Nutrient and stoichiometric time series measurements of decomposing coarse detritus in freshwaters.

Decomposition of coarse detritus (e.g., dead organic matter larger than ~1 mm such as leaf litter or animal carcasses) in freshwater ecosystems is well described in terms of mass loss, particularly as rates that compress mass loss into one number (e.g., a first-order decay coefficient, or breakdown rate, "k"); less described are temporal changes in the elemental composition of these materials during decomposition, with important implications for elemental cycling from microbes to ecosystems. This stands in contrast with work in the terrestrial realm, where a focus on detrital elemental cycling has provided a sharper mechanistic understanding of decomposition, especially with specific processes such as immobilization and mineralization. Notably, freshwater ecologists often measure carbon (C), nitrogen (N), and phosphorus (P), and their stoichiometric ratios in decomposing coarse materials, including carcasses, wood, leaf litter, and more, but these measurements remain piecemeal. These detrital nutrients are measurements of the entire detrital-microbial complex and are integrative of numerous processes, especially nutrient immobilization and mineralization, and associated microbial growth and death. Thus, data relevant to an elemental, mechanistically focused decomposition ecology are available in freshwaters, but have not been fully applied to that purpose. We synthesized published detrital nutrient and stoichiometry measurements at a global scale, yielding 4038 observations comprising 810 decomposition time series (i.e., measurements within a defined cohort of decomposing material through time) to build a basis for understanding the temporality of elemental content in freshwater detritus. Specifically, the dataset focuses on temporally and ontogenetically (mass loss) explicit measurements of N, P, and stoichiometry (C:N, C:P, N:P). We also collected ancillary data, including detrital characteristics (e.g., species, lignin content), water physiochemistry, geographic location, incubation system type, and methodological variables (e.g., bag mesh size). These measurements are important to unlocking mechanistic insights into detrital ontogeny (the temporal trajectory of decomposing materials) that can provide a deeper understanding of heterotroph-driven C and nutrient cycling in freshwaters. Moreover, these data can help to bridge aquatic and terrestrial decomposition ecology, across plant or animal origin. By focusing on temporal trajectories of elements, this dataset facilitates cross-ecosystem comparisons of fundamental decomposition controls on elemental fluxes. It provides a strong starting point (e.g., via modeling efforts) for comparing processes such as immobilization and mineralization that are understudied in freshwaters. Time series from decomposing leaf litter, particularly in streams, are common in the dataset, but we also synthesized ontogenies of animal-based detritus, which tend to decompose rapidly compared with plant-based detritus that contains high concentrations of structural compounds such as lignin and cellulose. Although animal-based data were rare, comprising only three time series, their inclusion in this dataset underscores the opportunities to develop an understanding of decomposition that encompasses all detrital types, from carrion to leaf litter. There are no copyright or proprietary restrictions on the dataset; please cite this data paper when reusing these materials.

Nutrient and stoichiometry dynamics of decomposing litter in stream ecosystems: A global synthesis.

Decomposing organic matter forms a substantial resource base, fueling the biogeochemical function and secondary production of most aquatic ecosystems. However, detrital N (nitrogen) and P (phosphorus) dynamics remain relatively unexplored in aquatic ecosystems relative to terrestrial ecosystems, despite fundamentally linking microbial processes to ecosystem function across broad spatial scales. We synthesized 217 published time series of detrital carbon (C), N, P, and their stoichiometric ratios (C:N, C:P, N:P) from stream ecosystems to analyze the temporal nutrient dynamics of decomposing litter using generalized additive models. Model results indicated that detritus was a net source of N (irrespective of inorganic or organic form) to the environment, regardless of initial N content. In contrast, P sink/source dynamics were more strongly influenced by the initial P content, in which P-poor litters were sinks for nutrients until these shifted to net P mineralization after ~40% mass loss. However, large variations surrounded both the N and P predictions, suggesting the importance of nonmicrobial factors such as fragmentation by invertebrates. Detrital C:N ratios converged and became more similar toward the end of the decomposition, suggesting predictable microbial functional effects throughout detrital ontogeny. C:P and N:P ratios also converged to some degree, but these model predictions were less robust than for C:N, due in part to the lower number of published detrital C:P time series. The explorations of environmental covariate effects were frequently limited by a few coincident covariate measurements across studies, but temperature, N availability, and P tended to accelerate the existing ontogenetic patterns in C:N. Our analysis helps to unite organic matter decomposition across aquatic-terrestrial boundaries by describing the basic patterns of elemental flows catalyzed by decomposition in streams, and points to a research agenda with which to continue addressing gaps in our knowledge of detrital nutrient dynamics across ecosystems.

Recovery of Partially Engorged Haemaphysalis longicornis (Acari: Ixodidae) Ticks from Active Surveillance.

The invasive Asian longhorned tick, Haemaphysalis longicornis, has rapidly spread across the northeastern United States and is associated with pathogens of public health and veterinary concern. Despite its importance in pathogen dynamics, H. longicornis blood-feeding behavior in nature, specifically the likelihood of interrupted feeding, remains poorly documented. Here, we report the recovery of partially engorged, questing H. longicornis from active tick surveillance in Pennsylvania. Significantly more engorged H. longicornis nymphs (1.54%) and adults (3.07%) were recovered compared to Ixodes scapularis nymphs (0.22%) and adults (zero). Mean Scutal Index difference between unengorged and engorged nymph specimens was 0.65 and 0.42 for I. scapularis and H. longicornis, respectively, suggesting the questing, engorged H. longicornis also engorged to a comparatively lesser extent. These data are among the first to document recovery of engorged, host-seeking H. longicornis ticks and provide initial evidence for interrupted feeding and repeated successful questing events bearing implications for pathogen transmission and warranting consideration in vector dynamics models.

Distribution and Density of Haemaphysalis longicornis (Acari: Ixodidae) on Public Lands in Pennsylvania, United States.

Since the recent introduction of the Asian longhorned tick (Haemaphysalis longicornis Neumann) in the United States, quantitative surveillance information remains lacking, which hinders accurate estimates of population structure and entomological risk. We conducted statewide, active tick surveillance from May to August 2019 and report data on H. longicornis geographical distribution and population density in Pennsylvania. In total, 615 H. longicornis were collected from four counties. Across samples recovering H. longicornis, mean density of H. longicornis was 9.2/100 m2, comparably greater than Ixodes scapularis Say (8.5/100 m2). Density of H. longicornis was also significantly greater in August, largely driven by larvae, and greater in recreational habitat types (12.6/100 m2) and in Bucks County (11.7/100 m2), situated adjacent to the location of the first U.S. discovery of intense infestations. These data are among the first to document H. longicornis from statewide tick surveillance and provide initial measures of population density enabling more quantitative characterizations of distributional patterns.