LightGBM hybrid model based DEM correction for forested areas.

The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role in canopy height monitoring and ecological sensitivity analysis. Despite extensive research on DEMs in recent years, significant errors still exist in forested areas due to factors such as canopy occlusion, terrain complexity, and limited penetration, posing challenges for subsequent analyses based on DEMs. Therefore, a CNN-LightGBM hybrid model is proposed in this paper, with four different types of forests (tropical rainforest, coniferous forest, mixed coniferous and broad-leaved forest, and broad-leaved forest) selected as study sites to validate the performance of the hybrid model in correcting COP30DEM in different forest area DEMs. In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. This choice is based on LightGBM's leaf-growth strategy and histogram linking methods, which are effective in reducing the data's memory footprint and utilising more of the data without sacrificing speed. The study uses elevation values from ICESat-2 as ground truth, covering several parameters including COP30DEM, canopy height, forest coverage, slope, terrain roughness and relief amplitude. To validate the superiority of the CNN-LightGBM hybrid model in DEMs correction compared to other models, a test of LightGBM model, CNN-SVR model, and SVR model is conducted within the same sample space. To prevent issues such as overfitting or underfitting during model training, although common meta-heuristic optimisation algorithms can alleviate these problems to a certain extent, they still have some shortcomings. To overcome these shortcomings, this paper cites an improved SSA search algorithm that incorporates the ingestion strategy of the FA algorithm to increase the diversity of solutions and global search capability, the Firefly Algorithm-based Sparrow Search Optimization Algorithm (FA-SSA algorithm) is introduced. By comparing multiple models and validating the data with an airborne LiDAR reference dataset, the results show that the R2 (R-Square) of the CNN-LightGBM model improves by more than 0.05 compared to the other models, and performs better in the experiments. The FA-SSA-CNN-LightGBM model has the highest accuracy, with an RMSE of 1.09 meters, and a reduction of more than 30% of the RMSE when compared to the LightGBM and other hybrid models. Compared to other forested area DEMs (such as FABDEM and GEDI), its accuracy is improved by more than 50%, and the performance is significantly better than other commonly used DEMs in forested areas, indicating the feasibility of this method in correcting elevation errors in forested area DEMs and its significant importance in advancing global topographic mapping.

Cultivation of a Wild Strain of Wood Ear Auricularia cornea from Brazil.

Auricularia cornea has become one of the most important cultivated mushrooms worldwide. Although not remarkably flavorful, Auricularia species are very versatile and rehydrate easily after drying, adding a unique and pleasing texture to the dishes. In this study, we collected, identified, and domesticated a wild strain of A. cornea from the Brazilian Atlantic Rainforest. The wild strain was evaluated for mycelial growth at different temperatures and substrates, biological efficiency, and nutritional composition. The temperature that best favored the A. cornea mycelium growth was 30 °C, and the substrate was sterile Eucalyptus sawdust. The highest biological efficiency value obtained was 106.90 ± 13.28%. Nutritional analysis showed that the produced wood ears contained 71.02% carbohydrates, 19.63% crude fiber, 11.59% crude protein, 10.19% crude fat, and 4.24% ash on dry matter basis. For the mineral content profile, the elements K and P were the most abundant. This is the first report on cultivation of a wild strain of A. cornea from Brazil.

Whole genomes of Amazonian uakari monkeys reveal complex connectivity and fast differentiation driven by high environmental dynamism.

Despite showing the greatest primate diversity on the planet, genomic studies on Amazonian primates show very little representation in the literature. With 48 geolocalized high coverage whole genomes from wild uakari monkeys, we present the first population-level study on platyrrhines using whole genome data. In a very restricted range of the Amazon rainforest, eight uakari species (Cacajao genus) have been described and categorized into the bald and black uakari groups, based on phenotypic and ecological differences. Despite a slight habitat overlap, we show that posterior to their split 0.92 Mya, bald and black uakaris have remained independent, without gene flow. Nowadays, these two groups present distinct genetic diversity and group-specific variation linked to pathogens. We propose differing hydrology patterns and effectiveness of geographic barriers have modulated the intra-group connectivity and structure of bald and black uakari populations. With this work we have explored the effects of the Amazon rainforest's dynamism on wild primates' genetics and increased the representation of platyrrhine genomes, thus opening the door to future research on the complexity and diversity of primate genomics.

Multivariate statistical analysis as a tool for monitoring drinking water sources in an Atlantic Rainforest Conservation Unit.

Water quality monitoring is paramount in identifying and mitigating pollution sources, protecting aquatic ecosystems, and ensuring safe water for human and wildlife consumption. This study is aimed at evaluating the quality of drinking water sources in three communities located in a Sustainable Use Conservation Unit in the municipality of Mangaratiba, Rio de Janeiro, Brazil, employing a multivariate statistical analysis. A total of 161 water samples were collected from January to December 2022, encompassing 32 surface water and 129 tap water samples. Physicochemical parameters were determined in situ employing a Horiba U50 multiparameter probe. The samples were stored and transported at 4 °C to the laboratory for microbiological analyses concerning total coliforms and Escherichia coli using a commercial enzymatic test. All samples contained coliforms, while E. coli were detected in 87% of the samples. The multivariate analysis indicated that the microbiological water quality in sampling region R2 was influenced by rainy periods and that, in general, the water quality within R3 was the most affected by the transport of solids to the water sources. The statistical methods applied herein aided in characterizing the study areas and detecting points of attention regarding physicochemical and microbiological parameters that significantly influence the water quality of each sampling point. Representative points for each study region were identified and may be employed for future monitoring and prevention actions.

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake.

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain1. The global annual mean GPP is historically thought to be around 120 PgC yr-1 (refs. 2-6), which is about 30-50 PgC yr-1 lower than GPP inferred from the oxygen-18 (18O) isotope7 and soil respiration8. This disparity is a source of uncertainty in predicting climate-carbon cycle feedbacks9,10. Here we infer GPP from carbonyl sulfide, an innovative tracer for CO2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr-1, which is consistent with estimates from 18O (150-175 PgC yr-1) and soil respiration ( 149 - 23 + 29 PgC yr-1), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120-140 PgC yr-1) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements11, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories9,10, our findings lay a physiological foundation on which the understanding and prediction of carbon-climate feedbacks can be advanced.

Among the world's smallest vertebrates: a new miniaturized flea-toad (Brachycephalidae) from the Atlantic rainforest.

The genus Brachycephalus includes miniaturized toadlets with two distinct morphotypes: brightly colored species with a bufoniform phenotype and smaller, cryptic species with a leptodactyliform phenotype. The diversity of leptodactyliform species is still underappreciated, and we generally lack fundamental information about their biology. Recent sampling efforts, including DNA analyses and recordings of advertisement calls, have improved our understanding of this group. In the present study, we describe a new species of Brachycephalus, one of the smallest vertebrates known. This new species is distinguished from its congeners by a combination of morphological, bioacoustic, and genetic data. Despite being among the smallest frogs globally (the second smallest amphibian species), it exhibits skeletal traits typical of larger frogs, such as the presence of cranial bones that are lost or fused in other miniature frogs, including other Brachycephalus. Our description underscores how new discoveries within the megadiverse fauna of the Atlantic Forest-a rich biodiversity hotspot-can provide insights into phenotypic variation, including vertebrate body size. By describing this new species, we also aim to revisit the hypothesis that the type series of B. hermogenesi includes two species, potentially including individuals of the species described here.

Root traits drive the recovery of soil nematodes during restoration of open mines in a tropical rainforest.

Mining is a major threat to vegetation and soil in the tropical forests. Reforestation of degraded surface mines is critically dependent on the recovery of soil health, where the nematodes play an important role. However, the key determinants of community assembly of soil nematodes during mine-restoration remain unknown in the tropical rainforests. Here, the recovery of taxonomic diversity of nematode communities and their trophic groups during reforestation of an extremely degraded tropical open-mining area is studied. The factors that may impact their recovery, such as root traits (length, area and tissue density), soil properties (pH and soil organic matter content (SOM)), and taxonomic diversities of soil bacterial and fungal communities are investigated. Differences in these parameters were evaluated in the three soil types: (i) mined soil - the erstwhile soil that was removed during mining and stock-piled for 10 years at the foot of an extremely degraded open-mining area; (ii) reforested soil, sampled from a 10-year successful restoration, which used the mined soil for reforestation; and (iii) undisturbed soil, collected from an adjacent undisturbed/not-mined tropical rainforest. A total of 11, 34 and 29 nematode-genera were identified in mined-, undisturbed-, and reforested soils, respectively. The taxonomic diversities of the 5 nematode groups in the mined soil were 1.5-5.2 times lower than in the undisturbed soil, but were similar in the restored and undisturbed soils. Taxonomic diversities of phytophagous and predator nematodes were correlated to restored root traits; whereas of bacterivores, fungivores, and omnivores were correlated to pH, SOM, soil bacterial and fungal communities. Consequently, complete loss of roots during mining likely severely reduced the nematodes, but their recovery after reforestation led to the restoration of taxonomic diversity of nematode communities. The mix-planting fast-growing tree species may be appropriate for recovering soil health, including nematode diversity, during reforestation of open tropical mines.

[Niche and interspecific association of main woody plants in Cunninghamia lanceolata plantation community in Jianfengling, China]. / 尖峰岭杉木人工林群落主要木本植物的生态位和种间联结.

Studies on niche and interspecific association can reveal plant interspecific relationship in the community, and provide theoretical support for promoting the transformation and development of plantation to natural forest. Based on Cunninghamia lanceolata investigation data of permanent plots of plantation in Jianfengling area of Hainan Tropical Rainforest National Park, we analyzed niche and interspecific association of the top 20 woody species in the community according to their importance values. The results showed that there were 163 species of woody species belonging to 101 genera and 55 families in the C. lanceolata plantation community, with complex species composition. As a constructive species, C. lanceolata had the highest importance value and niche breadth, and thus was the absolute dominant species in the community. It had a large niche overlap and niche similarity with many other species, among which the highest was observed in Adinandra hainanensis. The average niche overlap and niche similarity of the community were 0.54 and 0.49, respectively. The change trends of those two niche indicators were basically the same, indicating that some species were similar in resource demands. The overall association of main woody species was significantly positive. The χ2 test, association coefficient, Pearson correlation coefficient, and Spearman rank correlation coefficient suggested that the amounts of pairs with positive association were more than that with negative ones. The proportion of significant association species pairs was relatively low, indicating that the community stability was strong, species could coexist stably, and most species did not form close ties. On the whole, C. lanceolata had inhibited the regeneration of original tree species, and A. hainanensis, Garcinia oblongifolia, and Heptapleurum heptaphyllum could be used in natural transformation and restoration of C. lanceolata plantation in the Hainan Tropical Rainforest National Park.

Spencermartinsiella nicolii sp. nov., a potential opportunistic pathogenic yeast species isolated from rotting wood in Brazil.

Nineteen isolates representing a candidate for a novel yeast species belonging to the genus Spencermartinsiella were recovered from rotting wood samples collected at different sites in Atlantic Rainforest and Amazonian Forest ecosystems in Brazil. Similarity search of the nucleotide sequence of the intergenic spacer (ITS)-5.8S and large subunit D1/D2 regions of the ribosomal gene cluster showed that this novel yeast is closely related to Spencermartinsiella cellulosicola. The isolates differ by four nucleotide substitutions in the D1/D2 domain and six substitutions and 31 indels in the ITS region from the holotype of S. cellulosicola. Phylogenomic analysis based on 1474 single-copy orthologues for a set of Spencermartinsiella species whose whole genome sequences are available confirmed that the novel species is phylogenetically close to S. cellulosicola. The low average nucleotide identity value of 83% observed between S. cellulosicola and the candidate species confirms that they are distinct. The novel species produced asci with hemispherical ascospores. The name Spencermartinsiella nicolii sp. nov. is proposed. The holotype is CBS 14238T. The MycoBank number is MB855027. Interestingly, the D1/D2 sequence of the S. nicolii was identical to that of an uncultured strain of Spencermartinsiella causing systemic infection in a male adult crocodile (Crocodylus niloticus). The characterization of some virulence factors and antifungal susceptibility of S. nicolii isolates suggest that this yeast may be an opportunistic pathogen for animals, including humans; the isolates grow at 37 °C.

Host preference explains the high endemism of ectomycorrhizal fungi in a dipterocarp rainforest.

Ectomycorrhizal (ECM) fungi are important tree symbionts within forests. The biogeography of ECM fungi remains to be investigated because it is challenging to observe and identify species. Because most ECM plant taxa have a Holarctic distribution, it is difficult to evaluate the extent to which host preference restricts the global distribution of ECM fungi. To address this issue, we aimed to assess whether host preference enhances the endemism of ECM fungi that inhabit dipterocarp rainforests. Highly similar sequences of 175 operational taxonomic units (OTUs) for ECM fungi that were obtained from Lambir Hill's National Park, Sarawak, Malaysia, were searched for in a nucleotide sequence database. Using a two-step binomial model, the probability of presence for the query OTUs and the registration rate of barcode sequences in each country were simultaneously estimated. The results revealed that the probability of presence in the respective countries increased with increasing species richness of Dipterocarpaceae and decreasing geographical distance from the study site (i.e. Lambir). Furthermore, most of the ECM fungi were shown to be endemic to Malaysia and neighbouring countries. These findings suggest that not only dispersal limitation but also host preference are responsible for the high endemism of ECM fungi in dipterocarp rainforests. Moreover, host preference likely determines the areas where ECM fungi potentially expand and dispersal limitation creates distance-decay patterns within suitable habitats. Although host preference has received less attention than dispersal limitation, our findings support that host preference has a profound influence on the global distribution of ECM fungi.

Fish mortality in the Amazonian drought of 2023: the role of experimental biology in our response to climate change.

Higher temperatures exacerbate drought conditions by increasing evaporation rates, reducing soil moisture and altering precipitation patterns. As global temperatures rise as a result of climate change, these effects intensify, leading to more frequent and severe droughts. This link between higher temperatures and drought is particularly evident in sensitive ecosystems like the Amazon rainforest, where reduced rainfall and higher evaporation rates result in significantly lower water levels, threatening biodiversity and human livelihoods. As an example, the serious drought experienced in the Amazon basin in 2023 resulted in a significant decline in fish populations. Elevated water temperatures, reaching up to 38°C, led to mass mortality events, because these temperatures surpass the thermal tolerance of many Amazonian fish species. We know this because our group has collected data on critical thermal maxima (CTmax) for various fish species over multiple years. Additionally, warmer waters can cause hypoxia, further exacerbating fish mortality. Thus, even Amazon fish species, which have relatively high thermal tolerance, are being impacted by climate change. The Amazon drought experienced in 2023 underscores the urgent need for climate action to mitigate the devastating effects on Amazonian biodiversity. The fact that we have been able to link fish mortality events to data on the thermal tolerance of fishes emphasizes the important role of experimental biology in elucidating the mechanisms behind these events, a link that we aim to highlight in this Perspective.

Water deficit and storm disturbances co-regulate Amazon rainforest seasonality.

Canopy leaf abundance of Amazon rainforests increases in the dry season but decreases in the wet season, contrary to earlier expectations of water stress adversely affecting plant functions. Drivers of this seasonality, particularly the role of water availability, remain debated. We introduce satellite-based ecophysiological indicators to demonstrate that Amazon rainforests are constrained by water during dry seasons despite light-driven canopy greening. Evidence includes a shifted partitioning of photosynthetically active radiation toward more isoprene emissions and synchronized declines in leaf and xylem water potentials. In addition, we find that convective storms attenuate light-driven ecosystem greening in the late dry season and then reverse to net leaf loss in the wet season, improving rainforest leaf area predictability by 24 to 31%. These findings highlight the susceptibility of Amazon rainforests to increasing risks of drought and windthrow disturbances under warming.

Tick-borne Apicomplexa in wildlife and ticks of French Guiana.

Tick-borne Apicomplexa encompass a group of parasites responsible for significant medical and veterinary diseases, including babesiosis, theileriosis, and hepatozoonosis. In this study, we investigated the presence and diversity of tick-borne Apicomplexa in wildlife and ticks inhabiting the Amazon rainforests of French Guiana. To this end, we conducted molecular screening and typing using 18S rRNA sequences on a collection of 1161 specimens belonging to 71 species, including 44 species of wild mammals, five species of passerines, and 22 species of ticks. We characterized eight genovariants of Babesia, Theileria, Hemolivia, and Hepatozoon parasites, some matching known species, while others suggested potential novel species. These parasites were detected in wild mammals, including opossums, sloths, armadillos, porcupines, margays, greater grisons, and ticks, but not in passerines. Finally, similarities with surveys conducted in Brazil highlight the specific sylvatic transmission cycles of South American tick-borne Apicomplexa.

Title: Apicomplexes transmis par les tiques chez la faune sauvage et les tiques de Guyane française. Abstract: Les Apicomplexes transmis par les tiques englobent un groupe de parasites responsables de maladies médicales et vétérinaires importantes, notamment la babésiose, la theilériose et l'hépatozoonose. Dans cette étude, nous avons étudié la présence et la diversité des Apicomplexes transmis par les tiques dans la faune sauvage et les tiques habitant les forêts tropicales amazoniennes de Guyane française. À cette fin, nous avons effectué un criblage moléculaire et un typage à l'aide de séquences d'ARNr 18S sur une collection de 1 161 spécimens appartenant à 71 espèces, dont 44 espèces de mammifères sauvages, cinq espèces de passereaux et 22 espèces de tiques. Nous avons caractérisé huit génovariants des parasites Babesia, Theileria, Hemolivia et Hepatozoon, certains correspondant à des espèces connues tandis que d'autres suggéraient de nouvelles espèces potentielles. Ces parasites ont été détectés chez des mammifères sauvages, dont des opossums, des paresseux, des tatous, des porcs-épics, des margays, des grisons et des tiques, mais pas chez des passereaux. Enfin, des similitudes avec des enquêtes menées au Brésil mettent en évidence les cycles de transmission sylvatiques spécifiques des Apicomplexa transmis par les tiques d'Amérique du Sud.

Significance of AI-assisted techniques for epiphyte plant monitoring and identification from drone images.

Monitoring forest canopies is vital for ecological studies, particularly for assessing epiphytes in rain forest ecosystems. Traditional methods for studying epiphytes, such as climbing trees and building observation structures, are labor, cost intensive and risky. Unmanned Aerial Vehicles (UAVs) have emerged as a valuable tool in this domain, offering botanists a safer and more cost-effective means to collect data. This study leverages AI-assisted techniques to enhance the identification and mapping of epiphytes using UAV imagery. The primary objective of this research is to evaluate the effectiveness of AI-assisted methods compared to traditional approaches in segmenting/identifying epiphytes from UAV images collected in a reserve forest in Costa Rica. Specifically, the study investigates whether Deep Learning (DL) models can accurately identify epiphytes during complex backgrounds, even with a limited dataset of varying image quality. Systematically, this study compares three traditional image segmentation methods Auto Cluster, Watershed, and Level Set with two DL-based segmentation networks: the UNet and the Vision Transformer-based TransUNet. Results obtained from this study indicate that traditional methods struggle with the complexity of vegetation backgrounds and variability in target characteristics. Epiphyte identification results were quantitatively evaluated using the Jaccard score. Among traditional methods, Watershed scored 0.10, Auto Cluster 0.13, and Level Set failed to identify the target. In contrast, AI-assisted models performed better, with UNet scoring 0.60 and TransUNet 0.65. These results highlight the potential of DL approaches to improve the accuracy and efficiency of epiphyte identification and mapping, advancing ecological research and conservation.

Phylogenetic structure of moth communities (Geometridae, Lepidoptera) along a complete rainforest elevational gradient in Papua New Guinea.

We use community phylogenetics to elucidate the community assembly mechanisms for Geometridae moths (Lepidoptera) collected along a complete rainforest elevational gradient (200-3700 m a.s.l) on Mount Wilhelm in Papua New Guinea. A constrained phylogeny based on COI barcodes for 604 species was used to analyse 1390 species x elevation occurrences at eight elevational sites separated by 500 m elevation increments. We obtained Nearest Relatedness Index (NRI), Nearest Taxon Index (NTI) and Standardised Effect Size of Faith's Phylogenetic Diversity (SES.PD) and regressed these on temperature, plant species richness and predator abundance as key abiotic and biotic predictors. We also quantified beta diversity in the moth communities between elevations using the Phylogenetic Sorensen index. Overall, geometrid communities exhibited phylogenetic clustering, suggesting environmental filters, particularly at higher elevations at and above 2200 m a.s.l and no evidence of overdispersion. NRI, NTI and SES.PD showed no consistent trends with elevation or the studied biotic and abiotic variables. Change in community structure was driven by turnover of phylogenetic beta-diversity, except for the highest 2700-3200 m elevations, which were characterised by nested subsets of lower elevation communities. Overall, the elevational signal of geometrid phylogeny was weak-moderate. Additional insect community phylogeny studies are needed to understand this pattern.

New tree height allometries derived from terrestrial laser scanning reveal substantial discrepancies with forest inventory methods in tropical rainforests.

Tree allometric models, essential for monitoring and predicting terrestrial carbon stocks, are traditionally built on global databases with forest inventory measurements of stem diameter (D) and tree height (H). However, these databases often combine H measurements obtained through various measurement methods, each with distinct error patterns, affecting the resulting H:D allometries. In recent decades, terrestrial laser scanning (TLS) has emerged as a widely accepted method for accurate, non-destructive tree structural measurements. This study used TLS data to evaluate the prediction accuracy of forest inventory-based H:D allometries and to develop more accurate pantropical allometries. We considered 19 tropical rainforest plots across four continents. Eleven plots had forest inventory and RIEGL VZ-400(i) TLS-based D and H data, allowing accuracy assessment of local forest inventory-based H:D allometries. Additionally, TLS-based data from 1951 trees from all 19 plots were used to create new pantropical H:D allometries for tropical rainforests. Our findings reveal that in most plots, forest inventory-based H:D allometries underestimated H compared with TLS-based allometries. For 30-metre-tall trees, these underestimations varied from -1.6 m (-5.3%) to -7.5 m (-25.4%). In the Malaysian plot with trees reaching up to 77 m in height, the underestimation was as much as -31.7 m (-41.3%). We propose a TLS-based pantropical H:D allometry, incorporating maximum climatological water deficit for site effects, with a mean uncertainty of 19.1% and a mean bias of -4.8%. While the mean uncertainty is roughly 2.3% greater than that of the Chave2014 model, this model demonstrates more consistent uncertainties across tree size and delivers less biased estimates of H (with a reduction of 8.23%). In summary, recognizing the errors in H measurements from forest inventory methods is vital, as they can propagate into the allometries they inform. This study underscores the potential of TLS for accurate H and D measurements in tropical rainforests, essential for refining tree allometries.

Toxoplasma gondii Exposure and Dietary Habits of Two Sympatric Carnivores in the Valdivian Temperate Rainforest, Southern Chile.

Toxoplasma gondii, a parasitic protozoan, may infect most warm-blooded animals, including humans and carnivores. Our study focused on alien-invasive American minks (Neogale vison) and domestic cats (Felis catus) in the Valdivian Temperate Rainforest, Chile. The main goal was to investigate the relationship between their dietary habits and T. gondii exposure in the Valdivia River watershed. To detect T. gondii exposure, blood serum samples from 49 domestic cats and 40 American minks were analyzed using an ELISA, and stable isotope analysis of δ15N and δ13C from vibrissae was performed to determine the dietary habits of both species. Relationships between T. gondii exposure and dietary habits were explored using generalized linear mixed-effects models. American minks that were T. gondii seropositive exhibited a broader prey range compared to seropositive domestic cats, with minimal dietary overlap between the two groups. Exposure of domestic cats to T. gondii had no significant association with any isotope value or prey item in their diet. In American minks, we found a positive and significant association between the proportion of Domestic chicken (Gallus gallus domesticus) in the diet and high δ15N values with T. gondii exposure. This suggests that domestic species prey related to anthropogenic areas, and the consumption of high-trophic-level prey, may contribute to T. gondii exposure in American minks. Conversely, contrary to previous hypotheses, consumption of rodents showed no significant association with T. gondii exposure in either species. Our findings emphasize the importance of further research to investigate trophic interactions in the transmission dynamics of T. gondii in the Valdivian Temperate Rainforest.

Cloning Cellulase Genes from Victoria Falls Rainforest Decaying Logs Metagenome.

The Victoria Falls rainforest is a protected site whose forest floors harbor a host of cellulolytic microorganisms involved in biomass degradation. This study collected decaying logs and soil from the rainforest for bioprospecting cellulases from their metagenomes. Metagenomic DNA was isolated from the compound sample. Degenerate cellulase primers were used to amplify cellulase genes in the metagenome. The resulting amplicons cloned into Z-competent Escherichia coli DH5α were analyzed by functional screening for the production of cellulase extracellularly. Functional screening of the clones resulted in one clone (Clone-i) testing positive for extracellular cellulase production. Submerged fermentation of Clone-i was carried out for cellulase production. The cellulases were characterized to determine their activity's optimum pH and temperature. The diversity of the cellulases produced by Clone-i was determined. Clone-i's optimum enzyme activity was observed after 72 hours of incubation at 50°C and pH 5. Clone-i produced 80% more exoglucanases as compared to endoglucanases. The cellulolytic Clone-i' isolate shows Victoria Falls rainforest's potential as an enzyme bioprospecting site, reflecting that metagenomics is a valuable tool in microbial ecology.

Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees.

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.