Landscape-level disturbances, such as forest loss, can profoundly alter the functional composition and diversity of biotic assemblages. In fact, the landscape-moderated functional trait selection (LMFTS) hypothesis states that landscape-level disturbances may act as environmental filters that select a set of species with disturbance-adapted attributes while causing the loss of species with disturbance-sensitive attributes, ultimately compromising ecosystem functioning. However, the impact of landscape patterns on the functional composition and diversity of tropical regenerating trees (saplings) is unknown.

Using a multiscale approach to identify the best spatial scale (i.e. the scale of effect), we tested the effect of forest cover, matrix openness and forest patch density (fragmentation) on functional composition and functional diversity of tree saplings in old-growth forest patches (n = 59) in three Mexican rainforest regions with different degree of deforestation. For 368 species and ~23,000 individuals, we compiled information from global and national databases on six functional traits related to seed dispersal and plant establishment and calculated their community abundance-weighted mean (CWMs) and three complementary functional diversity indices.

Forest loss and matrix openness reduced functional richness and evenness, but only in the two most deforested regions. Overall, fragmentation had contrasting effects on functional diversity and composition, but correlated negatively with some functional traits in the most deforested region. Importantly, in the regions with high-to-intermediate degree of deforestation, functional composition experienced major changes: maximum height, seed mass, fruit size and wood density decreased, and SLA increased, in forest patches surrounded by open matrices in highly deforested and fragmented landscapes. This caused a shift of community traits towards more disturbed-adapted attributes.

Synthesis and applications. In agreement with the LMFTS hypothesis, our results confirm that landscape modifications in regions undergoing high and long-lasting deforestation greatly impoverish the functional composition and diversity of sapling communities. The shift from communities composed mainly by conservative attributes towards communities with a higher prevalence of disturbance-adapted attributes disrupts the future community structure and jeopardizes critical ecosystem functions. Management practices focused on preventing deforestation, increasing forest cover, and promoting treed matrices are necessary to preserve the functionality of these species-rich but increasingly threatened rainforests.

We worked in three rainforest regions from southeastern Mexico with different patterns and history of land-use change: (1) Marqués de Comillas region (in Selva Lacandona rainforest, Chiapas) and labeled as low-deforestation region (LDR) in the database; (2) Los Tuxtlas rainforest (Veracruz), labeled as intermediate-deforestation region (IDR); and (3) Northern Chiapas, labeled as high-deforestation region (HDR). In each region, we selected 20 old-growth forest patches (i.e. 60 forest patches in total). Sampling was conducted in the dry season, from January to May 2018. At the centre of each forest patch, we established 25 circular plots of 1.60 m radius (8 m² each, which represents 200 m² sampled in each patch), in a grid of 5 × 5 plots with a 30 m separation between them. In each plot, all saplings (excluding palms and lianas) ≥ 30 cm in height and < 1 cm of diameter at breast height (DBH) were identified and counted. Then, we summed up the values obtained for the 25 plots to obtain a single value for each forest patch (i.e. sampling unit).

For each forest patch (i.e. community), we collected six functional traits that represent the whole plant trait economic spectrum, play a key role in plant regeneration and are sensitive to environmental modifications: tree maximum height (Hmax, m), seed mass (SM, mg), specific leaf area (SLA, mm2/mg), fruit size (FS, mm), wood density (WD, g/cm3) and dispersal syndrome (DS). We then calculated the community abundance-weighted mean (CWM) for each of the afore-mentioned functional traits. We also calculated three complementary indices of functional diversity (Villéger et al., 2008): functional richness (FRic), functional evenness (FEve) and functional divergence (FDiv). FRic represents the amount of functional space occupied by the community and is based on the convex hull concept, which is the minimum convex hull that includes all species considered. FEve represents the homogeneity in the distribution of species trait abundances of a community, so FEve decreases when species trait abundances are distributed less uniformly among the included species or when functional distances among species are less regular. Finally, FDiv measures how far the abundances of the different species are from the centre of the functional space.

Concerning the landscape variables, we estimated four landscape metrics: two metrics of landscape composition (i.e., FC = forest cover, MO = matrix openness) and two metrics of landscape configuration (i.e., PD = patch density, ED = forest edge density). Landscape variables were assessed in 13 concentric landscapes (i.e. buffers or landscape areas) of 100- to 1300-m radius (at 100-m intervals) from the centre of each sampling site. This multi-scale approach was used in order to identify the spatial scale at which the relationship between each response variable and each landscape metric is strongest (i.e. scale of effect; Jackson & Fahrig, 2015). Forest cover was estimated by dividing the total amount of old-growth forest area in the landscape by the landscape area × 100 (%). Matrix openness was calculated as the percentage of the matrix covered by open areas (i.e. cattle pastures, annual crops, water bodies and human settlements). Patch density was calculated as the number of old-growth forest patches in the landscape divided by the landscape area (n/ha). Edge density was estimated as the length of the perimeter of all old-growth forest patches in the landscape divided by the landscape area (m/ha).

References:

Jackson, H. B. & Fahrig, L. 2015. Are ecologists conducting research at the optimal scale? Global Ecology and Biogeography, 24, 52–63.

Villéger, S., Mason, N. W. H., & Mouillot, D. (2008). New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology, 89, 2290–2301.