The response of lianas to 20 yr of nutrient addition in a Panamanian forest

Patterns and inferred causes of liana mortality in a tropical forest

Lianas are major contributors to tropical forest dynamics, yet we know little about their mortality. Using overlapping censuses of the lianas and trees across a 50 ha stand of moist tropical forest, we contrasted community-wide patterns of liana mortality with relatively well-studied patterns of tree mortality to quantify patterns of liana death and identify contributing factors. Liana mortality rates were 172% higher than tree mortality rates, but species-level mortality rates of lianas were similar to trees with 'fast' life-history strategies and both growth forms exhibited similar spatial and size-dependent patterns. The mortality rates of liana saplings (<2.1 cm in diameter), which represent about 50% of liana individuals, decreased with increasing disturbance severity and remained consistently low during post-disturbance stand thinning. In contrast, larger liana individuals and trees of all sizes had elevated mortality rates in response to disturbance and their mortality rates decreased over time since disturbance. Within undisturbed forest patches, liana mortality rates increased with increasing soil fertility in a manner similar to trees. The distinct responses of liana saplings to disturbance appeared to distinguish liana mortality from that of trees, whereas similarities in their patterns of death suggest that there are common drivers of woody plant mortality.

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 7 years 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.

Local canopy disturbance as an explanation for long-term increases in liana abundance

Canopy disturbance explains liana abundance and distribution within tropical forests and thus may also explain the widespread pattern of increasing liana abundance; however, this hypothesis remains untested. We used a 10-year study (2007-2017) of 117,100 rooted lianas in an old-growth Panamanian forest to test whether local canopy disturbance explains increasing liana abundance. We found that liana density increased 29.2% and basal area 12.5%. The vast majority of these increases were associated with clonal stem proliferation following canopy disturbance, particularly in liana-dense, low-canopy gaps, which had far greater liana increases than did undisturbed forest. Lianas may be ecological niche constructors, arresting tree regeneration in gaps and thus creating a high-light environment that favours sustained liana proliferation. Our findings demonstrate that liana abundance is increasing rapidly and their ability to proliferate via copious clonal stem production in canopy gaps explains much of their increase in this and possibly other tropical forests.

Lianas do not reduce tree biomass accumulation in young successional tropical dry forests

Young successional tropical forests are crucial in the global carbon cycle because they can quickly sequester large quantities of atmospheric carbon. However, lianas (woody vines) can significantly decrease biomass accumulation in young regenerating forests. Lianas are abundant in tropical dry forests, and thus we hypothesized that lianas reduce biomass accretion in dry forests. Lianas may be particularly detrimental to the growth of young trees, which are vulnerable to competition from lianas. Alternatively, lianas may have a stronger negative effect on the largest trees because lianas seek the high-light environment at the top of the forest canopy. We tested these hypotheses using a liana-removal experiment in 13 dry forest stands that ranged from 1 to 70 years in southwestern Panama. We measured biomass accumulation annually for more than 10,000 stems from 2013 to 2017. Contrary to our expectations, liana removal had no effect on tree biomass accumulation across our successional forests and throughout our study period. Liana removal did not benefit smaller trees or larger trees. Lianas did not increase biomass accumulation on recruits, and did not increase biomass loss due to mortality. Surprisingly, removing lianas had a negative effect on three out of 41 tree species. Lianas had no effect on biomass accumulation and loss, possibly because: (1) trees allocated resources to roots instead of stems, (2) trees and lianas partitioned water, (3) higher irradiance after liana removal reduced soil moisture, or (4) low water availability might have been such a strong stressor that it reduced plant-plant competition.

Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis

Despite their low contribution to forest carbon stocks, lianas (woody vines) play an important role in the carbon dynamics of tropical forests. As structural parasites, they hinder tree survival, growth and fecundity; hence, they negatively impact net ecosystem productivity and long-term carbon sequestration.Competition (for water and light) drives various forest processes and depends on the local abundance of resources over time. However, evaluating the relative role of resource availability on the interactions between lianas and trees from empirical observations is particularly challenging. Previous approaches have used labour-intensive and ecosystem-scale manipulation experiments, which are infeasible in most situations.We propose to circumvent this challenge by evaluating the uncertainty of water and light capture processes of a process-based vegetation model (ED2) including the liana growth form. We further developed the liana plant functional type in ED2 to mechanistically simulate water uptake and transport from roots to leaves, and start the model from prescribed initial conditions. We then used the PEcAn bioinformatics platform to constrain liana parameters and run uncertainty analyses.Baseline runs successfully reproduced ecosystem gas exchange fluxes (gross primary productivity and latent heat) and forest structural features (leaf area index, aboveground biomass) in two sites (Barro Colorado Island, Panama and Paracou, French Guiana) characterized by different rainfall regimes and levels of liana abundance.Model uncertainty analyses revealed that water limitation was the factor driving the competition between trees and lianas at the drier site (BCI), and during the relatively short dry season of the wetter site (Paracou). In young patches, light competition dominated in Paracou but alternated with water competition between the wet and the dry season on BCI according to the model simulations.The modelling workflow also identified key liana traits (photosynthetic quantum efficiency, stomatal regulation parameters, allometric relationships) and processes (water use, respiration, climbing) driving the model uncertainty. They should be considered as priorities for future data acquisition and model development to improve predictions of the carbon dynamics of liana-infested forests. Synthesis. Competition for water plays a larger role in the interaction between lianas and trees than previously hypothesized, as demonstrated by simulations from a process-based vegetation model.