Biology subjects

Harte, J.

Publications and source records attributed to Harte, J..

6 recordsLinked to original sources

bioRxiv2026

Modeling and Detecting Downward Causation in Disease Transmission

We compare two epidemic models: the deterministic SIR (Susceptible-Infected-Recovered) model and the maximum-entropy-based DyMES (Dynamic Maxent across Entwined Scales) framework. In contrast to the widely used SIR model, the recently proposed DyMES model incorporates both top-down and bottom-up mechanisms and thus can capture local responses to global behavior. We simulate both models in three disease scenarios using parameter values drawn from the literature and analyze trends in the epidemic trajectories. Increasing the strength of downward causation lowers the peak but extends the time taken to return to the initial state, changing the trajectory from an SIR-like rise and fall to an epidemic with a long tail. By combining the Maxent inference procedure and top-down causation, the DyMES model predicts the probability distribution of disease incidence across population sub-aggregates.

systems biology↗

bioRxiv2026

A maximum entropy perspective reveals deviations from steady state during active diversification

Ecosystems are rarely at steady state, yet most theory predicting universal biodiversity patterns assumes they are. Here, we test whether and how eco-evolutionary dynamics drive departures from steady state by combining arthropod community data from the geologic chronosequence of the Hawaiian Archipelago with the Maximum Entropy Theory of Ecology (METE), a minimalist steady-state framework that simultaneously predicts species abundance distributions (SADs) and individual metabolic rate distributions (IPDs). The chronosequence of the Hawaiian Archipelago has yielded insights into eco-evolutionary processes because ecosystems growing on different aged substrates offer snapshots of community assembly with different histories. We find that deviations from METE peak at geologically middle-aged sites (150 Kya-1.4 Mya), consistent with active adaptive radiation pushing communities away from statistical steady state. Within-site {beta}-diversity, which also peaks at middle-aged sites, robustly predicts deviations from METE across all sites, while the proportion of non-native species predicts deviations only after excluding the geologically youngest site. Partitioning {beta}-diversity between native and non-native species resolves this discrepancy: at the youngest site, non-native species are distributed homogeneously and do not elevate {beta}-diversity despite their high proportional representation. Together, these results are consistent with a trajectory from young, dispersal-assembled communities near statistical steady state, through an eco-evolutionary non-steady-state transition driven by diversification, to a new stable steady state at the oldest sites. Our findings suggest that periods of active diversification create windows of ecological instability that may facilitate biological invasion, with implications for understanding invasion dynamics in biodiversity hotspots.

ecology↗

bioRxiv2026

Lactate promotes IL-8 secretion in human alveolar macrophages through GPR132 and lipid metabolic reprogramming

Alveolar macrophages are the primary lung immune cell. They play a crucial role in both maintenance of tissue homeostasis and the initiation of inflammation, secreting multiple immune mediators including the chemokine interleukin-8 (IL-8). Inflammatory settings are often characterised by tissue hypoxia, increased glycolytic rates and lactate secretion, yet how lactate influences alveolar macrophage function remains unclear. Here we investigated how lactate, once considered a waste-product, shapes alveolar macrophage function. To do so, primary human alveolar macrophages (hAMs) and a combination of flow cytometry, ELISA/Luminex, western blot, light microscopy, bioluminescence resonance energy transfer (BRET) and analysis of publicly available datasets were used to understand the role of lactate in lung pathological environments. We demonstrate that hAMs sense extracellular lactate via the expression of different lactate transporters (e.g. MCT1, MCT4) and receptors (i.e. GPR132). Lactate treatment of hAMs increased IL-8 secretion in a MCT1-dependent manner. Lipid metabolism and lipid droplet formation, as well as direct lactate-driven GPR132 signalling were required for lactate-dependent IL-8 release. Our findings uncover a previously unrecognised dual mechanism by which lactate orchestrates immune regulation in hAMs. Specifically, lactate-driven IL-8 production requires two distinct lactate-driven processes: uptake via MCT1, which reprograms lipid metabolism, and signaling through the lactate receptor GPR132. This functional integration of lactate transport and receptor-mediated signaling provides new mechanistic insight into lactates role in hAM biology and highlights potential targets for therapeutic intervention.

immunology↗

bioRxiv2021

Land use, macroecology, and the accuracy of the Maximum Entropy Theory of Ecology: A case study of Azorean arthropods

Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbance affect the shape of macroecological patterns, and therefore analyzing these patterns can provide insights into how ecosystems are affected by land use change. We here use arthropod census data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: native forest, exotic forest, semi-natural pasture, and intensive pasture, to examine the effects of land use type on three macroecological patterns: the species abundance distribution, the metabolic rate distribution of individuals, and the species-area relationship. The Maximum Entropy Theory of Ecology (METE) has successfully predicted these patterns across habitats and taxa in undisturbed ecosystems, and thus provides a null expectation for their shapes. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture is consistently the worst fit, and the intensive pasture is intermediately well fit. We show that the direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium, leading to greater heterogeneity in composition and complex dynamics that violate METEs assumption of static state variables. The comparative better fit for the intensive pasture plausibly results from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux. Analyzing deviations from theoretical predictions across land use type provides useful information about how land use and disturbance affect ecosystems, and such comparisons could be useful across other habitats and taxa.

ecology↗

bioRxiv2019

Density dependence and a colonization rule predict spatial patterning

Spatial patterns in ecology contain useful information about underlying mechanisms and processes. Although there are many summary statistics used to quantify these spatial patterns, there are far fewer models that directly link explicit ecological mechanisms to observed patterns easily derived from available data. We present a model of intraspecific spatial aggregation that quantitatively relates static spatial patterning to negative density dependence. Individuals are placed according to the colonization rule consistent with the Maximum Entropy Theory of Ecology (METE), and die with probability proportional to their abundance raised to a power , a parameter indicating the degree of density dependence. Our model shows quantitatively and generally that increasing density dependence randomizes spatial patterning. = 1 recovers the strongly aggregated METE distribution that is consistent with many ecosystems empirically, and as [->] 2 our prediction approaches the binomial distribution consistent with random placement. In between our model predicts less aggregation than METE, but more than random placement. We additionally relate our mechanistic parameter to the statistical aggregation parameter k in the negative binomial distribution, giving it an ecological interpretation in the context of density dependence. We use our model to analyze two contrasting datasets, a 50 ha tropical forest and a 64 m2 serpentine grassland plot. For each dataset, we infer for individual species as well as a community parameter. We find that is generally larger in the tightly packed forest than the sparse grassland, and the degree of density dependence increases at smaller scales. These results are consistent with current understanding in both ecosystems, and we infer this underlying density dependence using only empirical spatial patterns. Our model can easily be applied to other datasets where spatially explicit data are available.

ecology↗

bioRxiv2018

Disturbance macroecology: integrating disturbance ecology and macroecology in different-age post-fire stands of a closed-cone pine forest as a case study

Macroecological studies have generally restricted their scope to relatively steady-state systems, and as a result, how biodiversity and abundance metrics are expected to scale in disturbance-dependent ecosystems is unknown. We examine macroecological patterns in a fire-dependent forest of Bishop pine (Pinus muricata). We target two different-aged stands in a stand-replacing fire regime, one a characteristically mature stand with a diverse understory, and one more recently disturbed by a stand-replacing fire (17 years prior to measurement). We compare the stands using macroecological metrics of species richness, abundance and spatial distributions that are predicted by the Maximum Entropy Theory of Ecology (METE), an information-entropy based theory that has proven highly successful in predicting macroecological metrics across a wide variety of systems and taxa. Ecological patterns in the mature stand more closely match METE predictions than do data from the recently disturbed stand. This suggests METEs predictions are more robust in late-successional, slowly changing, or steady-state systems than those in rapid flux with respect to species composition, abundances, and organisms sizes. Our findings highlight the need for a macroecological theory that incorporates natural disturbance and other ecological perturbations into its predictive capabilities, because most natural systems are not in a steady state.

ecology↗