Phenology has achieved a prominent position in current scenarios of global change research given its role in monitoring and predicting the timing of recurrent life cycle events. However, the implications of phenology to environmental conservation and management remain poorly explored. Here, we present the first explicit appraisal of how phenology -a multidisciplinary science encompassing biometeorology, ecology, and evolutionary biology -can make a key contribution to contemporary conservation biology. We focus on shifts in plant phenology induced by global change, their impacts on species diversity and plantanimal interactions in the tropics, and how conservation efforts could be enhanced in relation to plant resource organization. We identify the effects of phenological changes and mismatches in the maintenance and conservation of mutualistic interactions, and examine how phenological research can contribute to evaluate, manage and mitigate the consequences of land-use change and other natural and anthropogenic disturbances, such as fire, exotic and invasive species. We also identify cutting-edge tools that can improve the spatial and temporal coverage of phenological monitoring, from satellites to drones and digital cameras. We highlight the role of historical information in recovering long-term phenological time series, and track climate-related shifts in tropical systems. Finally, we propose a set of measures to boost the contribution of phenology to conservation science. We advocate the inclusion of phenology into predictive models integrating evolutionary history to identify species groups that are either resilient or sensitive to future climatechange scenarios, and understand how phenological mismatches can affect community dynamics, ecosystem services, and conservation over time. We hereby submit the revised draft of our 'Perspectives' manuscript entitled "Linking plant phenology to conservation biology" to which we now incorporate the rather minor changes suggested by the reviewers. While responding to those very positive comments, we also indicate how we have incorporated the reviewers' remarks. UNIVERSIDADE ESTADUAL PAULISTAWe thank you and the reviewers again for all the suggestions that have improved our The MS is well written, integrates interesting different aspects of plant phenology and provide a guide to include phenology in prospective long-term studies and management plans. Therefore the study is of general interest for a wide audience, particularly for Biological Conservation readers.Next, I suggest some changes to improve the current version of the MS 1. Authors comment the effect of climate and land use change on Section 4. For example, they argue that edge effect "increase of flowering and fruiting activity" (Line #389) or fragmentation affect reproductive success. Yet, these are functional responses of plant populations to different types of disturbances/changes, but they do not necessary entail changes in phenology. Please, review the MS and make sure that you only include ...

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The deciduousness of tropical trees and communities depend on ecosystems characteristics such as plant species diversity, and strength of the dry season. Based on seven years of phenological observations, we provide the first long‐term description of leafing patterns of a woody cerrado community, aiming to investigate (1) the leaf exchange strategies considering the interannual variation in the degree of deciduousness of individuals and species and quantify the community deciduousness; (2) the relationship between interannual patterns of leaf fall and leaf flush according to the species’ leaf exchange strategies and climate; (3) the onset of cerrado growing season and its relation to climate seasonality. To detect seasonality and leafing onset we applied circular statistics and to understand the relationships between environmental predictors and leaf exchange strategies, we used generalized additive models. From 106 species observed, we classified 69 as deciduous (26 species), semi‐deciduous (25) or evergreen (18) and defined the studied cerrado as a semi‐deciduous vegetation. Leaf phenology was markedly seasonal and similar among years. Leaf fall peaked in the dry season, and leaf flush in the dry‐to‐wet transition. Leaf fall patterns related to temperature and leaf flush to day length and rainfall. Semi‐deciduous and deciduous species were more constrained by climate than the evergreen ones. The cerrado growing season started in the dry‐to‐wet season transition. Interannual variations in rainfall and temperature affected the individuals’ and, consequently, species’ degree of deciduousness, highlighting individual and species variability, and suggesting that cerrado leafing patterns are likely susceptible to future climate change scenarios.

Rupestrian grasslands are biodiverse, evolutionary old vegetation complexes that harbor more than 5000 species of vascular plants and one of the highest levels of plant endemism in the world. Growing on nutrient-impoverished soils and under harsh environmental conditions, these mountaintop ecosystems were once spared from major human interventions of agriculture and intensive cattle ranching. However, in Brazil, rupestrian grasslands have experienced one of the most extreme land use changes among all Brazilian ecosystems, suffering from ill policies leading to intense mining activities, uncontrolled tourism, and unplanned road construction. Indeed, the discovery of large mineral reserves, the adoption of ineffective conservation policies, and, going forward, climate change, are Communicated by David Hawksworth.

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.

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Nowadays, global warming and its resulting environmental changes is a hot topic in different biology research area. Phenology is one effective way of tracking such environmental changes through the study of plant's periodic events and their relationship to climate. One promising research direction in this area relies on the use of vegetation images to track phenology changes over time. In this scenario, the creation of effective image-based plant identification systems is of paramount importance. In this paper, we propose the use of a new representation of time series to improve plants recognition rates. This representation, called recurrence plot (RP), is a technique for nonlinear data analysis, which represents repeated events on time series into a two-dimensional representation (an image). Therefore, image descriptors can be used to characterize visual properties from this RP images so that these features can be used as input of a classifier. To the best of our knowledge, this is the first work that uses recurrence plot for plant recognition task. Performed experiments show that RP can be a good solution to describe time series. In addition, in a comparison with visual rhythms (VR), another technique used for time series representation, RP shows a better performance to describe texture properties than VR. On the other hand, a correlation analysis and the adoption of a well successful classifier fusion framework show that both representations provide complementary information that is useful for improving classification accuracies.