Upscaling species richness and abundances in tropical forests

Deviation from neutral species abundance distributions unveils geographical differences in the structure of diatom communities

In recent years, the application of metagenomics techniques has advanced our understanding of plankton communities and their global distribution. Despite this progress, the relationship between the abundance distribution of diatom species and varying marine environmental conditions remains poorly understood. This study, leveraging data from the Tara Oceans expedition, tests the hypothesis that diatoms in sampled stations display a consistent species abundance distribution structure, as though they were sampled from a single ocean-wide metacommunity. Using a neutral sampling theory, we thus develop a framework to estimate the structure and diversity of diatom communities at each sampling station given the shape of the species abundance distribution of the metacommunity and the information of a reference station. Our analysis reveals a substantial temperature gradient in the discrepancies between predicted and observed biodiversity across the sampled stations. These findings challenge the hypothesis of a single neutral metacommunity, indicating that environmental differences substantially influence both the composition and structure of diatom communities.

Consistent patterns of common species across tropical tree communities

Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.

Unveiling global species abundance distributions

Whether most species are rare or have some intermediate abundance is a long-standing question in ecology. Here, we use more than one billion observations from the Global Biodiversity Information Facility to assess global species abundance distributions (gSADs) of 39 taxonomic classes of eukaryotic organisms from 1900 to 2019. We show that, as sampling effort increases through time, the shape of the gSAD is unveiled; that is, the shape of the sampled gSAD changes, revealing the underlying gSAD. The fraction of species unveiled for each class decreases with the total number of species in that class and increases with the number of individuals sampled, with some groups, such as birds, being fully unveiled. The best statistical fit for almost all classes was the Poisson log-normal distribution. This strong evidence for a universal pattern of gSADs across classes suggests that there may be general ecological or evolutionary mechanisms governing the commonness and rarity of life on Earth.

New Findings on the Biology and Ecology of the Ecuadorian Amazon Fungus Polyporus leprieurii var. yasuniensis

Polyporus leprieurii var. yasuniensis is a prolific wood-decay fungus inhabiting the forest floor of one of the most biodiverse places on earth, the Yasuní National Park in Ecuador. Basidiocarps and aerial rhizomorphs are commonly found growing on woody debris distributed along the floor of this forest ecosystem. Because of the extraordinary abundance of this fungus in the tropical rainforest, we carried out investigations to better understand the biological and ecological aspects contributing to its prolific distribution. Data on growth inhibition in paired competition studies with sixteen fungal isolates exemplifies defense mechanisms used to defend its territory, including pseudosclerotial plates and the development of a melanized rhizomorphic mat. Results of biomass loss on eleven types of tropical wood in microcosm experiments demonstrated the broad decay capacity of the fungus. In and ex situ observations provided information on how long rhizomorphs can prevail in highly competitive ecosystems as well as stressful conditions in the laboratory. Finally, high concentrations of metal ions occur on rhizomorphs as compared to colonized wood. Sequestration of metal ions from the environment by the melanized rhizomorphs may offer protection against competitors. The development of melanized rhizomorphs is key to find and colonize new substrates and resist changing environmental conditions.

Metagenomic Sequencing Reveals that the Assembly of Functional Genes and Taxa Varied Highly and Lacked Redundancy in the Earthworm Gut Compared with Soil under Vanadium Stress

Exploring the ecological mechanism of microbial community assembly in soil and the earthworm gut in a vanadium polluted environment could help us understand the effects of vanadium stress on microbial diversity maintenance and function, as well as the mechanism of microbial mitigation of vanadium stress. Combining metagenomic sequencing and abundance distribution models, we explored the assembly of earthworm intestinal bacteria and native soil bacteria after 21 days of earthworm exposure to a gradient level of vanadate (0 to 300 mg kg⁻¹) in soil. Stochastic processes dominated the assembly of both genes and taxa in earthworm gut and soil. Both the composition of taxa and functional genes in earthworm gut varied highly with the vanadium concentration, while in soil, only the taxa changed significantly, whereas the functional genes were relatively stable. The functional redundancy in soil, but not in the earthworm gut, was confirmed by a Mantel test and analysis of similarities (ANOSIM) test. In addition, vanadium detoxifying gene (VDG)-carrying taxa were more diverse but less abundant in soil than in the worm gut; and VDGs were more abundant in soil than in the worm gut. Their wider niche breadth indicated that VDG-carrying taxa were generalists in soil, in contrast to their role in the worm gut. These results suggested that earthworm intestinal and soil microbes adopted different strategies to counteract vanadium stress. The results provide new insights into the effects of soil vanadium stress on the assembly of earthworm gut and soil microbiota from both bacterial taxa and genetic function perspectives.

IMPORTANCE Metagenomic sequencing revealed the variation of functional genes in the microbial community in soil and earthworm gut with increasing vanadium concentrations, which provided a new insight to explore the effect of vanadium stress on microbial community assembly from the perspective of functional genes. Our results reinforced the view that functional genes and taxa do not appear to have a simple corresponding relationship. Taxa are more sensitive compared with functional genes, suggesting the existence of bacterial functional redundancy in soil, but not in the earthworm gut. These observations indicate different assembly patterns of earthworm intestinal and soil bacteria under vanadium stress. Thus, it is important and necessary to include genetic functions to comprehensively understand microbial community assembly.

Upscaling human activity data: A statistical ecology approach

Big data require new techniques to handle the information they come with. Here we consider four datasets (email communication, Twitter posts, Wikipedia articles and Gutenberg books) and propose a novel statistical framework to predict global statistics from random samples. More precisely, we infer the number of senders, hashtags and words of the whole dataset and how their abundances (i.e. the popularity of a hashtag) change through scales from a small sample of sent emails per sender, posts per hashtag and word occurrences. Our approach is grounded on statistical ecology as we map inference of human activities into the unseen species problem in biodiversity. Our findings may have applications to resource management in emails, collective attention monitoring in Twitter and language learning process in word databases.

Upscaling Statistical Patterns from Reduced Storage in Social and Life Science Big Datasets

Recent technological and computational advances have enabled the collection of data at an unprecedented rate. On the one hand, the large amount of data suddenly available has opened up new opportunities for new data-driven research but, on the other hand, it has brought into light new obstacles and challenges related to storage and analysis limits. Here, we strengthen an upscaling approach borrowed from theoretical ecology that allows us to infer with small errors relevant patterns of a dataset in its entirety, although only a limited fraction of it has been analysed. In particular we show that, after reducing the input amount of information on the system under study, by applying our framework it is still possible to recover two statistical patterns of interest of the entire dataset. Tested against big ecological, human activity and genomics data, our framework was successful in the reconstruction of global statistics related to both the number of types and their abundances while starting from limited presence/absence information on small random samples of the datasets. These results pave the way for future applications of our procedure in different life science contexts, from social activities to natural ecosystems.

Ecosystem Service Multifunctionality: Decline and Recovery Pathways in the Amazon and Chocó Lowland Rainforests

The balance between the supply of multiple ecosystem services (ES) and the fulfillment of society demands is a challenge, especially in the tropics where different land use transition phases emerge. These phases are characterized by either a decline (from intact old-growth to logged forests) or a recovery of ES (successional forests, plantations, and agroforestry systems). This highlights the importance of ecosystem service multifunctionality (M) assessments across these land use transition phases as a basis for forest management and conservation. We analyzed synergies and trade-offs of ES to identify potential umbrella ES. We also evaluated the impact of logging activities in the decline of ES and M, and the influence of three recovery phases in the supply of ES and M. We installed 156 inventory plots (1600 m2) in the Ecuadorian Central Amazon and the Chocó. We estimated indicators for provisioning, regulating, supporting services and biodiversity. M indicator was estimated using the multifunctional average approach. Our results show that above-ground carbon stocks can be considered as an umbrella service as it presented high synergetic relations with M and various ES. We observed that logging activities caused a decline of 16–18% on M, with high impacts for timber volume and above-ground carbon stocks, calling for more sustainable practices with stricter post-harvesting control to avoid a higher depletion of ES and M. From the recovery phases it is evident that, successional forests offer the highest level of M, evidencing high potential to recover multiple ES after human disturbance.

Spatial Agreement among Vegetation Disturbance Maps in Tropical Domains Using Landsat Time Series

Detecting disturbances in native vegetation is a crucial component of many environmental management strategies, and remote sensing-based methods are the most efficient way to collect multi-temporal disturbance data over large areas. Given that there is a large range of datasets for monitoring, analyzing, and detecting disturbances, many methods have been well-studied and successfully implemented. However, factors such as the vegetation type, input data, and change detection method can significantly alter the outcomes of a disturbance-detection study. We evaluated the spatial agreement of disturbance maps provided by the Breaks For Additive Season and Trend (BFAST) algorithm, evaluating seven spectral indices in three distinct vegetation domains in Brazil: Atlantic forest, savanna, and semi-arid woodland, by assessing levels of agreement between the outputs. We computed individual map accuracies based on a reference dataset, then ranked their performance, while also observing their relationships with specific vegetation domains. Our results indicated a low rate of spatial agreement among index-based disturbance maps, which itself was minimally influenced by vegetation domain. Wetness indices produced greater detection accuracies in comparison to greenness-related indices free of saturation. The normalized difference moisture index performed best in the Atlantic forest domains, yet performed poorest in semi-arid woodland, reflecting its specific sensitivity to vegetation and its water content. The normalized difference vegetation index led to high disturbance detection accuracies in the savanna and semi-arid woodland domains. This study offered novel insight into vegetation disturbance maps, their relationship to different ecosystem types, and corresponding accuracies. Distinct input data can produce non-spatially correlated disturbance maps and reflect site-specific sensitivity. Future research should explore algorithm limitations presented in this study, as well as the expansion to other techniques and vegetation domains across the globe.

Biased-corrected richness estimates for the Amazonian tree flora

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come.

Degradation of Ecosystem Services and Deforestation in Landscapes With and Without Incentive-Based Forest Conservation in the Ecuadorian Amazon

Anthropogenic activities such as logging or forest conversion into agricultural lands are affecting Ecuadorian Amazon forests. To foster private and communal conservation activities an economic incentive-based conservation program (IFC) called Socio Bosque was established. Existing analyses related to conservation strategies are mainly focused on deforestation; while degradation and the role of IFC to safeguard ecosystem services are still scarce. Further on, there is a lack of landscape-level studies taking into account potential side effects of IFC on different forest types. Therefore we assessed ecosystem services (carbon stocks, timber volume) and species richness in landscapes with and without IFC. Additionally, we evaluated potential side-effects of IFC in adjacent forest types; hypothesizing potential leakage effects of IFC. Finally, we tested if deforestation rates decreased after IFC implementation. Forest inventories were conducted in 72 plots across eight landscapes in the Ecuadorian Central Amazon with and without IFC. Plots were randomly selected within three forest types (old-growth, logged and successional forests). In each plot all individuals with a diameter at breast height greater than 10 cm were measured. Old-growth forests in general showed higher carbon stocks, timber volume and species richness, and no significant differences between old-growth forests in IFC and non-IFC landscapes were found. Logged forests had 32% less above-ground carbon (AGC) and timber volume in comparison to old-growth forests. Surprisingly, logged forests near IFC presented higher AGC stocks than logged forests in non-IFC landscapes, indicating positive side-effects of IFC. Successional forests contain 56% to 64% of AGC, total carbon and timber volume, in comparison to old-growth forests, and 82% to 87% in comparison to logged forests. Therefore, successional forests could play an important role for restoration and should receive more attention in national climate change policies. Finally, after IFC implementation deforestation rate decreased on parish level. Our study presents scientific evidence of IFC contribution to conserving ecosystem services and species richness. In addition IFC could help indirectly to reduce degradation effects attributed to logging, indicating potential compatibility of conservation aims with forest activities at a landscape level.

Remarks on the Maximum Entropy Principle with Application to the Maximum Entropy Theory of Ecology

In the first part of the paper we work out the consequences of the fact that Jaynes’ Maximum Entropy Principle, when translated in mathematical terms, is a constrained extremum problem for an entropy function H(p) expressing the uncertainty associated with the probability distribution p. Consequently, if two observers use different independent variables p or g(p), the associated entropy functions have to be defined accordingly and they are different in the general case. In the second part we apply our findings to an analysis of the foundations of the Maximum Entropy Theory of Ecology (M.E.T.E.) a purely statistical model of an ecological community. Since the theory has received considerable attention by the scientific community, we hope to give a useful contribution to the same community by showing that the procedure of application of MEP, in the light of the theory developed in the first part, suffers from some incongruences. We exhibit an alternative formulation which is free from these limitations and that gives different results.