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

Here, we introduce the Special Section (SS) on long‐term monitoring and new analytical methods in tropical phenology. The SS puts together nine original papers plus a synthesis, bringing significant advances and new insights into our understanding of tropical phenology across Africa and tropical America. The papers address environmental cues, methodological shortcomings, and provide innovative analytical approaches, opening new pathways, perspective and applications of tropical phenology for forest management and environmental monitoring. The SS is a substantial step toward a more comprehensive overview of trends in tropical phenology, as seven of nine studies evaluate >10‐yr data sets applying new methods of analysis such as hierarchical Bayesian models, generalized additive models, and Fourier analysis. We argue that it is essential to maintain ongoing monitoring programs and build a tropical phenology network at least for long‐term (>10 yr) study sites, providing the means for national and international financial support. Cross‐continental comparisons are now a primary goal, as we work toward a global vision of trends and shifts in tropical phenology in the Anthropocene

Beta diversity of plant-pollinator networks and the spatial turnover of pairwise interactions

Interactions between species form complex networks that vary across space and time. Even without spatial or temporal constraints mutualistic pairwise interactions may vary, or rewire, across space but this variability is not well understood. Here, we quantify the beta diversity of species and interactions and test factors influencing the probability of turnover of pairwise interactions across space. We ask: 1) whether beta diversity of plants, pollinators, and interactions follow a similar trend across space, and 2) which interaction properties and site characteristics are related to the probability of turnover of pairwise interactions. Geographical distance was positively correlated with plant and interaction beta diversity. We find that locally frequent interactions are more consistent across space and that local flower abundance is important for the realization of pairwise interactions. While the identity of pairwise interactions is highly variable across space, some speciespairs form interactions that are locally frequent and spatially consistent. Such interactions represent cornerstones of interacting communities and deserve special attention from ecologists and conservation planners alike.Fil: Carstensen, Daniel W.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Sabatino, Cristina Malena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; ArgentinaFil: Trøjelsgaard, Kristian. University Aarhus; Dinamarca. Aalborg University; DinamarcaFil: Morellato, Leonor Patricia C.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasi

Are native bees and Apis mellifera equally efficient pollinators of the rupestrian grassland daisy Aspilia jolyana (Asteraceae)?

Most angiosperms rely on animals for pollination, and insects, especially bees, are the most frequent pollinators. Many native Neotropical plants are frequently visited by the invasive honeybee (Apis mellifera), but its role in the pollination of these plants has been little investigated. We assessed the contribution of various floral visitors, including native bees and the honeybee, on the pollination of a generalist rupestrian grassland daisy, Aspilia jolyana (Asteraceae), in Serra do Cipó, Espinhaço Mountain Range, Brazil. We recorded floral visitors and measured the seed set resulting from one single visitation. We observed a total of 442 visits, mostly by bees, with Bombus pauloensis and Apis mellifera being the most common floral visitors. Other visitors included many other species of bees, flies, hummingbirds, wasps and butterflies. Pollinators significantly increased seed set in comparison to non-visited (bagged) capitula. Moreover, there was no difference among bee species/groups in their contribution to seed set. Thus, A. jolyana benefits from its generalized pollination strategy, and frequent bee visitors, including several native species and the invasive honeybee, are equally effective pollinators for this generalist daisy of rupestrian grassland

Climate change, in the framework of the constructal law

Here we present a simple and transparent alternative to the complex models of Earth thermal behavior under time-changing conditions. We show the one-to-one relationship between changes in atmospheric properties and time-dependent changes in temperature and its distribution on Earth. The model accounts for convection and radiation, thermal inertia and changes in albedo (ρ) and greenhouse factor (γ). The constructal law is used as the principle that governs the evolution of flow configuration in time, and provides closure for the equations that describe the model. In the first part of the paper, the predictions are tested against the current thermal state of Earth. Next, the model showed that for two time-dependent scenarios, (δρ = 0.002; δγ = 0.011) and (δρ = 0.002; δγ = 0.005) the predicted equatorial and polar temperature increases and the time scales are (Δ<i>T</i><sub>H</sub> = 1.16 K; Δ<i>T</i><sub>L</sub> = 1.11 K; 104 years) and (0.41 K; 0.41 K; 57 years), respectively. In the second part, a continuous model of temperature variation was used to predict the thermal response of the Earth's surface for changes bounded by δρ = δγ and δρ = −δγ. The results show that the global warming amplitudes and time scales are consistent with those obtained for δρ = 0.002 and δγ = 0.005. The poleward heat current reaches its maximum in the vicinity of 35° latitude, accounting for the position of the Ferrel cell between the Hadley and Polar Cells

Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks

Plant phenology studies rely on long-term monitoring of life cycles of plants. High-resolution unmanned aerial vehicles (UAVs) and near-surface technologies have been used for plant monitoring, demanding the creation of methods capable of locating, and identifying plant species through time and space. However, this is a challenging task given the high volume of data, the constant data missing from temporal dataset, the heterogeneity of temporal profiles, the variety of plant visual patterns, and the unclear definition of individuals' boundaries in plant communities. In this letter, we propose a novel method, suitable for phenological monitoring, based on convolutional networks (ConvNets) to perform spatio-temporal vegetation pixel classification on high-resolution images. We conducted a systematic evaluation using high-resolution vegetation image datasets associated with the Brazilian Cerrado biome. Experimental results show that the proposed approach is effective, overcoming other spatio-temporal pixel-classification strategies

Leafing patterns and drivers across seasonally dry tropical communities

Investigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees

Accuracy and limitations for spectroscopic prediction of leaf traits in seasonally dry tropical environments

Generalized assessments of the accuracy of spectroscopic estimates of ecologically important leaf traits such as leaf mass per area (LMA) and leaf dry matter content (LDMC) are still lacking for most ecosystems, and particularly for non-forested and/or seasonally dry tropical vegetation. Here, we tested the ability of using leaf reflectance spectra to estimate LMA and LDMC and classify plant growth forms within the cerrado and campo rupestre seasonally dry non-forest vegetation types of Southeastern Brazil, filling an existing gap in published assessments of leaf optical properties and plant traits in such environments. We measured leaf reflectance spectra from 1648 individual plants comprising grasses, herbs, shrubs, and trees, developed partial least squares regression (PLSR) models linking LMA and LDMC to leaf spectra (400–2500 nm), and identified the spectral regions with the greatest discriminatory power among growth forms using Bhattacharyya distances. We accurately predicted leaf functional traits and identified different growth forms. LMA was overall more accurately predicted (RMSE = 8.58%) than LDMC (RMSE = 9.75%). Our model including all sampled plants was not biased towards any particular growth form, but growth-form specific models yielded higher accuracies and showed that leaf traits from woody plants can be more accurately estimated than for grasses and forbs, independently of the trait measured. We observed a large range of LMA values (31.80–620.81 g/m2) rarely observed in tropical or temperate forests, and demonstrated that values above 300 g/m2 could not be accurately estimated. Our results suggest that spectroscopy may have an intrinsic saturation point, and/or that PLSR, the current approach of choice for estimating traits from plant spectra, is not able to model the entire range of LMA values. This finding has very important implications to our ability to use field, airborne, and orbital spectroscopic methods to derive generalizable functional information. We thus highlight the need for increasing spectroscopic sampling and research efforts in drier non-forested environments, where environmental pressures lead to leaf adaptations and allocation strategies that are very different from forested ecosystems. Our findings also confirm that leaf reflectance spectra can provide important information regarding differences in leaf metabolism, structure, and chemical composition. Such information enabled us to accurately discriminate plant growth forms in these environments regardless of lack of variation in leaf economic traits, encouraging further adoption of remote sensing methods by ecologists and allowing a more comprehensive assessment of plant functional diversity

A Change-Driven Image Foveation Approach for Tracking Plant Phenology

One of the challenges in remote phenology studies lies in how to efficiently manage large volumes of data obtained as long-term sequences of high-resolution images. A promising approach is known as image foveation, which is able to reduce the computational resources used (i.e., memory storage) in several applications. In this paper, we propose an image foveation approach towards plant phenology tracking where relevant changes within an image time series guide the creation of foveal models used to resample unseen images. By doing so, images are taken to a space-variant domain where regions vary in resolution according to their contextual relevance for the application. We performed our validation on a dataset of vegetation image sequences previously used in plant phenology studies

Soil profile, relief features and their relation to structure and distribution of Brazilian Atlantic rain forest trees

In tropical forests, the environmental heterogeneity can provide niche partitioning at local scales and determine the diversity and plant species distribution. Thus, this study aimed to investigate the variations of tree species structure and distribution in response to relief and soil profile features in a portion of the largest remnant of Brazilian Atlantic rain forest. All trees >= 5 cm diameter at breast height were recorded in two 0.99 ha plots. Topographic survey and a soil characterization were accomplished in both plots. Topsoil samples (0-20 cm) were taken from 88 quadrats and analyzed for chemical and particle size properties. Differences for both diversity and tree density were identified among three kinds of soils. A canonical correspondence analysis (CCA) indicated that the specific abundance varied among the three kinds of soils mapped: a shallow Udept - Orthent / Aquent gradient, probably due to differences in soil drainage. Nutrient content was less likely to affect tree species composition and distribution than relief, pH, Al3+, and soil texture. Some species were randomly distributed and did not show restriction to relief and soil properties. However, preferences in niche occupation detected in this study, derived from the catenary environments found, rise up as an important explanation for the high tree species diversity in tropical forests.FAPESPFAPESP [95/9626-0]UNESPUNESPCNPqCNPqCAPESCAPESUNESP Rio ClaroUNESP Rio Clar

The length of the dry season may be associated with leaf scleromorphism in cerrado plants

Apesar das limitações nutricionais e elevada acidez dos solos, a flora do cerrado é a mais rica entre as savanas. Muitas espécies lenhosas do cerrado possuem folhas escleromórficas e o nível de escleromorfismo foliar parece depender da disponibilidade de água e nutrientes no solo. Visando um melhor entendimento sobre a estrutura e funcionalidade da vegetação do cerrado, foram comparadas duas comunidades de cerrado sensu stricto: uma na região central do Brasil (Brasília, DF) e a outra na periferia sul (Itirapina, SP). Para tal, comparamos a duração da estação seca, a fertilidade do solo, as concentrações foliares de N, P, K, Ca e Mg e a área foliar específica (AFE) entre as duas comunidades do cerrado. A estação seca na periferia foi menor em relação à região central, e seu solo foi considerado mais fértil e mais ácido. A vegetação periférica apresentou maior AFE e apresentou maiores concentrações foliares de N, P, Ca e Mg. Baseado nestes resultados, propomos que a maior AFE observada na comunidade periférica se deve à menor duração da estação seca, a qual possibilita melhores condições para absorção de nutrientes do solo.Despite limitations of low fertility and high acidity of the soils, the cerrado flora is the richest amongst savannas. Many cerrado woody species show sclerophyllous leaves, which might be related to the availability of water and nutrients in the soil. To better understand the function and structure of cerrado vegetation within its own variations, we compared two cerrado communities: one in its core region in central Brazil (Brasília, DF) and the other on its southern periphery (Itirapina, SP). We contrasted the length of the dry season, soil fertility rates, leaf concentrations of N, P, K, Ca and Mg and the specific leaf area (SLA) between these communities. The dry season was shorter on the periphery, where the soil was more fertile although more acidic. Plants from the periphery showed higher SLA and higher leaf concentrations of N, P, Ca and Mg. We propose that the higher SLA of plants from the periphery is related to the shorter dry season, which allows better conditions for nutrient uptake