AVALIAÇÃO DO SUCESSO DA RESTAURAÇÃO FLORESTAL DE MATAS CILIARES NA TRANSIÇÃO AMAZÔNIA-CERRADO EM MATO GROSSO

Monitoring is an important practice for analyzing the quality of forest restoration projects. This study evaluates the success of forest restoration in three areas of riparian forest, in the state of Mato Grosso, in the transition between the Amazon and Cerrado biomes. Eleven plots measuring 12 x 30 m were installed in areas 1 (A1) and 3 (A3) and 12 in area 2 (A2). Planting and natural regeneration, área coverage by grasses and calculation of phytosociological parameters were evaluated. A total of 1107 planted individuals, 30 species and 18 families were marked and identified, with emphasis on Fabaceae, Bignoniaceae and Anacardiaceae. The mean density and basal area were 902 ind/ha and 10.51 m²/ha, respectively. Senegalia tenuifolia (L.) Britton & Rose, Hymenaea courbaril L. and Inga vera Willd. stood out as the most representative species in the study, with emphasis on S. tenuifolia in A2, with a regenerating overpopulation (8,425.93 ind/ there is). The average canopy cover was 27.8% and the incidence of grasses was significant in two of the three areas. After seven years, the areas cannot be considered restored and adaptive management practices would facilitate the direction to the planned ecological trajectory, however, further assessments are needed to better support these actions.Este estudo avaliou o sucesso da restauração florestal de três áreas de mata ciliar, na transição entre os biomas Amazônia e Cerrado em Mato Grosso. Onze parcelas de 12 x 30 m foram instaladas nas áreas 1 (A1) e 3 (A3) e doze parcelas na área 2 (A2). Foram avaliados o plantio e a regeneração natural através de análise fitossociológica, índices de diversidade e similaridade e cobertura das áreas por gramíneas. Um total de 1107 indivíduos plantados, 30 espécies e 18 famílias foram avaliadas, com destaque para Fabaceae, Bignoniaceae e Anacardiaceae. A densidade variou entre 752 e 981 ind./ha e a área basal entre 7,58 e 12,64 m²/ha. Senegalia tenuifolia (L.) Britton & Rose, Hymenaea courbaril L. e Inga vera Willd. destacaram-se como espécies mais representativas no plantio segundo o IVI, com ênfase para S. tenuifolia na A2, com uma superpopulação regenerante (8.425,93 ind./ha). A cobertura de copa média foi de 27,8% e a incidência de gramíneas foi expressiva em duas das três áreas. Após sete anos, as áreas não podem ser consideradas totalmente restauradas e práticas de manejo adaptativo facilitariam o direcionamento à trajetória ecológica desejável, entretanto, são necessárias novas avaliações da dinâmica e trajetória sucessional desses ecossistemas. Palavras-chave: monitoramento; florestas tropicais; recuperação de áreas degradadas.   Evaluation of the success of forest restoration of riparian forests in the Amazon-Cerrado transition in Mato Grosso   ABSTRACT: This study evaluated the success of forest restoration in three areas of riparian forest, in the transition between the Amazon and Cerrado biomes in Mato Grosso. Eleven 12 x 30 m plots were installed in areas 1 (A1) and 3 (A3) and twelve plots in area 2 (A2). The evaluation was made and the natural sociological coverage through the evaluation, diversity and similarity indices and coverage of grassy areas. A total of 1107 planted individuals, 30 species and 18 families were evaluated, with emphasis on Fabaceae, Bignoniaceae and Anacardiaceae. The density varied between 752 and 981 ind./ha and the basal area between 7.58 and 12.64 m²/ha. Senegalia tenuifolia (L.) Britton & Rose, Hymenaea courbaril L. and Inga vera Willd. they stood out as the most representative species in planting according to the IVI, with emphasis on S. tenuifolia in A2, with a regenerating overpopulation (8,425.93 ind./ha). The average canopy cover was 27.8% and the incidence of grasses was significant in two of the three areas. After seven years, the areas cannot be considered fully restored and adaptive management practices would facilitate the direction to the desirable ecological trajectory, however, new assessments of the dynamics and successional trajectory of these ecosystems are needed. Keywords: monitoring; tropical forests; recovery of degraded areas

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