Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama

Abstract

In tropical regions, rainfall gradients often explain the abundance and distribution of plant species. For example, many tree and liana species adapted to seasonal drought are more abundant and diverse in seasonally‐dry forests, characterized by long periods of seasonal water deficit. Mean annual precipitation (MAP) is commonly used to explain plant distributions across climate gradients. However, the relationship between MAP and plant distribution is often weak, raising the question of whether other seasonal precipitation patterns better explain plant distributions in seasonally‐dry forests. In this study, we examine the relationship between liana abundance and multiple metrics of seasonal and annual rainfall distribution to test the hypothesis that liana density and diversity increase with increasing seasonal drought along a rainfall gradient across the isthmus of Panama. We found that a normalized seasonality index, which combines MAP and the variability of monthly rainfall throughout the year, was a significant predictor of both liana density and species richness, whereas MAP, rainfall seasonality and the mean dry season precipitation (MDP) were far weaker predictors. The strong response of lianas to the normalized seasonality index indicates that, in addition to the total annual amount of rainfall, how rainfall is distributed throughout the year is an important determinant of the hydrological conditions that favor liana proliferation. Our findings imply that changes in annual rainfall and rainfall seasonality will determine the future distribution and abundance of lianas. Models that aim to predict future plant diversity, distribution, and abundance may need to move beyond MAP to a more detailed understanding of rainfall variability at sub‐annual timescales.

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

“…Despite the fact that we only included two sites in this analysis, the modelling workflow and the new model development allow expanding simulations over a larger rainfall gradient in the future. Next steps should focus on the ability of ED2 to reproduce trends of liana abundance with dry season length and mean annual precipitation (Schnitzer & Bongers, 2011) or seasonality (Parolari et al., 2020) over a larger number of sites. This expansion to drier conditions should confirm the observed trend in this study of water dominating the liana versus tree competition.…”

Lianas maintain insectivorous bird abundance and diversity in a neotropical forest

“…Because lianas increase habitat heterogeneity, determining the factors that influence liana abundance in tropical forests may be critical to predict bird abundance and diversity accurately, particularly for the diverse guild of insectivorous birds. Liana abundance tends to increase with decreasing rainfall and increasing seasonality in tropical forests, varying twofold across a gradient from relatively aseasonal wet forest to seasonal moist forest (Schnitzer 2005, DeWalt et al 2015, Schnitzer 2018, Parolari et al 2020). Liana abundance is also high in young, regenerating tropical forests (Barry et al 2015), decreasing with forest age after 70–100 yr of forest regeneration (DeWalt et al 2000).…”

Beyond MAP: A guide to dimensions of rainfall variability for tropical ecology

“…Although tropical ecologists have often defaulted to using annual means to characterize rainfall regimes, a growing number of examples demonstrates that other dimensions of rainfall are either stronger predictors of spatial and temporal variation in ecological properties and processes than MAP, or that these dimensions can add substantial explanatory power after controlling for MAP (e.g., Davidar, Puyravaud, & Leigh, 2005;Ouédraogo et al, 2016;Parolari et al, 2019;Rungwattana et al, 2018;Tedesco et al, 2008;Williams & Middleton, 2008 Harris, Jones, Osborn, & Lister, 2014) and the National Oceanic and Atmospheric Administration (https://www.esrl.noaa.gov/psd/data/gridd ed/). Monthly, daily, or even hourly time series for locations of interest can be extracted from these datasets in a straightforward manner.…”

“…For example, hydrological seasonality indices are strong predictors of reproductive strategies of tropical fish (Tedesco et al., 2008), and rainfall seasonality indices explain brain size in African primates (van Woerden, van Schaik, & Isler, 2010). Liana abundance and diversity across tropical forests are more strongly related to a seasonality index than to either MAP or dry season length (Parolari et al., 2019). Though their applications have so far been limited, we propose that relative seasonality metrics may be more useful than dry season length or other measures of absolute seasonality for explaining geographic variation in functional traits and life history strategies for other tropical organisms, as well as ecosystem functions and their emergent properties.…”