Pre-Columbian soil fertilization and current management maintain food resource availability in old-growth Amazonian forests

Aims: The extent and persistence of pre-Columbian human legacies in old-growth Amazonian forests are still controversial, partly because modern societies re-occupied old settlements, challenging the distinction between pre- and post-Columbian legacies. Here, we compared the effects of pre-Columbian vs. recent landscape domestication processes on soils and vegetation in two Amazonian regions. Methods: We studied forest landscapes at varying distances from pre-Columbian and current settlements inside protected areas occupied by traditional and indigenous peoples in the lower Tapajós and the upper-middle Madeira river basins. By conducting 69 free-listing interviews, participatory mappings, guided-tours, 27 forest inventories, and soil analysis, we assessed the influences of pre-Columbian and current activities in soils and plant resources surrounding the settlements. Results: In both regions, we found that pre-Columbian villages were more densely distributed across the landscape than current villages. Soil nutrients (mainly Ca and P) were higher closer to pre-Columbian villages but were generally not related to current villages, suggesting past soil fertilization. Soil charcoal was frequent in all forests, suggesting frequent fire events. The density of domesticated plants used for food increased in phosphorus enriched soils. In contrast, the density of plants used for construction decreased near current villages. Conclusions: We detected a significant effect of past soil fertilization on food resources over extensive areas, supporting the hypothesis that pre-Columbian landscape domestication left persistent marks on Amazonian landscapes. Our results suggest that a combination of pre-Columbian phosphorus fertilization with past and current management drives plant resource availability in old-growth forests.</p

Predicting environmental gradients with fern species composition in Brazilian Amazonia

Conclusions: Fern species composition can be used as an indicator of soil cation concentration, which can be expected to be relevant also for other components of rain forests. Presence-absence data are adequate for this purpose, which makes the collecting of additional data potentially very rapid. Comparison with earlier studies suggests that edaphic preferences of fern species have good transferability across geographical regions within lowland Amazonia. Therefore, species and environmental data sets already available in the Amazon region represent a good starting point for generating better environmental and floristic maps for conservation planning.</p

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Large range sizes link fast life histories with high species richness across wet tropical tree floras

Understanding how the traits of lineages are related to diversification is key for elucidating the origin of variation in species richness. Here, we test whether traits are related to species richness among lineages of trees from all major biogeographical settings of the lowland wet tropics. We explore whether variation in mortality rate, breeding system and maximum diameter are related to species richness, either directly or via associations with range size, among 463 genera that contain wet tropical forest trees. For Amazonian genera, we also explore whether traits are related to species richness via variation among genera in mean species-level range size. Lineages with higher mortality rates—faster life-history strategies—have larger ranges in all biogeographic settings and have higher mean species-level range sizes in Amazonia. These lineages also have smaller maximum diameters and, in the Americas, contain dioecious species. In turn, lineages with greater overall range size have higher species richness. Our results show that fast life-history strategies influence species richness in all biogeographic settings because lineages with these ecological strategies have greater range sizes. These links suggest that dispersal has been a key process in the evolution of the tropical forest flora

Data from: Alternative functional trajectories along succession after different land-use in central Amazonia

1. The recovery capacity and the successional pathways of tropical forests after anthropogenic disturbance vary considerably and may depend on prior land-use type and intensity. It is still unclear if forests subjected to high intensity impact, such as periodically burned pastures, are capable of restoring their original functional properties. 2. This study analysed the functional trait dynamics of the dominant species in successional trajectories following two land uses, pasture or clear-cut, north of Manaus. Fourteen years of demographic data from the Biological Dynamics of Forest Fragments Project were used to determine the dominant species of the two successional trajectories, for which leaf area, leaf dry mass content, specific leaf area and wood density were collected whereas seed mass was obtained from literature. Community weighted mean (CWM) of each trait was weighted by basal area determined annually along succession. PCA was used to analyse the extension and direction of the functional trajectories of plots. 3. Forests regenerating from pastures increased in wood density along successional time, but other traits did not change significantly. Succession after clear-cut exhibited increasing leaf dry mass content and seed mass, and decreasing leaf area along time, but no change in wood density. Functional trajectories of plots after clear-cut were more extensive and directional than those of pasture-derived plots. 4. Synthesis and applications: We demonstrate how central Amazonian secondary forests subjected to different land uses showed differences in functional trait trajectories, in ways parallel to previously shown changes in biomass, floristic diversity and forest structure. These results indicate that natural recovery of forest functional traits is affected by prior land-use history, with implications for management and restoration. Thus, natural recovery of forests on abandoned pastures is much slower than clear-cuts, even though seed sources from mature forests are very close to these areas, and the former may need intervention to counteract the diverted succession