Milton Tirado

Seasonal drought limits tree species across the Neotropics

Within the tropics, the species richness of tree communities is strongly and positively associated with precipitation. Previous research has suggested that this macroecological pattern is driven by the negative effect of water-stress on the physiological processes of most tree species. This process implies that the range limits of taxa are defined by their ability to occur under dry conditions, and thus in terms of species distributions it predicts a nested pattern of taxa distribution from wet to dry areas. However, this ‘dry-tolerance’ hypothesis has yet to be adequately tested at large spatial and taxonomic scales. Here, using a dataset of 531 inventory plots of closed canopy forest distributed across the Western Neotropics we investigated how precipitation, evaluated both as mean annual precipitation and as the maximum climatological water deficit, influences the distribution of tropical tree species, genera and families. We find that the distributions of tree taxa are indeed nested along precipitation gradients in the western Neotropics. Taxa tolerant to seasonal drought are disproportionally widespread across the precipitation gradient, with most reaching even the wettest climates sampled; however, most taxa analysed are restricted to wet areas. Our results suggest that the ‘dry tolerance’ hypothesis has broad applicability in the worlds most species-rich forests. In addition, the large number of species restricted to wetter conditions strongly indicates that an increased frequency of drought could severely threaten biodiversity in this region. Overall, this study establishes a baseline for exploring how tropical forest tree composition may change in response to current and future environmental changes in this region.

Are all species necessary to reveal ecologically important patterns

While studying ecological patterns at large scales, ecologists are often unable to identify all collections, forcing them to either omit these unidentified records entirely, without knowing the effect of this, or pursue very costly and time-consuming efforts for identifying them. These “indets” may be of critical importance, but as yet, their impact on the reliability of ecological analyses is poorly known. We investigated the consequence of omitting the unidentified records and provide an explanation for the results. We used three large-scale independent datasets, (Guyana/ Suriname, French Guiana, Ecuador) each consisting of records having been identified to a valid species name (identified morpho-species – IMS) and a number of unidentified records (unidentified morpho-species – UMS). A subset was created for each dataset containing only the IMS, which was compared with the complete dataset containing all morpho-species (AMS: = IMS + UMS) for the following analyses: species diversity (Fishers alpha), similarity of species composition, Mantel test and ordination (NMDS). In addition, we also simulated an even larger number of unidentified records for all three datasets and analyzed the agreement between similarities again with these simulated datasets. For all analyses, results were extremely similar when using the complete datasets or the truncated subsets. IMS predicted ≥91% of the variation in AMS in all tests/analyses. Even when simulating a larger fraction of UMS, IMS predicted the results for AMS rather well. Using only IMS also out-performed using higher taxon data (genus-level identification) for similarity analyses. Finding a high congruence for all analyses when using IMS rather than AMS suggests that patterns of similarity and composition are very robust. In other words, having a large number of unidentified species in a dataset may not affect our conclusions as much as is often thought.

Forest-Cover Change from Labor- and Capital-Intensive Commercial Logging in the Southern Chocó Rainforests†

Abstract This article examines two key aspects of land-cover change in the south of the Chocó region. First, it assesses and compares the local impact on forest condition of labor-intensive and capital-intensive commercial logging. Second, it assesses the regional significance and permanency of these changes. Studies of land-cover change associated with commercial logging have focused almost exclusively on capital-intensive extraction and have assumed that after logging, degraded forests are transformed into agricultural cover. This study shows that both capital- and labor-intensive logging result in similar land-cover changes (i.e., forest degradation) if the timber sought is the same. However, labor-intensive loggers also seek timber species not sought by capital-intensive loggers, and this impact is statistically different from the impact of the extraction of the first group of species. Results also show that only a small fraction (20–30 percent) of the area logged is later converted to agricultural cover types. The persistence of logged forests means that up to 20 percent of the remaining forest cover could correspond to forests with significant and lasting levels of degradation. Furthermore, the different production requirements for each group of species also mean that there is a spatial differentiation in the impact of logging in the region. Logged forests are arranged into two consecutive corridors on each side of access routes (e.g., rivers). The first corridor corresponds to a narrow (approximately 1-km) band of high-intensity degradation. The second, broader (approximately 2-km) forest band, with lower levels of degradation, extends inland along first-tier corridors. A key factor determining the permanency of this land-cover pattern is the strong control local communities have over the land in the region. This limits the spread of patterns observed in other frontier areas, especially the conversion of logged forests into agricultural cover.

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models

Abstract With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large‐scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi‐explicit simulations based on three large‐scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi‐explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi‐explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)‐neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.