The World's Tallest Tropical Tree in Three Dimensions

Structural coloration is widespread in the marine environment. Within the large variety of marine organisms, macroalgae represent a diverse group of more than 24 000 species. Some macroalgae have developed complex optical responses using different nanostructures and material compositions. In this review, we describe the mechanisms that are employed to produce structural color in algae and provide a discussion on the functional relevance by analyzing the geographical distribution and ecology in detail. In contrast to what is observed in the animal kingdom, we hypothesize that structural color in algae predominantly functions for a non‐communicative purpose, most likely protection from radiation damage, e.g., by harmful UV light. We suggest that the presence of structural color in algae is likely influenced by local factors such as radiation intensity and turbidity of the water.

Growing evidence suggests that liana competition with trees is threatening the global carbon sink by slowing the recovery of forests following disturbance. A recent theory based on local and regional evidence further proposes that the competitive success of lianas over trees is driven by interactions between forest disturbance and climate. We present the first global assessment of liana–tree relative performance in response to forest disturbance and climate drivers. Using an unprecedented dataset, we analysed 651 vegetation samples representing 26,538 lianas and 82,802 trees from 556 unique locations worldwide, derived from 83 publications. Results show that lianas perform better relative to trees (increasing liana‐to‐tree ratio) when forests are disturbed, under warmer temperatures and lower precipitation and towards the tropical lowlands. We also found that lianas can be a critical factor hindering forest recovery in disturbed forests experiencing liana‐favourable climates, as chronosequence data show that high competitive success of lianas over trees can persist for decades following disturbances, especially when the annual mean temperature exceeds 27.8°C, precipitation is less than 1614 mm and climatic water deficit is more than 829 mm. These findings reveal that degraded tropical forests with environmental conditions favouring lianas are disproportionately more vulnerable to liana dominance and thus can potentially stall succession, with important implications for the global carbon sink, and hence should be the highest priority to consider for restoration management.

The marine world is incredibly rich in brilliant and intense colours. Photonic structures are found in many different species and provide extremely complex optical responses that cannot be achieved solely by pigments. In this study we examine the cuticular structure of the red alga Chondrus crispus (Irish Moss) using anatomical and optical approaches. We experimentally measure the optical response of the multilayer structure in the cuticle. Using finite-difference time-domain modelling, we demonstrate conclusively for the first time that the dimensions and organisation of lamellae are responsible for the blue structural colouration on the surface of the fronds. Comparison of material along the apical-basal axis of the frond demonstrates that structural colour is confined to the tips of the thalli and show definitively that a lack of structural colour elsewhere corresponds with a reduction in the number of lamellae and the regularity of their ordering. Moreover, by studying the optical response for different hydration conditions, we demonstrate that the cuticular structure is highly porous and that the presence of water plays a critical role in its ability to act as a structural light reflector.

Lianas (woody vines) are abundant and diverse, particularly in tropical ecosystems. Lianas use trees for structural support to reach the forest canopy, often putting leaves above their host tree. Thus they are major parts of many forest canopies. Yet, relatively little is known about distributions of lianas in tropical forest canopies, because studying those canopies is challenging. This knowledge gap is urgent to address because lianas compete strongly with trees, reduce forest carbon uptake and are thought to be increasing, at least in the Neotropics. Lianas can be difficult to study using traditional field methods. Their pliable stems often twist and loop through the understorey, making it difficult to assess their structure and biomass, and the sizes and locations of their crowns. Furthermore, liana stems are commonly omitted from standard field surveys. Remote sensing of lianas can help overcome some of these obstacles and can provide critical insights into liana ecology, but to date there has been no systematic assessment of that contribution. We review progress in studying liana ecology using ground‐based, airborne and space‐borne remote sensing in four key areas: (i) spatial and temporal distributions, (ii) structure and biomass, (iii) responses to environmental conditions and (iv) diversity. This demonstrates the great potential of remote sensing for rapid advances in our knowledge and understanding of liana ecology. We then look ahead, to the possibilities offered by new and future advances. We specifically consider the data requirements, the role of technological advances and the types of methods and experimental designs that should be prioritised. Synthesis. The particular characteristics of the liana growth form make lianas difficult to study by ground‐based field methods. However, remote sensing is well suited to collecting data on lianas. Our review shows that remote sensing is an emerging tool for the study of lianas, and will continue to improve with recent developments in sensor and platform technology. It is surprising, therefore, how little liana ecology research has utilised remote sensing to date—this should rapidly change if urgent knowledge gaps are to be addressed. In short, liana ecology needs remote sensing.

The ability to accurately assess liana (woody vine) infestation at the landscape level is essential to quantify their impact on carbon dynamics and help inform targeted forest management and conservation action. Remote sensing techniques provide potential solutions for assessing liana infestation at broader spatial scales. However, their use so far has been limited to seasonal forests, where there is a high spectral contrast between lianas and trees. Additionally, the ability to align the spatial units of remotely sensed data with canopy observations of liana infestation requires further attention. We combined airborne hyperspectral and LiDAR data with a neural network machine learning classification to assess the distribution of liana infestation at the landscape‐level across an aseasonal primary forest in Sabah, Malaysia. We tested whether an object‐based classification was more effective at predicting liana infestation when compared to a pixel‐based classification. We found a stronger relationship between predicted and observed liana infestation when using a pixel‐based approach (RMSD = 27.0% ± 0.80) in comparison to an object‐based approach (RMSD = 32.6% ± 4.84). However, there was no significant difference in accuracy for object‐ versus pixel‐based classifications when liana infestation was grouped into three classes; Low [0–30%], Medium [31–69%] and High [70–100%] (McNemar’s χ² = 0.211, P = 0.65). We demonstrate, for the first time, that remote sensing approaches are effective in accurately assessing liana infestation at a landscape scale in an aseasonal tropical forest. Our results indicate potential limitations in object‐based approaches which require refinement in order to accurately segment imagery across contiguous closed‐canopy forests. We conclude that the decision on whether to use a pixel‐ or object‐based approach may depend on the structure of the forest and the ultimate application of the resulting output. Both approaches will provide a valuable tool to inform effective conservation and forest management.