly specialised moth pollinators track host plant phenology in unpredictable climates. BMC Ecology and Evolution 21, 113. https://doi.org/10.1186/s12862-021-01889-4 CrossRefGoogle ScholarPubMed
Fournier, LA (1974) Un método cuantitativo para la medición de características fenológicas en árboles. Turrialba 24, 422423.Google Scholar
Frankie, GW, Baker, HG and Opler, PA (1974) Comparative phenological studies of trees in tropical wet and dry forests in the lowlands of Costa Rica. The Journal of Ecology 62, 881919.CrossRefGoogle Scholar
Freitas, L and Bolmgren, K (2008) Synchrony is more than overlap: measuring phenological synchronization considering time length and intensity. Brazilian Journal of Botany 31, 721724. https://doi.org/10.1590/S0100-84042008000400017 CrossRefGoogle Scholar
Fuentes-Franco, R, Coppola, E, Giorgi, F, Pavia, EG, Diro, GT and Graef, F (2015) Inter-annual variability of precipitation over Southern Mexico and Central America and its relationship to sea surface temperature from a set of future projections from CMIP5 GCMs and RegCM4 CORDEX simulations. Climate Dynamics 45, 425440. https://doi.org/10.1007/s00382-014-2258-6 CrossRefGoogle Scholar
Giambelluca, TW, DeLay, JK, Nullet, MA, Scholl, MA and Gingerich, SB (2011) Canopy water balance of windward and leeward Hawaiian cloud forests on Haleakalā, Maui, Hawai’i. Hydrological Processes 25, 438447. https://doi.org/10.1002/hyp.7738 CrossRefGoogle Scholar
Gómez de Silva, H, González-García, F and Casillas-Trejo, MP (1999) Birds of the upper cloud forest of El Triunfo, Chiapas, Mexico. Ornitologia Neotropical 10, 126.Google Scholar
González-Espinosa, M, Meave, JA, Lorea-Hernández, FG, Ibarra-Manríquez, G and Newton, AC (2011) The Red List of Mexican Cloud Forest Trees. Cambridge, UK: Fauna & Flora International. http://www.globaltrees.org/rl_mexican_cloudforest.htm Google Scholar
González-García, F, Santana-C, E, Barbudo, PDJ, Rico-Gray, V and Moliner, VU (2017) Diet and feeding behavior of the Horned Guan (Oreophasis derbianus) in Mexico. The Wilson Journal of Ornithology 129, 771782. https://doi.org/10.1676/16-041.1 CrossRefGoogle Scholar
González-Zamora, A, Arroyo-Rodríguez, V, Chaves, ÓM, Sánchez-López, S, Stoner, KE and Riba-Hernández, P (2009) Diet of spider monkeys (Ateles geoffroyi) in Mesoamerica: current knowledge and future directions. American Journal of Primatology: Official Journal of the American Society of Primatologists 71, 820. https://doi.org/10.1002/ajp.20625 CrossRefGoogle ScholarPubMed
Hargreaves, GH and Samani, ZA (1985) Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1, 9699. https://doi.org/10.13031/2013.26773 CrossRefGoogle Scholar
Hu, J and Riveros-Iregui, DA (2016) Life in the clouds: are tropical montane cloud forests responding to changes in climate? Oecologia 180, 10611073. https://doi.org/10.1007/s00442-015-3533-x CrossRefGoogle ScholarPubMed
Jarvis, A and Mulligan, M (2011) The climate of cloud forests. Hydrological Processes 25, 327343. https://doi.org/10.1002/hyp.7847 CrossRefGoogle Scholar
Kovach Computing Services (2013) Oriana (version 4.02). Retrieved from https://www.kovcomp.co.uk/oriana/ Google Scholar
Lira-Torres, I, Naranjo-Piñera, EJ, Güiris-Andrade, DM and Cruz-Aldán, E (2004) Ecología de Tapirus bairdii (Perissodactyla: Tapiridae) en la Reserva de la Biosfera El Triunfo (Polígono 1), Chiapas, México. Acta Zoológica Mexicana 20, 121.CrossRefGoogle Scholar
Long, A and Heath, M (1991) Flora of the El Triunfo Biosphere Reserve, Chiapas, Mexico. A preliminary floristic inventory and the plant communities of Polygon 1. Anales del Instituto de Biología, Universidad Nacional Autónoma de México. Serie Botánica 62, 133172.Google Scholar
Loope, LL and Giambelluca, TW (1998) Vulnerability of island tropical montane cloud forests to climate change, with special reference to East Maui, Hawaii. Climatic Change 39, 503517. https://doi.org/10.1007/978-94-017-2730-3_18 CrossRefGoogle Scholar
Mendoza, I (2020) Estadística circular aplicada a la Ecología. Ecosistemas 29, 1995. https://doi.org/10.7818/ECOS.1995 Google Scholar
Mendoza, I, Peres, CA and Morellato, LPC (2017) Continental-scale patterns and climatic drivers of fruiting phenology: a quantitative Neotropical review. Global and Planetary Change 148, 227241. https://doi.org/10.1016/j.gloplacha.2016.12.001 CrossRefGoogle Scholar
Montanaro, G, Dichio, B and Xiloyannis, C (2010) Significance of fruit transpiration on calcium nutrition in developing apricot fruit. Journal of Plant Nutrition and Soil Science 173, 618622. https://doi.org/10.1002/jpln.200900376 CrossRefGoogle Scholar
Morellato, LPC, Alberti, LF and Hudson, IL (2010) Applications of circular statistics in plant phenology: a case studies approach. In Hudson, IL, Keatley, MR (eds), Phenological Research: Methods for Environmental and Climate Change Analysis (pp. 339359). Dordrecht: Springer. https://doi.org/10.1007/978-90-481-3335-2_16 CrossRefGoogle Scholar
Murray-Tortarolo, G, Jaramillo, VJ, Maass, M, Friedlingstein, P and Sitch, S (2017) The decreasing range between dry-and wet-season precipitation over land and its effect on vegetation primary productivity. PLoS ONE 12, e0190304. https://doi.org/10.1371/journal.pone.0190304 CrossRefGoogle ScholarPubMed
Murray-Tortarolo, GN (2021) Seven decades of climate change across Mexico. Atmósfera 34, 217226. https://doi.org/10.20937/atm.52803 Google Scholar
Numata, S, Yasuda, M, Okuda, T, Kachi, N and Noor, NSM (2003) Temporal and spatial patterns of mass flowerings on the Malay Peninsula. American Journal of Botany 90, 10251031. https://doi.org/10.3732/ajb.90.7.1025 CrossRefGoogle ScholarPubMed
Oshima, C, Tokumoto, Y and Nakagawa, M (2015) Biotic and abiotic drivers of dipterocarp seedling survival following mast fruiting in Malaysian Borneo. Journal of Tropical Ecology 31, 129137. https://doi.org/10.1017/S026646741400073X CrossRefGoogle Scholar
Pau, S, Cordell, S, Ostertag, R, Inman, F and Sack, L (2020) Climatic sensitivity of species’ vegetative and reproductive phenology in a Hawaiian montane wet forest. Biotropica 52, 825835. https://doi.org/10.1111/btp.12801 CrossRefGoogle Scholar
Pau, S, Wolkovich, EM, Cook, BI, Davies, TJ, Kraft, NJ, Bolmgren, K, Rodríguez Betancourt, JL and Cleland, EE (2011) Predicting phenology by integrating ecology, evolution and climate science. Global Change Biology 17, 36333643. https://doi.org/10.1111/j.1365-2486.2011.02515.x CrossRefGoogle Scholar
Quej, VH, Almorox, J, Ibrakhimov, M and Saito, L (2016) Empirical models for estimating daily global solar radiation in Yucatán Peninsula, Mexico. Energy Conversion and Management 110, 448456. https://doi.org/10.1016/j.enconman.2015.12.050 CrossRefGoogle Scholar
R Core Team (2022) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/ Google Scholar
Ramírez, F and Davenport, TL (2016) The phenology of the capuli cherry [Prunus serotina subsp. capuli (Cav.) McVaugh] characterized by the BBCH scale, landmark stages and implications for urban forestry in Bogotá, Colombia. Urban Forestry & Urban Greening 19, 202211. https://doi.org/10.1016/j.ufug.2016.06.028 CrossRefGoogle Scholar
Ramos-Robles, M, Andresen, E and Díaz-Castelazo, C (2016) Temporal changes in the structure of a plant-frugivore network are influenced by bird migration and fruit availability. PeerJ 4, e2048.CrossRefGoogle ScholarPubMed
Rojas-Soto, OR, Sosa, V and Ornelas, JF (2012) Forecasting cloud forest in eastern and southern Mexico: conservation insights under future climate change scenarios. Biodiversity and Conservation 21, 26712690. https://doi.org/10.1007/s10531-012-0327-x CrossRefGoogle Scholar
Solórzano, S (1995) Fenología de 22 especies arbóreas y su relación con la migración altitudinal del Quetzal (Pharomachrus mocinno mocinno De la Llave 1832) en la Reserva de la Biosfera El Triunfo. Chiapas, México (Bachelor thesis). Retrieved from Repositorio Institucional de la Universidad Nacional Autónoma de México.Google Scholar
Solórzano, S, Ávila, L, Castillo, S, Meave, JA and Ibarra-Manríquez, G (2010) Fenología de los árboles del bosque mesófilo de la Reserva de la Biosfera El Triunfo, Chiapas. In Pérez Farrera, MA, Tejeda Cruz, C, Silva Rivera, E (eds), Los bosques mesófilos de montaña en Chiapas: situación actual, diversidad y conservación (pp. 121160). Tuxtla Gutiérrez, México: Universidad de Ciencias y Artes de Chiapas.Google Scholar
Solórzano, S, Castillo, S, Valverde, T and Ávila, L (2000) Quetzal abundance in relation to fruit availability in a cloud forest in southeastern Mexico. Biotropica 32, 523532. https://doi.org/10.1111/j.1744-7429.2000.tb00498.x CrossRefGoogle Scholar
Tejeda-Cruz, C and Sutherland, WJ (2005) Cloud forest bird responses to unusually severe storm damage. Biotropica 37, 8895. https://doi.org/10.1111/j.1744-7429.2005.03079.x CrossRefGoogle Scholar
Todeschini, F, Toledo, JJD, Rosalino, LM and Hilario, RR (2020) Niche differentiation mechanisms among canopy frugivores and zoochoric trees in the northeastern extreme of the Amazon. Acta Amazonica 50, 263272. https://doi.org/10.1590/1809-4392202000732 CrossRefGoogle Scholar
Turc, L (1961) Estimation of irrigation water requirements, potential evapotranspiration: a simple climatic formula evolved up to date. Annales Agronomiques 12, 1349.Google Scholar
Van Schaik, CP, Terborgh, JW and Wright, SJ (1993) The phenology of tropical forests: adaptive significance and consequences for primary consumers. Annual Review of Ecology and Systematics 24, 353377.CrossRefGoogle Scholar
Wheelwright, NT (1985) Competition for dispersers, and the timing of flowering and fruiting in a guild of tropical trees. Oikos 44, 465477.CrossRefGoogle Scholar
Wheelwright, NT (1986) A seven-year study of individual variation in fruit production in tropical bird-dispersed tree species in the family Lauraceae. In Estrada, A, Flemming, TH (eds), Frugivores and Seed Dispersal (pp. 1935). Dordrecht, Netherlands: Junk Publishers.CrossRefGoogle Scholar
Williams-Linera, G (1997) Phenology of deciduous and broadleaved-evergreen tree species in a Mexican tropical lower montane forest. Global Ecology and Biogeography Letters 6, 115127.CrossRefGoogle Scholar
Williams-Linera, G, Alvarez-Aquino, C and Tolome, J (2021) Tree damage, growth and phenology after a hurricane in a tropical dry forest in Veracruz. Revista Mexicana de Ciencias Forestales 12, 185201. https://doi.org/10.29298/rmcf.v12i67.858 CrossRefGoogle Scholar
Wootton, A (2022) Relaciones entre tendencias climáticas, patrones fenológicos y abundancia del quetzal en El Triunfo, Chiapas. (Unpublished doctoral thesis). El Colegio de la Frontera Sur, San Cristóbal de las Casas, Mexico.Google Scholar
Wootton, A, Enríquez, PL and Navarrete-Gutiérrez, D (2023) Regional patterns of vegetation, temperature, and rainfall trends in the coastal mountain range of Chiapas, Mexico. Atmósfera 36, 91122. https://doi.org/10.20937/ATM.53026 Google Scholar
Wunderle, JM (1995) Responses of bird populations in a Puerto Rican forest to Hurricane Hugo: the first 18 months. The Condor 97, 879896.CrossRefGoogle Scholar
Xu, K and Servedio, MR (2021) The evolution of flower longevity in unpredictable pollination environments. Journal of Evolutionary Biology 34, 17811792. https://doi.org/10.1111/jeb.13936 CrossRefGoogle ScholarPubMed
Zárate-Cuevas, L, Núñez-López, NM, Cuevas-Guzmán, R, Morales-Arias, JG, Sánchez-Rodríguez, EV, Guzmán-Hernández, L and Solís Magallanes, JA (2022) Fenología reproductiva de árboles en una zona montañosa del occidente de México. Revista Mexicana de Ciencias Forestales 13, 155176. https://doi.org/10.29298/rmcf.v13i69.1176 CrossRefGoogle Scholar
Zimmerman, JK, Wright, SJ, Calderón, O, Pagan, MA and Paton, S (2007) Flowering and fruiting phenologies of seasonal and aseasonal neotropical forests: the role of annual changes in irradiance. Journal of Tropical Ecology 23, 231251. https://doi.org/10.1017/S0266467406003890 CrossRefGoogle Scholar
Figure 0

Figure 1. Photos of the 21 tree species included in this study in the cloud forest of polygon 1 of El Triunfo, Mexico. Species shown are as follows: (1) Ocotea chiapensis, (2) Nectandra rudis, (3) Licaria excelsa, (4) Ocotea acuminatissima, (5) Cinnamomum zapatae, (6) Saurauia madrensis, (7) Saurauia yasicae, (8) Conostegia volcanalis, (9) Citharexylum mocinnii, (10) Hedyosmum mexicanum, (11) Ardisia compressa, (12) Ardisia verapazensis, (13) Morus insignis, (14) Trophis cuspidata, (15) Frangula capreifolia, (16) Symplococarpun purpusii, (17) Dendropanax arboreus, (18) Clusia salvinii, (19) Prunus brachybotrya, (20) Prunus tetradenia, and (21) Eugenia capuli.

Figure 1

Figure 2. Circular histograms of flowering, unripe fruiting, and ripe fruiting intensity in the zoochorous community in El Triunfo, Mexico, during April 2019–March 2020. Months without observations but including estimated flowering and fruiting values are shown with an E. Arrows indicate the degree of seasonality (r value). Numbers in histograms are the sums of intensity scores for all trees observed in the study.

Figure 2

Figure 3. Circular histograms of number of ripe fruits in the zoochorous tree community in El Triunfo, Mexico, during: (1992) January–December 1992, (1993) January–December 1993 (Solórzano et al.2000), and April 2019–March 2020 (2019–2020) in the upper row; and April, May, and December 2019 and January–March 2020 (2020), and December–May 2021 (2021) in the lower row. Months without observations but including estimated flowering and fruiting values are shown with an E. Arrow length indicate the degree of seasonality (significant r value; Table S3). Numbers in histograms are sums of the logarithmically transformed number of ripe fruits estimated monthly in all trees observed.

Figure 3

Table 1. Synchronization of flowering, unripe fruiting, and ripe fruiting in 12 species and the overall zoochorous community in El Triunfo, Mexico. Values range from 0 representing no synchronization of phenophases and 1 full synchronization

Figure 4

Table 2. Results of the best-fitting models for the relations between phenophases (flowering, unripe fruiting, ripe fruiting, and number of fruits) and climate variables in El Triunfo, Mexico, using generalized linear mixed model analysis. Climate variables are monthly rainfall (rain), minimum daily temperature (Tmin), maximum daily temperature (Tmax), and monthly averages of daily solar radiation (solar). * Models with a ∆AIC > 2.0 were considered significant for the best fit

Supplementary material: File

Wootton et al. supplementary material 1

Wootton et al. supplementary material
Download Wootton et al. supplementary material 1(File)
File 128.9 KB
Supplementary material: File

Wootton et al. supplementary material 2

Wootton et al. supplementary material
Download Wootton et al. supplementary material 2(File)
File 49.6 KB
Supplementary material: File

Wootton et al. supplementary material 3

Wootton et al. supplementary material
Download Wootton et al. supplementary material 3(File)
File 57.1 KB