Responses of Aquatic Saproxylic Macroinvertebrates to Reduced-Impact Logging in Central Amazonia.

Reduced-impact logging (RIL) is an alternative land use because it reduces damage to forest cover in comparison with clear-cut practices. However, management practices adopted in RIL can affect wood availability and, consequently, fauna associated with dead wood during part of their life cycle (saproxylic). In this study, we evaluated whether aquatic saproxylic macroinvertebrates are affected by reduced-impact logging in Central Amazonia. We selected six streams in areas under reduced-impacted logging and six in primary forest areas and collected submerged woody debris. We did not find any differences in water pH, conductivity, and wood availability between reduced-impacted forest and primary forest streams. We found 248 saproxylic aquatic macroinvertebrates belonging to 37 taxa. We found five wood specialist (Dryops, Lutrochus, Stenochironomus, Oukuriella, and Endotribelos) and 32 generalists, totalling 98 and 150 individuals, respectively. In general, our results show that reduced-impact logging does not affect richness, abundance, and composition of saproxylic macroinvertebrates. The main explanation for this pattern is that management practices do not change important macroinvertebrate niche dimensions, including wood availability and the water's chemical and physical variables. Thus, controlled logging, such as applied in the area of the Central Amazonian streams studied, opens a new prospect for insect conservation and commercial exploitation of wood, which is not possible when clear-cut practices are adopted.

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can / A distinção taxonômica de comunidades de macroinvertebrados de córregos da Mata Atlântica não pode ser previsto pela paisagem e por variáveis climáticas, mas os índices de biodiversidade tradicional podem

Predicting how anthropogenic activities may influence the various components of biodiversity is essential for finding ways to reduce diversity loss. This challenge involves: a) understanding how environmental factors influence diversity across different spatial scales, and b) developing ways to measure these relationships in a way that is fast, economical, and easy to communicate. In this study, we investigate whether landscape and bioclimatic variables could explain variation in biodiversity indices in macroinvertebrate communities from 39 Atlantic Forest streams. In addition to traditional diversity measures, i.e., species richness, abundance and Shannon index, we used a taxonomic distinctness index that measures the degree of phylogenetic relationship among taxa. The amount of variation in the diversity measures that was explained by environmental and spatial variables was estimated using variation partitioning based on multiple regression. Our study demonstrates that taxonomic distinctness does not respond in the same way as the traditional used in biodiversity studies. We found no evidence that taxonomic distinctness responds predictably to variation in landscape metrics, indicating the need for the incorporation of predictors at multiple scales in this type of study. The lack of congruence between taxonomic distinctness and other indices and its low predictability may be related to the fact that this measure expresses long-term evolutionary adaptation to ecosystem conditions, while the other traditional biodiversity metrics respond to short-term environmental changes.(AU)

Prever como as atividades antrópicas podem influenciar os vários componentes da biodiversidade é essencial para encontrar maneiras de reduzir a perda de diversidade. Este desafio envolve: a) a compreensão de como os fatores ambientais influenciam a diversidade em diferentes escalas espaciais e, b) desenvolver formas de medir essas relações de uma maneira rápida, econômica e de fácil comunicação. Neste estudo, nós investigamos se a paisagem e as variáveis bioclimáticas podem explicar a variação nos índices de biodiversidade em comunidades de macroinvertebrados de 39 riachos de Mata Atlântica. Adicionalmente às medidas tradicionais de diversidade, por ex.: riqueza de espécies, abundância e índice de Shannon, nos utilizamos índice de distinção taxonômica que mede o grau de relação filogenética dentre os taxa. A quantidade de variação nas medidas de diversidade que foi explicado por variáveis ambientais e espaciais foi estimada utilizando a variação particionada baseada em regressão múltipla. O presente estudo demonstra que o índice de distinção taxonômica não responde da mesma maneira que os índices tradicionais utilizados em estudos de biodiversidade. Nós não encontramos nenhuma evidência de que a distinção taxonômica responde previsivelmente à variação métricas da paisagem, indicando a necessidade de incorporação de preditores em múltiplas escalas neste tipo de estudo. A falta de congruência entre a distinção taxonômica e outros índices e sua baixa previsibilidade pode estar relacionada com o fato de esta medida expressar adaptações evolutivas de longo prazo para as condições ambientais, enquanto as outras métricas tradicionais respondem às alterações ambientais de curto prazo.(AU)

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can.

Predicting how anthropogenic activities may influence the various components of biodiversity is essential for finding ways to reduce diversity loss. This challenge involves: a) understanding how environmental factors influence diversity across different spatial scales, and b) developing ways to measure these relationships in a way that is fast, economical, and easy to communicate. In this study, we investigate whether landscape and bioclimatic variables could explain variation in biodiversity indices in macroinvertebrate communities from 39 Atlantic Forest streams. In addition to traditional diversity measures, i.e., species richness, abundance and Shannon index, we used a taxonomic distinctness index that measures the degree of phylogenetic relationship among taxa. The amount of variation in the diversity measures that was explained by environmental and spatial variables was estimated using variation partitioning based on multiple regression. Our study demonstrates that taxonomic distinctness does not respond in the same way as the traditional used in biodiversity studies. We found no evidence that taxonomic distinctness responds predictably to variation in landscape metrics, indicating the need for the incorporation of predictors at multiple scales in this type of study. The lack of congruence between taxonomic distinctness and other indices and its low predictability may be related to the fact that this measure expresses long-term evolutionary adaptation to ecosystem conditions, while the other traditional biodiversity metrics respond to short-term environmental changes.