A high‐throughput method to quantify feeding rates in aquatic organisms: A case study with Daphnia

1. Food ingestion is one of the most basic features of all organisms. However, obtaining precise—and high‐throughput—estimates of feeding rates remains challenging, particularly for small, aquatic herbivores such as zooplankton, snails, and tadpoles. These animals typically consume low volumes of food that are time‐consuming to accurately measure.
2. We extend a standard high‐throughput fluorometry technique, which uses a microplate reader and 96‐well plates, as a practical tool for studies in ecology, evolution, and disease biology. We outline technical and methodological details to optimize quantification of individual feeding rates, improve accuracy, and minimize sampling error.
3. This high‐throughput assay offers several advantages over previous methods, including i) substantially reduced time allotments per sample to facilitate larger, more efficient experiments; ii) technical replicates; and iii) conversion of in vivo measurements to units (mL^‐1 hr^‐1 ind^‐1) which enables broad‐scale comparisons across an array of taxa and studies.
4. To evaluate the accuracy and feasibility of our approach, we use the zooplankton, Daphnia dentifera, as a case study. Our results indicate that this procedure accurately quantifies feeding rates and highlights differences among seven genotypes.
5. The method detailed here has broad applicability to a diverse array of aquatic taxa, their resources, environmental contaminants (e.g., plastics), and infectious agents. We discuss simple extensions to quantify epidemiologically relevant traits, such as pathogen exposure and transmission rates, for infectious agents with oral or trophic transmission.

     

Validating Landsat-based landscape metrics with fine-grained land cover data

ContextModerate-grained data may not always represent landscape structure in adequate detail which could cause misleading results. Certain metrics have been shown to be predictable with changes in scale; however, no studies have verified such predictions using independent fine-grained data.ObjectivesOur objective was to use independently derived land cover datasets to assess relationships between metrics based on fine- and moderate-grained data for a range of analysis extents. We focus on metrics that previous literature has shown to have predictable relationships across scales.MethodsThe study area was located in eastern Connecticut. We compared a 1 m land cover dataset to a 30 m resampled dataset, derived from the 1 m data, as well as two Landsat-based datasets. We examined 11 metrics which included cover areas and patch metrics. Metrics were analyzed using analysis extents ranging from 100 to 1400 m in radius.ResultsThe resampled data had very strong linear relationships to the 1 m data, from which it was derived, for all metrics regardless of the analysis extent size. Landsat-based data had strong correlations for most cover area metrics but had little or no correlation for patch metrics. Increasing analysis areas improved correlations.ConclusionsRelationships between coarse- and fine-grained data tend to be much weaker when comparing independent land cover datasets. Thus, trends across scales that are found by resampling land cover are likely to be unsuitable for predicting the effects of finer-scale elements in the landscape. Nevertheless, coarser data shows promise in predicting fine-grained for cover area metrics provided the analysis area used is sufficiently large.     

Effects of grazing intensity and grazing exclusion on litter decomposition in the temperate steppe of Nei Mongol,China

Aims Grazing intensity and grazing exclusion affect ecosystem carbon cycling by changing the plant community and soil micro-environment in grassland ecosystems. The aims of this study were: 1) to determine the effects of grazing intensity and grazing exclusion on litter decomposition in the temperate grasslands of Nei Mongol; 2) to compare the difference between above-ground and below-ground litter decomposition; 3) to identify the effects of precipitation on litter production and decomposition. Methods We measured litter production, quality, decomposition rates and soil nutrient contents during the growing season in 2011 and 2012 in four plots, i.e. light grazing, heavy grazing, light grazing exclusion and heavy grazing exclusion. Quadrate surveys and litter bags were used to measure litter production and decomposition rates. All data were analyzed with ANOVA and Pearson’s correlation procedures in SPSS. Important findings Litter production and decomposition rates differed greatly among four plots. During the two years of our study, above-ground litter production and decomposition in heavy-grazing plots were faster than those in light-grazing plots. In the dry year, below-ground litter production and decomposition in light-grazing plots were faster than those in heavy-grazing plots, which is opposite to the findings in the wet year. Short-term grazing exclusion could promote litter production, and the exclusion of light-grazing could increase litter decomposition and nutrient cycling. In contrast, heavy-grazing exclusion decreased litter decomposition. Thus, grazing exclusion is beneficial to the restoration of the light-grazing grasslands, and more human management measures are needed during the restoration of heavy-grazing grasslands. Precipitation increased litter production and decomposition, and below-ground litter was more vulnerable to the inter-annual change of precipitation than above-ground litter. Compared to the light-grazing grasslands, heavy-grazing grasslands had higher sensitivity to precipitation. The above-ground litter decomposition was strongly positively correlated with the litter N content (R² = 0.489, p < 0.01) and strongly negatively correlated with the soil total N content (R² = 0.450, p < 0.01), but it was not significantly correlated with C:N and lignin:N. Below-ground litter decomposition was negatively correlated with the litter C (R² = 0.263, p < 0.01), C:N (R² = 0.349, p < 0.01) and cellulose content (R² = 0.460, p < 0.01). Our results will provide a theoretical basis for ecosystem restoration and the research of carbon cycling.     

Aggregating land use quantity and intensity to link water quality in upper catchment of Miyun Reservoir

Eutrophication resulting from nutrient enrichment decreases water quality and harms ecosystem structure and function, and its degree is significantly affected by land use in the catchment. Quantifying the relationship between eutrophication and land use can help effectively manage land use to improve water quality. Previous studies principally utilized land use quantity as an indicator to link water quality parameters, but these studies lacked insight into the impact of land use intensity. Taking the upper catchment of Miyun Reservoir as a case study, we developed a method of aggregating land use quantity and intensity to build a new land use indicator and tested its explanatory power on water quality. Six nutrient concentrations from 52 sub-watersheds covering the whole catchment were used to characterize the spatial distribution of eutrophication. Based on spatial techniques, empirical conversion coefficients, remote sensing data, and socio-economic statistical data, land use intensity was measured and mapped visually. The new land use indicator was calculated and linked to nutrient concentrations by Pearson correlation coefficients. Results demonstrated that our new indicator incorporating intensity information can quantify the different nutrient-exporting abilities of different land use areas. Compared to traditional indicators that only incorporate land use quantity, most Pearson correlation coefficients between the new indicator and water nutrient concentrations increased. This new information enhanced the explanatory power of land use on water nutrient concentrations, and so will be able to help us understand the impact of land use on water quality and guide decision making for better land use management.     

Gender identification of shovelnose sturgeon using ultrasonic and endoscopic imagery and the application of the method to the pallid sturgeon

Monthly sampling of shovelnose sturgeon Scaphirhynchus platorynchus , a biological surrogate for the endangered pallid sturgeon Scaphirhynchus albus , was conducted to develop a multi‐seasonal profile of reproductive stages. Data collected included histological characteristics of gonads from wild caught fish and laboratory and field ultrasonic and endoscopic images. These data were used to compare effectiveness of ultrasonic and endoscopic techniques at identifying gender of adult shovelnose sturgeon at different reproductive stages. The least invasive method ( i.e . ultrasound) was least effective while the most invasive ( i.e . endoscope through an abdominal incision) was the most effective at identifying shovelnose sturgeon gender. In most cases, success rate for identifying males was greater than females, with success at identifying both genders greater in more advanced reproductive stages. Concomitantly, for most months average reproductive stage was more advanced for males than females. April and May were the months with the most advanced reproductive stage, and were the months when ultrasound was most effective. Methods were also applied in the Upper Missouri River to validate their use on pallid sturgeon Scaphirhynchus albus . Ultrasound was successful at identifying pallid sturgeon gender, however, endoscopic examination through the urogenital duct was only successful at identifying pallid sturgeon gender when the urogenital duct was not opaque.     

Competitive and facilitative relationships among three shrub species,and the role of browsing intensity and rooting depth in the Succulent Karoo,South Africa

Abstract. The nearest‐neighbour technique is used to infer competition and facilitation between the three most abundant species in a semi‐arid region of western South Africa. Relationships among the shrubs Leipoldtia schultzei and Ruschia robusta, which are leaf‐succulent members of the Mesembryanthemaceae (‘mesembs’) and Hirpicium alienatum a non‐succulent Asteraceae, were compared on two adjacent sites with different histories of browsing intensity. Competition was more prevalent and more important than facilitation. The only evidence for facilitation was found at the heavily‐browsed site where the palatable Hirpicium was larger under the unpalatable Leipoldtia. Generally the prevalence and importance of competition was reduced at the heavily‐browsed site. Strong evidence was obtained for intraspecific competition in each of the three species; also, competition was evident between the two mesembs, where Leipoldtia was competitively dominant over Ruschia, although neither species inhibited Hirpicium. Minimal competition between the mesembs and the asteraceous shrub was interpreted in terms of differentiation in rooting depth, and competition within the mesembs, in terms of overlap in rooting depth. The mesembs had the bulk of their roots in the top 5 cm of soil, while the asteraceous shrub had the bulk of its roots, and all its fine roots, at greater depths. The shallow‐rooted morphology of the mesembs is well adapted to utilize small rainfall events, which occur frequently in the Succulent Karoo, and do not penetrate the soil deeply. Modifications of existing methods are applied for analysing nearest‐neighbour interactions.     

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.