Small forest losses degrade stream macroinvertebrate assemblages in the eastern Brazilian Amazon

Generally, habitat loss and fragmentation negatively affect biota, often in nonlinear ways. Such nonlinear responses suggest the existence of critical limits for habitat loss beyond which taxa experience substantial changes. Therefore, we identified change points for aquatic macroinvertebrate assemblages at both local-riparian and catchment extents in response to a forest-loss gradient in agriculture-altered landscapes of 51 small (1st to 3rd Strahler order) eastern Amazon streams. We used Threshold Indicator Taxa Analysis (TITAN) to identify change points for individual taxa and segmented regression analysis for assemblage richness. Considering the patterns of the cumulative frequency distributions of sum(Z−) maxima across bootstrap replications, peak changes in macroinvertebrate assemblages were at ∼9% (5–95 percentiles = 1–15%) of forest-loss at the catchment extent, and at ∼1.4% (5–95 percentiles = 0–35%) of forest-loss at the local-riparian extent. Although the assemblage change point at the site extent was less than that detected at the catchment extent, the markedly lower percentile range indicates that biotic assemblages are more clearly responsive to forest-loss at the catchment/network-riparian extents than the site extent. For catchment and site extents, segmented regression analysis determined a change point for assemblage richness at 57% and 79% of forest-loss, respectively. This indicates the low capacity of total richness to separate early and synchronous decreases of sensitive taxa from gradual increases of tolerant taxa. Our results also show that it is not enough to focus management and conservation actions on riparian zones, but that conservation strategies should be expanded to entire catchments as well. The sharp decline of sensitive taxa in response to removal of a small portion of forest cover, even at catchment extents, indicates that the Brazilian Forest Code is insufficient for protecting stream macroinvertebrates. Consequently, we recommend strategies to reverse the potential collapse of aquatic biodiversity, particularly through avoiding deforestation and forest degradation, encouraging socio-economic incentives for restoring degraded areas, creating protected areas, and maintaining the current protected areas. We argue that reducing habitat loss should be a top priority for conservation planners in tropical forests because the sensitivity of aquatic biodiversity to removal of riparian forest-cover in Amazon rainforests is higher than previously thought. Therefore, the Forest Code regulatory framework needs complementary regulation that may be achived by more restrictive State and biome policies. © 2019 Elsevier Lt

Integrated terrestrial-freshwater planning doubles conservation of tropical aquatic species

Conservation initiatives overwhelmingly focus on terrestrial biodiversity, and little is known about the freshwater cobenefits of terrestrial conservation actions. We sampled more than 1500 terrestrial and freshwater species in the Amazon and simulated conservation for species from both realms. Prioritizations based on terrestrial species yielded on average just 22% of the freshwater benefits achieved through freshwater-focused conservation. However, by using integrated cross-realm planning, freshwater benefits could be increased by up to 600% for a 1% reduction in terrestrial benefits. Where freshwater biodiversity data are unavailable but aquatic connectivity is accounted for, freshwater benefits could still be doubled for negligible losses of terrestrial coverage. Conservation actions are urgently needed to improve the status of freshwater species globally. Our results suggest that such gains can be achieved without compromising terrestrial conservation goals

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Biological indicators of diversity in tropical streams: Congruence in the similarity of invertebrate assemblages

Surrogate indicators are important alternatives to overcome the shortage of total biodiversity data for planning and implementing conservation measures. The most important premise of this approach is congruence among surrogate candidates and among different assemblages. The aim of this study was to evaluate abundance and incidence congruence between invertebrate assemblages at two taxonomic resolutions (genus and family), and between invertebrate assemblage (genus) and three groups of taxa (EPT, Odonata, and Trichoptera). We also evaluated the congruence between functional groups of EPT and the taxonomic groups listed above. Data were collected from 51 stream sites distributed along a disturbance gradient in the rural area of the Paragominas municipality of the state of Pará Brazil. We used Procrustes analysis to test congruence between invertebrate assemblages at the multiple taxonomic resolutions listed previously. Family taxonomic level was a good substitute for similarity patterns measured at the genera level. EPT genus also were highly congruent with whole invertebrate assemblage (genus level) variation. Trichoptera had greater congruence with all macroinvertebrate genera than did Odonata. The congruence between EPT functional groups and groups of taxa was greater than r = 0.70. In general, taxonomic and functional metrics responded similarly to environmental conditions (water quality, channel morphology, substrate, riparian vegetation cover). Trichoptera (abundance), EPT (genera and functional groups), or invertebrate families appear to be reasonable surrogates for Amazon stream invertebrate assemblage as biological indicators for assessing and conserving streams influenced by agriculture. © 2017 Elsevier Lt

A multi-assemblage, multi-metric biological condition index for eastern Amazonia streams

Abstract Multimetric indices (MMIs) are widely used for assessing ecosystem condition and they have been developed for a variety of biological assemblages. However, when multiple assemblages are assessed at sites, the assessment results may differ because of differing physiological sensitivities to particular stressor gradients, different organism size and guilds, and the effects of different scales of disturbances on the assemblages. Those differences create problems for managers seeking to avoid type-1 and type-2 statistical errors. To alleviate those problems, we used an anthropogenic disturbance index for selecting and weighting metrics, modeled metrics against natural variability to reduce the natural variability in metrics, and developed an MMI based on both fish and aquatic insect metrics. We evaluated eight different ways of calibrating and combining candidate metrics and found that MMIs with unweighted and modeled aquatic insect and fish metrics were the preferred MMI options