Response to Verbeeck and Kearsley: addressing the challenges of including lianas in global vegetation models

Verbeeck and Kearsley (1) rightfully point out that global vegetation models would greatly benefit from implicitly including the effects of lianas. Recent experimental evidence that lianas substantially reduce the capacity of tropical forests to uptake and store carbon is compelling (2, 3). Furthermore, lianas are increasing relative to trees rapidly in many neotropical forests (4), which will further change the way that forests uptake, cycle, and store carbon

Lianas reduce carbon accumulation and storage in tropical forests

Tropical forests store vast quantities of carbon, account for a third of the carbon fixed by photosynthesis, and are a major sink in the global carbon cycle. Recent evidence suggests that competition between lianas (woody vines) and trees may reduce forest-wide carbon uptake. However, estimates of the impact of lianas on carbon dynamics of tropical forests are crucially lacking. Here, we used a large-scale liana removal experiment and found that, three years after liana removal, lianas reduced net above-ground carbon uptake (growth and recruitment minus mortality) by ~76% per year, mostly by reducing tree growth. The loss of carbon uptake due to liana-induced mortality was 4-times greater in the control plots were lianas were present, but high variation among plots prevented a significant difference among the treatments. Lianas altered how aboveground carbon was stored. In forests where lianas are present, the partitioning of forest aboveground net primary production is dominated by leaves (53.2% compared to 39.2% in liana-free forests) at the expense of woody stems (from 28.9% compared to 43.9%), resulting in a more rapid return of fixed carbon to the atmosphere. After three years of experimental liana removal, our results clearly demonstrate large differences in carbon cycling between forests with and without lianas. Combined with the recently reported increases in liana abundance, these results indicate that lianas are an important and increasing agent of change in the carbon dynamics of tropical forests

Effect of lianas on forest-level tree carbon accumulation does not differ between seasons: Results from a liana removal experiment in Panama

1. Lianas are prevalent in Neotropical forests, where liana-tree competition can be intense, resulting in reduced tree growth and survival. The ability of lianas to grow relative to trees during the dry season suggests that liana-tree competition is also strongest in the dry season. If correct, the predicted intensification of the drying trend over large areas of the tropics in the future may therefore intensify liana-tree competition, resulting in a reduced carbon sink function of tropical forests. However, no study has established whether the liana effect on tree carbon accumulation is indeed stronger in the dry than in the wet season. 2. Using six years of data from a large-scale liana removal experiment in Panama, we provide the first experimental test of whether liana effects on tree carbon accumulation differ between seasons. We monitored tree and liana diameter increments at the beginning of the dry and wet season each year to assess seasonal differences in forest-level carbon accumulation between removal and control plots. 3. We found that median liana carbon accumulation was consistently higher in the dry (0.52 Mg C ha-1 yr-1) than the wet season (0.36 Mg C ha-1 yr-1), and significantly so in three of the years. Lianas reduced forest-level median tree carbon accumulation more severely in the wet (1.45 Mg C ha-1 yr-1) than the dry (1.05 Mg C ha-1 yr-1) season in all years. However, the relative effect of lianas was similar between the seasons, with lianas reducing forest-level tree carbon accumulation by 46.9% in the dry and 48.5% in the wet season. 4. Synthesis: Our results provide the first experimental demonstration that lianas do not have a stronger competitive effect on tree carbon accumulation during the dry season. Instead, lianas compete significantly with trees during both seasons, indicating a large negative effect of lianas on forest-level tree biomass increment regardless of seasonal water stress. Longer dry seasons are unlikely to impact liana-tree competition directly; however, the greater liana biomass increment during dry seasons may lead to further proliferation of liana biomass in tropical forests, with consequences for their ability to store and sequester carbon

A view from above: Unmanned aerial vehicles (UAVs) provide a new tool for assessing liana infestation in tropical forest canopies

1. Tropical forests store and sequester large quantities of carbon, mitigating climate change. Lianas (woody vines) are important tropical forest components, most conspicuous in the canopy. Lianas reduce forest carbon uptake and their recent increase may, therefore, limit forest carbon storage with global consequences for climate change. Liana infestation of tree crowns is traditionally assessed from the ground, which is labour intensive and difficult, particularly for upper canopy layers.2. We used a lightweight unmanned aerial vehicle (UAV) to assess liana infestation of tree canopies from above. It was a commercially available quadcopter UAV with an integrated, standard three‐waveband camera to collect aerial image data for 150 ha of tropical forest canopy. By visually interpreting the images, we assessed the degree of liana infestation for 14.15 ha of forest for which ground‐based estimates were collected simultaneously. We compared the UAV liana infestation estimates with those from the ground to determine the validity, strengths, and weaknesses of using UAVs as a new method for assessing liana infestation of tree canopies.3. Estimates of liana infestation from the UAV correlated strongly with ground‐based surveys at individual tree and plot level, and across multiple forest types and spatial resolutions, improving liana infestation assessment for upper canopy layers. Importantly, UAV‐based surveys, including the image collection, processing, and visual interpretation, were considerably faster and more cost‐efficient than ground‐based surveys. 4. Synthesis and applications. Unmanned aerial vehicle (UAV) image data of tree canopies can be easily captured and used to assess liana infestation at least as accurately as traditional ground data. This novel method promotes reproducibility of results and quality control, and enables additional variables to be derived from the image data. It is more cost‐effective, time‐efficient and covers larger geographical extents than traditional ground surveys, enabling more comprehensive monitoring of changes in liana infestation over space and time. This is important for assessing liana impacts on the global carbon balance, and particularly useful for forest management where knowledge of the location and change in liana infestation can be used for tailored, targeted, and effective management of tropical forests for enhanced carbon sequestration (e.g., REDD+ projects), timber concessions, and forest restoration

Lianas decelerate tropical forest thinning during succession

The well-established pattern of forest thinning during succession predicts an increase in mean tree biomass with decreasing tree density. The forest thinning pattern is commonly assumed to be driven solely by tree-tree competition. The presence of non-tree competitors could alter thinning trajectories, thus altering the rate of forest succession and carbon uptake. We used a large-scale liana removal experiment over 7years in a 60- to 70-year-old Panamanian forest to test the hypothesis that lianas reduce the rate of forest thinning during succession. We found that lianas slowed forest thinning by reducing tree growth, not by altering tree recruitment or mortality. Without lianas, trees grew and presumably competed more, ultimately reducing tree density while increasing mean tree biomass. Our findings challenge the assumption that forest thinning is driven solely by tree-tree interactions; instead, they demonstrate that competition from other growth forms, such as lianas, slow forest thinning and ultimately delay forest succession

Detection of spatial and temporal patterns of liana infestation using satellite-derived imagery

Lianas (woody vines) play a key role in tropical forest dynamics because of their strong influence on tree growth, mortality and regeneration. Assessing liana infestation over large areas is critical to understand the factors that drive their spatial distribution and to monitor change over time. However, it currently remains unclear whether satellite-based imagery can be used to detect liana infestation across closed-canopy forests and therefore if satellite-observed changes in liana infestation can be detected over time and in response to climatic conditions. Here, we aim to determine the efficacy of satellite-based remote sensing for the detection of spatial and temporal patterns of liana infestation across a primary and selectively logged aseasonal forest in Sabah, Borneo. We used predicted liana infestation derived from airborne hyperspectral data to train a neural network classification for prediction across four Sentinel-2 satellite-based images from 2016 to 2019. Our results showed that liana infestation was positively related to an increase in Greenness Index (GI), a simple metric relating to the amount of photosynthetically active green leaves. Furthermore, this relationship was observed in different forest types and during (2016), as well as after (2017–2019), an El Niño-induced drought. Using a neural network classification, we assessed liana infestation over time and showed an increase in the percentage of severely (>75%) liana infested pixels from 12.9% ± 0.63 (95% CI) in 2016 to 17.3% ± 2 in 2019. This implies that reports of increasing liana abundance may be more wide-spread than currently assumed. This is the first study to show that liana infestation can be accurately detected across closed-canopy tropical forests using satellite-based imagery. Furthermore, the detection of liana infestation during both dry and wet years and across forest types suggests this method should be broadly applicable across tropical forests. This work therefore advances our ability to explore the drivers responsible for patterns of liana infestation at multiple spatial and temporal scales and to quantify liana-induced impacts on carbon dynamics in tropical forests globally

Lianas Significantly Reduce Aboveground and Belowground Carbon Storage: A Virtual Removal Experiment

Lianas are structural parasites of trees that cause a reduction in tree growth and an increase in tree mortality. Thereby, lianas negatively impact forest carbon storage as evidenced by liana removal experiments. In this proof-of-concept study, we calibrated the Ecosystem Demography model (ED2) using 3 years of observations of net aboveground biomass (AGB) changes in control and removal plots of a liana removal experiment on Gigante Peninsula, Panama. After calibration, the model could accurately reproduce the observations of net biomass changes, the discrepancies between treatments, as well as the observed components of those changes (mortality, productivity, and growth). Simulations revealed that the long-term total (i.e., above- and belowground) carbon storage was enhanced in liana removal plots (+1.2 kgC m–2 after 3 years, +1.8 kgC m–2 after 10 years, as compared to the control plots). This difference was driven by a sharp increase in biomass of early successional trees and the slow decomposition of liana woody tissues in the removal plots. Moreover, liana removal significantly reduced the simulated heterotrophic respiration (−24%), which resulted in an average increase in net ecosystem productivity (NEP) from 0.009 to 0.075 kgC m–2 yr–1 for 10 years after liana removal. Based on the ED2 model outputs, lianas reduced gross and net primary productivity of trees by 40% and 53%, respectively, mainly through competition for light. Finally, model simulations suggested a profound impact of the liana removal on the soil carbon dynamics: the simulated metabolic litter carbon pool was systematically larger in control plots (+51% on average) as a result of higher mortality rates and faster leaf and root turnover rates. By overcoming the challenge of including lianas and depicting their effect on forest ecosystems, the calibrated version of the liana plant functional type (PFT) as incorporated in ED2 can predict the impact of liana removal at large-scale and its potential effect on long-term ecosystem carbon storage

Making (remote) sense of lianas

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