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

Parasitismo natural em moscas-das-frutas (Diptera: Tephritidae) no semiárido do sudoeste da Bahia, Brasil

Parasitoides são importantes agentes de controle natural de tefritídeos, e os conhecimentos sobre as relações tritróficas podem subsidiar o manejo destas pragas. Este trabalho objetivou estimar índices de parasitismo em moscas-das-frutas, em 21 espécies vegetais, e identificar as espécies de parasitoides associados, nas condições do semiárido do sudoeste da Bahia. Oito hospedeiros apresentaram infestação por Anastrepha spp. e, destes, em quatro, ocorreu parasitismo superior a 20,0%, sendo: 20,8% (Ziziphus joazeiro L.); 21,3% (Spondias tuberosa L.); 32,4% (Spondias purpurea L.) e 57,1% (Malpighia emarginata L.). Os parasitoides coletados pertencem à família Braconidae, sendo 89% de Doryctobracon areolatus e 11% de Asobara anastrephae

Parasitismo natural em moscas-das-frutas (Diptera: Tephritidae) no semiárido do sudoeste da Bahia, Brasil Natural parasitism in fruit-flies in the fruticulture area of anagé, semi-arid of southwestern Bahia, Brazil

Parasitoides são importantes agentes de controle natural de tefritídeos, e os conhecimentos sobre as relações tritróficas podem subsidiar o manejo destas pragas. Este trabalho objetivou estimar índices de parasitismo em moscas-das-frutas, em 21 espécies vegetais, e identificar as espécies de parasitoides associados, nas condições do semiárido do sudoeste da Bahia. Oito hospedeiros apresentaram infestação por Anastrepha spp. e, destes, em quatro, ocorreu parasitismo superior a 20,0%, sendo: 20,8% (Ziziphus joazeiro L.); 21,3% (Spondias tuberosa L.); 32,4% (Spondias purpurea L.) e 57,1% (Malpighia emarginata L.). Os parasitoides coletados pertencem à família Braconidae, sendo 89% de Doryctobracon areolatus e 11% de Asobara anastrephae.<br>Parasitoids are important natural control agents of tephritids and knowledge about the tritrophic relationships can support the management of these pests. This study aimed to estimate of parasitism indexes in fruit flies in 21 plant species and identify the species of parasitoids associated, in semiarid conditions of Southwestern Bahia. Eight hosts showed infestation by Anastrepha spp. and, of these, four occurred parasitism above 20.0%, of which: 20.8% (Ziziphus joazeiro L.); 21.3% (Spondias tuberosa L.); 32.4% (Spondias purpurea L.) and 57.1% (Malpighia emarginata L.). The collected parasitoids belong to the Braconidae family, 89% of Doryctobracon areolatus and 11% of Asobara anastrephae

First record of the association of banana (Musa sp.) and Ceratitis capitata (Widemann, 1824) in Brazil

Abstract Brazil is the fourth world’s largest banana (Musa spp.) producer and largest consumer. Mediterranean fruit fly Ceratitis capitata (Wiedemann, 1824) (Diptera: Tephritidae) is the main pest of quarantine importance in the exploration of fresh fruits. This species has shown wide ecological plasticity, with adaptation in several native and exotic hosts and different edaphoclimatic conditions. In November 2017 and March 2018, banana samples of AAB subgroup, Prata Anã, Prata Pacovan and Prata BRS Princesa, were collected from orchards located in the fruit producing region of São Francisco, Juazeiro, Bahia, Brazil. Fruits were sent to the laboratory for processing aimed at obtaining adults. A total of 177 tephritid pupae were obtained in Prata Anã variety, emerging 106 C. capitata adults. The total infestation rates in puparia kg fruit-1 and puparia fruit-1 were 7.45 and 0.70, respectively. Thus, the association between banana and C. capitata was recorded for the first time in Brazil and the probable implications related to this bitrophic association will be discussed