Morphological consequences of climate change for resident birds in intact Amazonian rainforest

Abstract

Warming from climate change is expected to reduce body size of endotherms, but studies from temperate systems have produced equivocal results. Over four decades, we collected morphometric data on a nonmigratory understory bird community within Amazonian primary rainforest that is experiencing increasingly extreme climate. All 77 species showed lower mean mass since the early 1980s—nearly half with 95% confidence. A third of species concomitantly increased wing length, driving a decrease in mass:wing ratio for 69% of species. Seasonal precipitation patterns were generally better than temperature at explaining morphological variation. Short-term climatic conditions affected all metrics, but time trends in wing and mass:wing remained robust even after controlling for annual seasonal conditions. We attribute these results to pressures to increase resource economy under warming. Both seasonal and long-term morphological shifts suggest response to climate change and highlight its pervasive consequences, even in the heart of the world’s largest rainforest.

Fig. 1.. Bird body change and climate trends within undisturbed Amazonia.

(A) Capture locations (crosses) in primary forest within the Amazon rainforest ecoregion, showing forest extent in 2020 derived from Landsat 8 imagery (map includes sites sampled before forest clearing). (B) Mean temperature and total precipitation (points) per season using climate reanalysis tiles [crosshatch in (A) inset] overlapping capture data. Lines and confidence intervals are outputs from generalized additive mixed models showing in situ climate change. Black squares on the x axis highlight recent widespread droughts (–84). (C) Mass, wing length, and mass:wing ratio trends of 77 bird species measured in 1979–2019. To obtain overall trend, species were pooled and designated as a random effect in Bayesian hierarchical models. Points are medians with 90% and 95% credible intervals (CIs). Estimates are colored orange if 95% CIs are entirely negative, blue if entirely positive, or black if overlapping zero. Results correspond to models 19, 22, and 25 (table S4). (D) Morphological trends of individual species, ordered by declining mass. Numbers on the right correspond to the same species in Fig. 4. Results correspond to models 1, 7, and 13 (table S4).

Fig. 2.. Mass:wing ratio trend by forest vertical niche.

Points are median estimates from the second level (trait) of Bayesian hierarchical models shown in Fig. 1D, with lines representing 90% and 95% CIs. Out of the three morphological metrics, only mass:wing ratio for midstory species had 95% CIs that did not overlap zero for the guild as a whole. Estimates are colored orange if 95% CIs are entirely negative, blue if entirely positive, or black if overlapping zero. Relative to the buffered microclimate on the forest floor, upper-stratum conditions are generally more severe (53, 85). Results correspond to model 16 (table S4).

Fig. 3.. Bird morphology modeled by time trend and climate covariates.

Each panel shows parameter estimates of a single model for one of the three metrics representing bird morphology in the community as a whole as response (columns), and time trend (year) and temperature (A to C) or precipitation (D to F) as covariates. Lag 0 is the season of capture (dry season), with lags 1 and 2 the previous wet and dry seasons, respectively. Points are medians with 90% and 95% CIs. Estimates are colored orange if 95% CIs are entirely negative, blue if entirely positive, or black if overlapping zero. Results correspond to models 20, 21, 23, 24, 26, and 27 (table S4).

Fig. 4.. Morphology by species modeled by time trend and climate covariates.

(A to C) Models of bird morphology metrics by year and mean temperature during the season of capture (dry season—lag 0) and two seasonal lags (previous wet—lag 1 and previous dry—lag 2). (D to F) Models of bird morphology by year and total precipitation. Species are ranked by declining mass (Fig. 1D), with points showing medians with 90% and 95% CIs estimated with Bayesian hierarchical models. Estimates are colored orange if 95% CIs are entirely negative, blue if entirely positive, or black if overlapping zero. Results correspond to models 2, 3, 8, 9, 14, and 15 (table S4).