Abstract
AbstractDesigns for litterfall sampling can be improved by understanding the sources of uncertainty in litterfall mass and nutrient concentration. We compared the coefficient of variation of leaf litterfall mass and nutrient concentrations (nitrogen, phosphorus, calcium, magnesium, and potassium) at different spatial scales and across years for six northern hardwood species from 23 stands in the White Mountains of New Hampshire, USA. Stands with steeper slopes (P = 0.01), higher elevations (P = 0.05), and more westerly aspect (P = 0.002) had higher interannual variation in litter mass, probably due to a litter trap design that allowed litter to blow into traps in windy years. The spatial variation of nutrient concentrations varied more across stands than within stands for all elements (P < 0.001). Phosphorus was the most spatially variable of all nutrients across stands (P < 0.001). Litter nutrient concentrations varied less from year to year than litter mass, but the magnitude of difference depended on the element and tree species. We compared the relative importance of variation in mass vs. concentration to estimates of nutrient flux by simulating different sampling intensities of one while holding the other constant. In this dataset, interannual variability of leaf litter mass contributed more to uncertainty in litterfall flux calculations than interannual variation in nutrient concentrations. Optimal sampling schemes will depend on the elements of interest and local factors affecting spatial and temporal variability.
Highlights
Leaf litterfall is probably the most commonly measured flux in forested ecosystems
Notable outliers were two CHRONOS stands, M3 and M5, which were very steep and had the highest interannual variation. When these two stands were excluded from the analysis, interannual variation (CV = 17.6% Æ 1.0%) was still significantly higher than spatial variation (10.7% Æ 0.5%) in a general linear model that included study (CHRONOS vs. multiple element limitation in northern hardwood ecosystems (MELNHE)) as a covariate (P < 0.001)
The main effect of species on spatial variability was not significant in our three-way ANOVA (P = 0.10), but there was a marginally significant (P = 0.05) interaction of species and scale. This interaction was due to red maple, which was the least variable of all species within plot (4%), and the most variable across stands (29%) based on the test of Tukey’s honestly significant differences (Fig. 2)
Summary
Leaf litterfall is probably the most commonly measured flux in forested ecosystems. It represents a major carbon and nutrient flux, it can indicate productivity and nutrient status, and it is relatively easy to measure. Some uncertainty in litterfall estimates is due to imperfect measurement, such as errors in collection, sample processing, and sample analysis. Natural variation cannot be reduced but can be better characterized by improved sampling schemes. Quantifying how these sources of variation contribute to uncertainty in nutrient flux estimates could help guide the design of litterfall sampling systems
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