Climatic thresholds and temporal decoupling drive reproductive phenology in neotropical cloud forests: A 36-year analysis
Data files
Sep 17, 2026 version files 1.95 MB
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Data_1983_20218_17_09_2026.csv
1.25 MB
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Data_1983_20218_17_09_2026.xlsx
671.83 KB
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README.md
11 KB
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Species_cloud_forest_2025_17_09_2026.csv
10.42 KB
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Species_cloud_forest_2025_17_09_2026.xlsx
7.73 KB
Abstract
Reproductive phenology influences ecosystem functioning and climate sensitivity in tropical montane cloud forests, but phase‑specific climatic thresholds and the temporal coupling between flowering and fruiting remain poorly quantified over decadal scales. We analyzed a 36‑year monthly record (1983‑2018) from a Venezuelan cloud forest (15 focal species) and NASA/POWER hydroclimatic data, integrating Random Forest models, regression‑tree threshold analysis, climate‑window sensitivity analyses, scale‑dependent coherence, species‑level trend analyses, and temporal models that account for seasonality and autocorrelation. In the complete seven‑variable model for 2001‑2018, precipitation was the dominant concurrent predictor of both flowering and fruiting, with regression‑tree thresholds of 32.57 and 88.01 mm month -1, respectively. A reduced model using only the three highest‑ranked predictors per phase recovered identical thresholds to the complete model; neither specification, however, remained stable under temporally structured cross‑validation. Sensitivity analyses supported the flowering threshold across model specifications, whereas fruiting was more model‑dependent and showed sensitivity to antecedent atmospheric conditions in the full period (excluding surface UVA irradiance). Flowering and fruiting showed strongest coherence at sub‑annual scales (peak at 8 months), while long‑term trajectories diverged: flowering declined and fruiting occurrence increased; both trends remained significant under seasonality‑adjusted models with autocorrelation‑robust errors and AR(1) sensitivity analyses. Species‑level analyses showed that flowering decline was broadly distributed but not ubiquitous, whereas the increase in fruiting occurrence concentrated in a subset of taxa. These results indicate temporal decoupling: within‑year reproductive coordination is preserved, while long‑term reproductive occurrence is reorganized across species, predictor sets, and climatic windows.
Overview
This dataset contains the phenological observations, climate records, and species trait information underlying the analyses reported in the manuscript (Ecography, ms. ECOG-08852).
The dataset is provided in both Microsoft Excel (.xlsx) and open-access comma-separated values (.csv) formats. The CSV files contain the same tabular data as the corresponding Excel files and are provided to facilitate accessibility, interoperability, and downstream analysis.
The dataset contains four files:
Data_1983_20218_17_09_2026.csv— open-access CSV version of the species-by-month reproductive phenology and concurrent climate records, 1983–2018.Data_1983_20218_17_09_2026.xlsx— Excel version of the species-by-month reproductive phenology and concurrent climate records, 1983–2018.Species_cloud_forest_2025_17_09_2026.csv— open-access CSV version of the taxonomy and functional reproductive traits of the 15 study species.Species_cloud_forest_2025_17_09_2026.xlsx— Excel version of the taxonomy and functional reproductive traits of the 15 study species.
All categorical and descriptive content in the deposited data files is in English. The Excel workbooks were rebuilt as plain tabular files without non-essential formatting, formulas, merged cells, highlighting, frozen panes, comments, figures, filters, or other spreadsheet elements that could interfere with accessibility or downstream analysis.
The analysis code that reproduces every table and figure from these data is archived separately in Figshare (see Related works below).
Study system
Reproductive phenology (flowering and fruiting) of 15 woody species monitored in a neotropical cloud forest. Monthly observations span 36 years (1983–2018).
Files 1–2: Data_1983_20218_17_09_2026.csv and Data_1983_20218_17_09_2026.xlsx
These two files contain the same phenological and climate dataset in different formats.
- Excel sheet name:
Data_1983_2018 - Data rows: 6,480 (one row per species x year x month observation)
- Columns: 23
- CSV encoding: UTF-8
- Missing/undetermined categorical information: the literal string
naor?is used where applicable or where a trait was not determined. - Surface UVA irradiance is unavailable before 2001 and is represented by
nain those records.
Column descriptions
| Column | Type | Units / codes | Description |
|---|---|---|---|
FRECUENCY_NUMBER |
integer | sequential record number | Record identifier in the species-by-month dataset. |
TAG |
string | 15 codes | Species tag identifier. |
SAMPLES |
integer | constant = 5 | Number of monitored individuals per species. |
FAMILY |
string | 12 families | Botanical family. |
SPECIE |
string | 15 species | Species scientific name. |
GROWTH |
string | Tree, Shrub, Climbing | Growth form. |
SEXUALITY |
string | Hermaphrodite, Dioecious, Andro-dioecious, Heterostyly, na | Sexual system. na = not determined. |
AUTOCOMPATIBILITY |
string | Self-incompatible, Self-compatible, na | Auto-compatibility. na = not determined. |
MATING_SYSTEM |
string | Obligate Xenogamy, Facultative Xenogamy, Facultative Xenogamy (?) | Mating system. (?) = inferred/uncertain. |
POLINITATION_SYNDROME |
string | Sphingophily, Melittophily, Myophily, and combinations of these syndromes | Pollination syndrome. |
SEED_DISPERSAL_SYNDROME |
string | Anemochory, Zoochory | Seed dispersal syndrome. |
YEAR |
integer | 1983–2018 | Calendar year. |
MONTH |
integer | 1–12 | Calendar month. |
MONTH_LETTER |
string | Jan–Dec | Three-letter month abbreviation. |
FLOWERS_BY_MONTH |
integer | phenological event count | Flowering intensity/count for that species-month. |
FRUITS_BY_MONTH |
integer | phenological event count | Fruiting intensity/count for that species-month. |
TEMPERATURE |
float | degrees Celsius | Monthly mean air temperature. |
PRECIPITATION |
float | mm | Monthly total precipitation. |
MONTHLY_SURFACE_UVA_IRRADIANCE |
float | W m^-2 | Monthly mean surface UVA irradiance. Available from 2001 onward; see limitation below. |
RELATIVE_HUMIDITY |
float | % | Monthly mean relative humidity. |
MONTHLY_SOIL_MOISTURE_0_10CM |
float | volumetric fraction | Monthly mean soil moisture, 0–10 cm layer. |
MONTHLY_SOIL_MOISTURE_10_20CM |
float | volumetric fraction | Monthly mean soil moisture, 10–20 cm layer. |
WS10M |
float | m s^-1 | Monthly mean wind speed at 10 m. |
Important limitation on UVA irradiance
Surface UVA irradiance (MONTHLY_SURFACE_UVA_IRRADIANCE) is only reliably
available from 2001 onward. For this reason, the full seven-predictor climate
model in the manuscript is restricted to 2001–2018 (n = 216 monthly records),
while no-UVA sensitivity models use the complete 1983–2018 series (n = 432
monthly records). This restriction is applied in the analysis code, not by
removing pre-2001 records from the deposited dataset.
Files 3–4: Species_cloud_forest_2025_17_09_2026.csv and Species_cloud_forest_2025_17_09_2026.xlsx
These two files contain the same taxonomy and functional-trait dataset in
different formats.
- Excel sheet name:
Species - Excel structure: row 1 contains a plain English descriptive title; column headers are on row 2. The analysis code reads this sheet with
header=1. - CSV structure: column headers are on the first row.
- Data rows: 15 (one per study species)
- Columns: 19
- CSV encoding: UTF-8
- Missing/undetermined categorical information:
?is used where applicable. - The former auxiliary Spanish-language sheet is not included in the curated version.
Column descriptions
| Column | Description |
|---|---|
No |
Species index, 1–15. |
Kingdom, Phylum, Class, Order, Family, Genus |
Taxonomic classification. |
Species |
Full accepted scientific name with authority. |
Distribution |
Geographic range: countries and subnational units, with WGSRPD-style region codes. |
Search link |
GBIF species page URL. |
Publication |
Original taxonomic publication reference. |
Growth |
Growth form: Tree, Shrub, Climbing. |
Sexuality |
Sexual system: Hermaphrodite, Andro-dioecious, Dioecious, Heterostyly, etc. |
Auto-compatibility |
Self-compatible or undetermined (?). |
Mating system |
Facultative Xenogamy or Obligate Xenogamy. |
Pollination syndrome |
Sphingophily, Melittophily, Myophily, Ornithophily, or combinations thereof. |
Seed dispersal syndrome |
Anemochory or Zoochory. |
Habitat |
Growth/habit descriptor recorded for the species. |
Geographical distribution |
Habitat category used in this dataset (Cloud forest). |
Methods summary
Monthly flowering and fruiting were scored per species. Climate variables were compiled from the corresponding monthly records. Analyses include Random Forest driver hierarchies, regression-tree climatic thresholds, wavelet coherence between flowering and fruiting, and long-term trend estimation (OLS and Mann-Kendall). Full methods are in the associated manuscript.
Software
Analyses were performed in Python 3.10+. The complete, deterministic pipeline (random_state = 42) is archived in Figshare (see Related works). The archived analysis script uses the Excel versions of the input datasets. No proprietary software is required to access the deposited tabular data; the CSV files can be read directly by standard text-processing and statistical software, and the Excel files can be read with spreadsheet applications or Python openpyxl/pandas libraries.
Related works
- Article: Ecography, https://doi.org/10.1002/ecog.08852 (relationship: this dataset is supplement to the article).
- Analysis code: archived in Figshare, https://doi.org/10.6084/m9.figshare.33715015 (relationship: this dataset is supplemented by the code).
License
This dataset is released under CC0 1.0 Universal (public domain dedication), in accordance with Dryad policy.