Rethinking tropical phenology: insights from long‐term monitoring and novel analytical methods

Morellato, Leonor Patrícia Cerdeira; Abernethy, Katharine; Mendoza, Irene

doi:10.1111/btp.12562

Cited by 13 publications

(8 citation statements)

References 18 publications

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“…There are increasing numbers of long‐term phenology studies from tropical forests (e.g., Chen et al, ; Morellato, Abernethy, & Mendoza, ) including 18 seed trap studies using the CTFS‐ForestGeo protocols used here (see Table S6 in Anderson‐Teixeira et al, ). We hope our success and the success of Chen et al () will encourage others to use similar modeling approaches to evaluate hypothesized proximate cues with long‐term tropical phenology data sets.…”

Section: Discussionmentioning

confidence: 99%

A phenology model for tropical species that flower multiple times each year

Wright

Calderón

Muller‐Landau

2019

Ecological Research

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Phenology models developed for temperate and boreal plants predict a single, population‐level first flowering date for each year. These models cannot accommodate species that flower multiple times each year in humid tropical forests nor flowering data with census‐interval rather than daily temporal resolution. Here, we present a new model framework able to predict the timing of multiple annual flowering events from census data. We extend a recent model, which predicted tropical flowering probabilities as discrete events occurring on census dates, by integrating predicted flowering probabilities over all dates between censuses. We evaluate our model against 29 years of daily climate and weekly flowering records for Hybanthus prunifolius (Violaceae) and Handroanthus guayacan (Bignoniaceae) from Barro Colorado Island, Panama. Previous experiments demonstrate that both species flower shortly after a heavy, dry‐season rain interrupts an extended dry period. Our model captures this sequence of rainfall events. Best‐fit model parameters are consistent with previous experimental results. This match suggests the new model framework will provide novel insights for other humid tropical forest species.

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Section: Discussionmentioning

confidence: 99%

A phenology model for tropical species that flower multiple times each year

Wright

Calderón

Muller‐Landau

2019

Ecological Research

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“…There 165 are a number of different approaches to estimating plant phenology based on satellite measurements (e.g. see Bush et al, 2018;Peano et al, 2019;Morellato et al, 2018;Moulin et al, 1997;Zhang et al, 2006). Ultimately the applied technique depends on the application needs, and the approach followed here is sufficient to characterize the active https://doi.org/10.5194/bg-2022-25 Preprint.…”

Section: Growing Season Estimationmentioning

confidence: 99%

Observed Water- and Light-Limitation Across Global Ecosystems

Jonard

Feldman

Gianotti

et al. 2022

Preprint

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Abstract. With a changing climate, it is becoming increasingly critical to understand vegetation responses to limiting environmental factors. Here, we investigate the spatial and temporal patterns of light and water limitation on photosynthesis using an observational framework. Our study is unique in characterizing the nonlinear relationships between photosynthesis and water and light, acknowledging approximately two regime behavior (no limitation and varying degree of limitation). It is also unique in using an observational framework instead of using model-derived photosynthesis properties. We combine data from three different satellite sensors, i.e., solar-induced chlorophyll fluorescence (SIF) from TROPOMI, surface soil moisture from SMAP, and above-ground canopy density from MODIS. We find both single-regime and two-regime models describe SIF sensitivity to soil moisture and photosynthetically active radiation (PAR) across the globe. The distribution and strength of soil moisture limitation on SIF are mapped in the water-limited environments while distribution and strength of PAR limitations are mapped in the energy-limited environments. Two-regime behavior is detected in 73 % of the cases for water limitation on photosynthesis, while two-regime detection is much lower at 36 % for light limitation on photosynthesis. SIF sensitivity to PAR strongly increases along moisture gradients, reflecting mesic vegetation’s adaptation to making rapid usage of incoming light availability on the weekly timescales. The transition point detected between the two regimes is connected to soil type and mean annual precipitation for the SIF-soil moisture relationship and for the SIF-PAR relationship. These thresholds have therefore an explicit relation to properties of the landscape, although they may also be related to finer details of the vegetation and soil interactions not resolved by the spatial scales here. The simple functions and thresholds are emergent behaviors capturing the interaction of many processes. The observational thresholds and strength of coupling can be used as benchmark information for land surface and Earth system models, especially those that characterize gross primary production mechanisms and vegetation dynamics.

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“…Phenology is a branch of science associating the events of the life cycle of organisms with their biotic and abiotic determinants [1]. Detailed knowledge of phenological phenomena and their mechanisms facilitates the identification of changes involved in plant growth and yield.…”

Section: Introductionmentioning

confidence: 99%

“…Phenological phases can be established based on several types of observations (i.e., (1) direct visual observations by a human observer; (2) close-range near-surface measurements; and (3) satellite remote sensing) [71]. Direct visual observations of plant phenology have been carried out for over a century in many locations, and there are large observation networks in different regions of the world (e.g., the Pan European Phenology Network [266,267] and the National Phenology Network (NPN) [244] in the United States).…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

2022

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Analyses of climate change based on point observations indicate an extension of the plant growing season, which may have an impact on plant production and functioning of natural ecosystems. Analyses involving remote sensing methods, which have added more detail to results obtained in the traditional way, have been carried out only since the 1980s. The paper presents the results of a bibliometric analysis of papers related to the growing season published from 2000–2021 included in the Web of Science database. Through filtering, 285 publications were selected and subjected to statistical processing and analysis of their content. This resulted in the identification of author teams that mostly focused their research on vegetation growth and in the selection of the most common keywords describing the beginning, end, and duration of the growing season. It was found that most studies on the growing season were reported from Asia, Europe, and North America (i.e., 32%, 28%, and 28%, respectively). The analyzed articles show the advantage of satellite data over low-altitude and ground-based data in providing information on plant vegetation. Over three quarters of the analyzed publications focused on natural plant communities. In the case of crops, wheat and rice were the most frequently studied plants (i.e., they were analyzed in over 30% and over 20% of publications, respectively).

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Rethinking tropical phenology: insights from long‐term monitoring and novel analytical methods

Cited by 13 publications

References 18 publications

A phenology model for tropical species that flower multiple times each year

A phenology model for tropical species that flower multiple times each year

Observed Water- and Light-Limitation Across Global Ecosystems

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

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