Influence of dry season on social wasp communities (Hymenoptera: Polistinae) in Deciduous Forest

 The seasonal deciduous forest, also known as dry forest, is characterized by the deciduity of tree species and two well-defined seasons which cause drastic changes in its physiognomy, and the seasonality of rainy periods directly impacts the forest’s biological communities. Social wasps (Vespidae: Polistinae) are well documented. However, some ecosystems in which they occur, such as the deciduous forest, are still subsampled. This study aimed to assess the response of social wasp communities to the dry season in a deciduous forest in the Mata Seca State Park, in the North of the state of Minas Gerais, Brazil. Insects were collected over 24 days divided into four field campaigns, each with six continuous days of collection (February, May, July, and November 2021), encompassing one campaign per season. All specimens were sacrificed and stored in 70% alcohol and later dry mounted for identification. The Kruskal-Wallis (KW) H test was performed to verify the difference between species richness, number of total colonies, and number of colonies of each tribe in relation to the collection station. In total, 131 colonies of eight species were located, particularly Polybia occidentalis (Olivier, 179), with 39 colonies, Polistes versicolor (Olivier, 1791), with 33, Mischocyttarus cassununga, with 21, and Protonectarina sylveirae (Saussure, 1854), with 13. Six species, five of which were from the Epiponini tribe, were collected in the four seasons. The responses of social wasps to the periods of drought in the deciduous forest vary with tribe. While Epiponini populations can keep colonies active in the dry season, Polistini cannot. Meanwhile, P. versicolor responds positively to the onset of the rainy season, increasing its population

Il ruolo delle precipitazioni occulte nella formazione e mantenimento della vegetazione forestale: il caso studio di Pantelleria

Le testimonianze storiche indicano per le isole circumsiciliane la presenza di floridi boschi che sono stati distrutti a seguito dei processi di deforestazione. In alcuni casi, dopo gli interventi di rimboschimento, la vegetazione riesce a ricostituirsi con difficoltà come a Lampedusa mentre in altri casi i processi di recupero sono molto rapidi. Un ruolo non indifferente viene svolto dalla presenza di piante in grado di diffondere propaguli ma anche dalle condizioni climatiche locali determinate sia dalla morfologia delle singole isole come, ad esempio, la presenza di rilievi montuosi, che dal particolare contesto oceanografico. I dati medi riportati dalle stazioni climatiche in termini di piovosità non giustificano in molti casi la presenza di una vegetazione forestale confermando il contributo, al ciclo idrologico, di componenti note come “precipitazioni occulte” (da condensa atmosferica o da nebbia) ed identificate correntemente come “Non-Rainfall-Water” (NRW). A dispetto dell’importanza data a questo fattore sono pochissime le informazioni quantitative, anche in ragione dello scarso grado di standardizzazione dei sistemi di misura dei processi di deposizione dell’acqua atmosferica. Nell’ambito delle indagini condotte su finanziamento del “Centre National de la Recherche Scientifique” francese (CNRS) - “Site d’Étude en Ecologie Globale, Pantelleria” e del programma CNRS-Mob-Île abbiamo avviato una indagine a Pantelleria collocando 8 microstazioni metereologiche lungo un transect ambientale dalla costa alla sommità del più importante rilievo dell’Isola (Montagna Grande, 830 m s.l.m.). La collocazione del sistema di rilevamento (umidità, temperatura, sensori di condensa e micro-lisimetri) ha reso necessaria una fase di messa a punto della strumentazione, che ha implicato anche l’individuazione e la caratterizzazione di sistemi e sensori per il rilievo ed il monitoraggio dei fenomeni di condensa atmosferica secondo approcci diversificati. Anche se ancora in modo non quantitativo, i risultati iniziali (in termini di frequenza e di durata dei fenomeni di deposizione registrati) suggeriscono come la componente NRW possa svolgere a Pantelleria un ruolo determinante nel ciclo idrologico generale, ma ulteriori osservazioni saranno necessarie per caratterizzare i fenomeni di deposizione sulle più importanti componenti del paesaggio dell’isola (vegetazione, muretti a secco, suolo

Environmental Shaping of Sponge Associated Archaeal Communities

Archaea are ubiquitous symbionts of marine sponges but their ecological roles and the influence of environmental factors on these associations are still poorly understood.We compared the diversity and composition of archaea associated with seawater and with the sponges Hymeniacidon heliophila, Paraleucilla magna and Petromica citrina in two distinct environments: Guanabara Bay, a highly impacted estuary in Rio de Janeiro, Brazil, and the nearby Cagarras Archipelago. For this we used metagenomic analyses of 16S rRNA and ammonia monooxygenase (amoA) gene libraries. Hymeniacidon heliophila was more abundant inside the bay, while P. magna was more abundant outside and P. citrina was only recorded at the Cagarras Archipelago. Principal Component Analysis plots (PCA) generated using pairwise unweighted UniFrac distances showed that the archaeal community structure of inner bay seawater and sponges was different from that of coastal Cagarras Archipelago. Rarefaction analyses showed that inner bay archaeaoplankton were more diverse than those from the Cagarras Archipelago. Only members of Crenarchaeota were found in sponge libraries, while in seawater both Crenarchaeota and Euryarchaeota were observed. Although most amoA archaeal genes detected in this study seem to be novel, some clones were affiliated to known ammonia oxidizers such as Nitrosopumilus maritimus and Cenarchaeum symbiosum.The composition and diversity of archaeal communities associated with pollution-tolerant sponge species can change in a range of few kilometers, probably influenced by eutrophication. The presence of archaeal amoA genes in Porifera suggests that Archaea are involved in the nitrogen cycle within the sponge holobiont, possibly increasing its resistance to anthropogenic impacts. The higher diversity of Crenarchaeota in the polluted area suggests that some marine sponges are able to change the composition of their associated archaeal communities, thereby improving their fitness in impacted environments

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

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