El bentos y su fracción derivante: Composición y estructura en un arroyo regulado (Achiras, Córdoba)

Flow regulation modifies the physico-chemical conditions of the fluvial system and consequently its biota. The aim of this study was to analyze the composition and structure of benthic and drift, upstream and downstream of the Achiras dam before and after construction. Sampling of benthos (Surber nets, 0.09 m2 and 300 μ) and drift (nets 1 m long, 300 μ and 0.0192 m2) were performed in high water and low water periods. The organisms were identified to the lowest  possible taxonomic level and benthic Feeding Functional Groups were identified. Density, taxonomic richness, Shannon diversity and evenness for benthos and drift were calculated. Data were compared by three-way ANOVAs. The structure of both assemblages varied spatially and temporally. Benthic community showed a total of 110 taxa, corresponding to 8 phyla, while drift assemblage 55 taxa corresponding to 6 phyla. In both assemblages, the phylum Arthropoda was the most abundant. In the site below the dam and in the post- construction period, the benthos richness was greater, while drift evenness exhibited the highest value at the site below the dam during low water period. The filtering collectors and scrapers showed significant differences between year, site and hydrological period. The chironomids Tanytarsus sp. and Rheotanytarsus sp. were the most abundant among collectors while filtering Camelobaetidius penai andStenophysa sp. among the scrapers. Data obtained in this study show that both data of benthic structure and its drifting fraction as the GFA data would indicate no significant changes attributable to dam effect. Longer studies would be required since in regulated systems most ecological changes happen more slowly than observed immediately.La regulación del flujo modifica las condiciones físico-químicas del sistema fluvial y, en consecuencia, su biota. El objetivo de este estudio fue analizar la composición y la estructura del bentos y la deriva, aguas arriba y aguas abajo de la presa de Achiras antes y después de la construcción. Se muestreo el bentos (redes Surber, 0.09 m2 y 300 μ) y la deriva (redes de 1 m de largo, 300 μ y 0.0192 m2)  en periodos de agua alta y baja. Los organismos se identificaron al nivel taxonómico más bajo posible y se identificaron los Grupos Funcionales de Alimentación del bentos. Se calcularon la densidad, la riqueza taxonómica, la diversidad de Shannon y la uniformidad para el bentos y la deriva. Los datos se compararon mediante ANOVA de tres vías. La estructura de ambos conjuntos varió espacial y temporalmente. La comunidad bentónica mostró un total de 110 taxones, que corresponden a 8 phyla, mientras que el conjunto de la deriva 55 taxones correspondientes a 6 phyla. En ambos conjuntos, el phylum Arthropoda fue el más abundante. En el sitio aguas abajo de la presa y en el período posterior a la construcción, la riqueza del bentos fue mayor, mientras que la uniformidad de la deriva exhibió el valor más alto en el sitio aguas abajo de la presa durante el período de poca agua. Los colectores filtradores y raspadores mostraron diferencias significativas entre el año, el sitio y el período hidrológico. Los quironómidos Tanytarsus sp. y Rheotanytarsus sp. fueron los más abundantes entre los colectores mientras que Camelobaetidius penai y Stenophysa sp. lo fueron entre los raspadores. Los datos obtenidos en este estudio muestran que tanto los datos de la estructura bentónica como su fracción de deriva como los datos de GFA no indicarían cambios significativos atribuibles al efecto de presa. Se requerirían estudios más largos, ya que en los sistemas regulados, la mayoría de los cambios ecológicos ocurren más lentamente de lo que se observa de inmediato

Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan-tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan-tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey's height, community wood density and aboveground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot- and site-level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey's height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium-sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate-diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change

Pan-tropical prediction of forest structure from the largest trees

Aim: Large tropical trees form the interface between ground and airborne observations, offering a unique opportunity to capture forest properties remotely and to investigate their variations on broad scales. However, despite rapid development of metrics to characterize the forest canopy from remotely sensed data, a gap remains between aerial and field inventories. To close this gap, we propose a new pan‐tropical model to predict plot-level forest structure properties and biomass from only the largest trees. Location: Pan‐tropical. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 867 plots distributed among 118 sites across the tropics, we tested the prediction of the quadratic mean diameter, basal area, Lorey’s height, community wood density and above ground biomass (AGB) from the ith largest trees. Results: Measuring the largest trees in tropical forests enables unbiased predictions of plot‐ and site‐level forest structure. The 20 largest trees per hectare predicted quadratic mean diameter, basal area, Lorey’s height, community wood density and AGB with 12, 16, 4, 4 and 17.7% of relative error, respectively. Most of the remaining error in biomass prediction is driven by differences in the proportion of total biomass held in medium‐sized trees (50–70 cm diameter at breast height), which shows some continental dependency, with American tropical forests presenting the highest proportion of total biomass in these intermediate‐diameter classes relative to other continents. Main conclusions: Our approach provides new information on tropical forest structure and can be used to generate accurate field estimates of tropical forest carbon stocks to support the calibration and validation of current and forthcoming space missions. It will reduce the cost of field inventories and contribute to scientific understanding of tropical forest ecosystems and response to climate change