Lianas have more acquisitive traits than trees in a dry but not in a wet forest

Medina‐Vega, José A.; Bongers, Frans; Poorter, Lourens; Schnitzer, Stefan A.; Sterck, Frank J.

doi:10.1111/1365-2745.13644

Cited by 31 publications

(48 citation statements)

References 175 publications

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“…In tropical semideciduous and deciduous forests, a short C gain window during the rainy season occurs due to the reduced leaf longevity (Chaturvedi et al, 2011). It has been widely observed that species from seasonal forests display high SLA and N content, whereas low leaf thickness, mostly due to the presence of drought‐avoiding species (Reich et al, 1997; Eamus, 1999; Wright et al, 2001; Givnish, 2002; Santiago et al, 2004; Powers & Tiffin, 2010; Souza et al, 2020; Medina‐Vega et al, 2021). This suite of leaf traits characterizes the “fast” resource use strategy (acquisitive leaves) in the global leaf economic spectrum (Díaz et al, 2016), which together contribute to maximizing photosynthesis when water is available (Eamus, 1999; Wright et al, 2001; Givnish, 2002; Chaturvedi et al, 2011; Souza et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot

Silva

Souza

Vitória

2021

J Vegetation Science

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Questions How is community functional composition associated with environmental and historical factors and how is this relationship mediated by spatial and phylogenetic autocorrelation? Location Atlantic Forest of South America. Methods We compiled abundance data of 2,122 species (most trees) distributed across 281 communities, seven functional traits, and 29 environmental and historical predictors. We mapped traits using community‐weighted means, and related traits to predictors by combining the fourth‐corner and the extended RLQ approaches. Results We found that decreases in rainfall, soil nutrition, biome stability in the last 120 kyr, and the increase in thermal variability were associated with high specific leaf area (SLA) and leaf N content, and reduced leaf thickness. In addition, increased temperature and soil sand content, and low biome stability in the last 21 kyr were associated with high wood density and leaf dry matter content, and reduced maximum plant height. Tree communities rich in taxa with N‐rich thin leaves and high SLA were mostly located in semideciduous and deciduous forests (e.g., Fabaceae), while communities rich in taxa with N‐poor thick leaves and low SLA were mostly found in rain forests (e.g., Myrtaceae and Lauraceae). Species with short stature, high wood density and heavy leaves were particularly abundant in the northern part of the Atlantic Forest (e.g., Myrtaceae), whereas tall species with light wood and leaves were abundant in the south (e.g., Lauraceae). There was not a particular direction in which seed dry mass increased most in response to predictors. Conclusions Our study reinforces the view that the multifaceted nature of community assembly needs analytical approaches that integrate abundance, functional, phylogenetic, and spatial data to properly understand how environmental and historical factors determine the dominance of functional traits. The observed patterns suggest that different regions of a given biome function in different ways, and probably provide different ecosystem services.

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Section: Discussionmentioning

confidence: 99%

Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot

Silva

Souza

Vitória

2021

J Vegetation Science

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“…The wind-dispersed comose seeds, then, might have favored twining plants to disperse and occupy open and semi-arid habitats. Twining plants seem to have greater capacities for the uptake and transportation of water and are more competitive than trees in high-light, nutrientrich environments, such as the seasonally dry forests (Medina-Vega et al, 2021). Xylem adaptations to drought and cold show similar trends and possibly contributed to rapid diversification events in several lineages of angiosperms in association with the global cooling and aridification, especially after the mid-Miocene climatic optimum (Folk et al, 2020).…”

Section: Potential Key Drivers Of Apocynaceae Diversificationmentioning

confidence: 99%

Evolution of Dispersal, Habit, and Pollination in Africa Pushed Apocynaceae Diversification After the Eocene-Oligocene Climate Transition

et al. 2021

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Apocynaceae (the dogbane and milkweed family) is one of the ten largest flowering plant families, with approximately 5,350 species and diverse morphology and ecology, ranging from large trees and lianas that are emblematic of tropical rainforests, to herbs in temperate grasslands, to succulents in dry, open landscapes, and to vines in a wide variety of habitats. Despite a specialized and conservative basic floral architecture, Apocynaceae are hyperdiverse in flower size, corolla shape, and especially derived floral morphological features. These are mainly associated with the development of corolline and/or staminal coronas and a spectrum of integration of floral structures culminating with the formation of a gynostegium and pollinaria—specialized pollen dispersal units. To date, no detailed analysis has been conducted to estimate the origin and diversification of this lineage in space and time. Here, we use the most comprehensive time-calibrated phylogeny of Apocynaceae, which includes approximately 20% of the species covering all major lineages, and information on species number and distributions obtained from the most up-to-date monograph of the family to investigate the biogeographical history of the lineage and its diversification dynamics. South America, Africa, and Southeast Asia (potentially including Oceania), were recovered as the most likely ancestral area of extant Apocynaceae diversity; this tropical climatic belt in the equatorial region retained the oldest extant lineages and these three tropical regions likely represent museums of the family. Africa was confirmed as the cradle of pollinia-bearing lineages and the main source of Apocynaceae intercontinental dispersals. We detected 12 shifts toward accelerated species diversification, of which 11 were in the APSA clade (apocynoids, Periplocoideae, Secamonoideae, and Asclepiadoideae), eight of these in the pollinia-bearing lineages and six within Asclepiadoideae. Wind-dispersed comose seeds, climbing growth form, and pollinia appeared sequentially within the APSA clade and probably work synergistically in the occupation of drier and cooler habitats. Overall, we hypothesize that temporal patterns in diversification of Apocynaceae was mainly shaped by a sequence of morphological innovations that conferred higher capacity to disperse and establish in seasonal, unstable, and open habitats, which have expanded since the Eocene-Oligocene climate transition.

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“…However, investigation at the leaf scale shows that our ability to differentiate lianas and trees based on spectral properties might depend on forest type, with detectable differences in dry forests (Guzmán Q. and Sanchez-Azofeifa, 2021) but not in wet forests (Sánchez-Azofeifa et al, 2009). Similarly, liana leaves have several distinct chemical and structural properties compared to trees (Asner and Martin, 2012; Werden et al, 2018), however differences appear mediated by climatic factors, depending on temperature and being minimized in wetter forests (Asner and Martin, 2012; Medina-Vega et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

Why can we detect lianas from space?

Visser

Detto

Meunier

et al. 2021

Preprint

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Lianas are found in virtually all tropical forests and have strong impacts on the forest carbon cycle by slowing tree growth, increasing tree mortality and arresting forest succession. In a few local studies, ecologists have successfully differentiated lianas from trees using various remote sensing platforms including satellite images. This demonstrates a potential to use remote sensing to investigate liana dynamics at spatio-temporal scales beyond what is currently possible with ground-based inventory censuses. However, why do liana-infested tree crowns and forest stands display distinct spectral signals? And is the spectral signal of lianas only locally unique or consistent across continental and global scales? Unfortunately, we are not yet able to answer these questions, and without such an understanding the limitations and caveats of large-scale application of automated classifiers cannot be understood. Here, we tackle the questions of why we can detect lianas from airborne and spaceborne remote sensing platforms. We identify whether a distinct spectral distribution exists for lianas, when compared to their tree hosts, at the leaf, canopy and stand scales in the solar spectrum (400 to 2500 nm). To do so, we compiled databases of (i) leaf reflectance spectra for over 4771 individual leaves of 571 species, (ii) fine-scale (~1m2) surface reflectance from 999 tree canopies characterized by different levels of liana infestation in Panama and Malaysia, and (iii) coarse-scale (>100 m2) surface reflectance from hundreds of hectares of heavily infested liana forest stands in French Guiana and Bolivia. Using these data, we find consistent spectral signal of liana-infested canopies across sites with a mean inter-site correlation of 89% (range 74-94%). However, as we find no consistent difference between liana and tree leaves, a distinct liana spectral signal appears to only manifests at the canopy and stand scales (>1m2). To better understand this signal, we implement mechanistic radiative transfer models capable of modeling the vertically stratificatied non-linear mixing of spectral signals intrinsic to lianas infestation of forest canopies. Next, we inversely fit the models to observed spectral signals of lianas at all scales to identify key biochemical or biophysical processes. We then corroborate our model results with field data on liana leaf chemistry and canopy structural properties. Our results suggest that a liana-specific spectral distribution arises due to the combination of cheaply constructed leaves and efficient light interception. A model experiment revealed that the spectral distribution was most sensitive to lower leaf and water mass per unit area, affecting the absorption of NIR and SWIR radiation, and a more planophile (flatter) leaf angle distribution. Finally, we evaluate the theoretical discernibility of lianas from trees and how this varies with remote sensing platforms and resolution. We end by discussing the potential, limitations and risks of applying automated classifiers to detect lianas from remotely sensed data at large scales.

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Lianas have more acquisitive traits than trees in a dry but not in a wet forest

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 31 publications

References 175 publications

Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot

Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot

Evolution of Dispersal, Habit, and Pollination in Africa Pushed Apocynaceae Diversification After the Eocene-Oligocene Climate Transition

Why can we detect lianas from space?

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