A critical comparison of integral projection and matrix projection models for demographic analysis

Structured demographic models are among the most common and useful tools in population biology. However, the introduction of integral projection models (IPMs) has caused a profound shift in the way many demographic models are conceptualized. Some researchers have argued that IPMs, by explicitly representing demographic processes as continuous functions of state variables such as size, are more statistically efficient, biologically realistic, and accurate than classic matrix projection models, calling into question the usefulness of the many studies based on matrix models. Here, we evaluate how IPMs and matrix models differ, as well as the extent to which these differences matter for estimation of key model outputs, including population growth rates, sensitivity patterns, and life spans. First, we detail the steps in constructing and using each type of model. Second, we present a review of published demographic models, concentrating on size-based studies, which shows significant overlap in the way IPMs and matrix models are constructed and analyzed. Third, to assess the impact of various modeling decisions on demographic predictions, we ran a series of simulations based on size-based demographic data sets for five biologically diverse species. We found little evidence that discrete vital rate estimation is less accurate than continuous functions across a wide range of sample sizes or size classes (equivalently bin numbers or mesh points). Most model outputs quickly converged with modest class numbers (≥10), regardless of most other modeling decisions. Another surprising result was that the most commonly used method to discretize growth rates for IPM analyses can introduce substantial error into model outputs. Finally, we show that empirical sample sizes generally matter more than modeling approach for the accuracy of demographic outputs. Based on these results, we provide specific recommendations to those constructing and evaluating structured population models. Both our literature review and simulations question the treatment of IPMs as a clearly distinct modeling approach or one that is inherently more accurate than classic matrix models. Importantly, this suggests that matrix models, representing the vast majority of past demographic analyses available for comparative and conservation work, continue to be useful and important sources of demographic information.Support for this work was provided by NSF awards 1146489, 1242558, 1242355, 1353781, 1340024, 1753980, and 1753954, 1144807, 0841423, and 1144083. Support also came from USDA NIFA Postdoctoral Fellowship (award no. 2019-67012-29726/project accession no. 1019364) for R. K. Shriver; the Swiss Polar Institute of Food and Agriculture for N. I. Chardon; the ICREA under the ICREA Academia Programme for C. Linares; and SERDP contract RC-2512 and USDA National Institute of Food and Agriculture, Hatch project 1016746 for A .M. Louthan. This is Contribution no. 21-177-J from the Kansas Agricultural Experiment Station

Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide

Copper-Binding Domain Variation in a Novel Murine Lysyl Oxidase Model Produces Structurally Inferior Aortic Elastic Fibers Whose Failure Is Modified by Age, Sex, and Blood Pressure

Lysyl oxidase (LOX) is a copper-binding enzyme that cross-links elastin and collagen. The dominant LOX variation contributes to familial thoracic aortic aneurysm. Previously reported murine Lox mutants had a mild phenotype and did not dilate without drug-induced provocation. Here, we present a new, more severe mutant, Loxb2b370.2Clo (c.G854T; p.Cys285Phe), whose mutation falls just N-terminal to the copper-binding domain. Unlike the other mutants, the C285F Lox protein was stably produced/secreted, and male C57Bl/6J Lox+/C285F mice exhibit increased systolic blood pressure (BP; p p p p = 2.8 × 10−8 for breaks by histology) that become increasingly disrupted with age (p p = 6.8 × 10−4). Aortic dilation was amplified in males vs. females (p p = 9.83 × 10−30) and TGFβ-responsive genes (p = 7.42 × 10−29), and aortas from older C57Bl/6J Lox+/C285F mice showed both enhanced susceptibility to elastase (p p Lox+/C285F mutants produce dysfunctional elastic fibers that show increased susceptibility to proteolytic damage. Over time, the progressive weakening of the connective tissue, modified by sex and blood pressure, leads to worsening aortic disease