Historical changes in tree and impervious surface cover following urban renewal in a small postindustrial city.

Changes in tree cover and impervious surfaces have been observed across many cities in the United States over the past 70 years. Many municipalities are implementing tree planting programs in efforts to increase tree cover. A detailed understanding of historical changes in land cover can inform urban forest management. I applied a convolutional neural network image segmentation approach to historical aerial imagery to delineate changes in land cover in 1957, 1974, and 2017 in Utica, New York, a small, postindustrial city. The model predicted tree, pavement, and building land cover in each year with overall accuracies ranging from 82-87%. From 1957 to 2017, tree cover declined in many areas and impervious surface cover (buildings and pavement) increased. Tree cover gains largely occurred in uninhabited, natural areas; whereas, the greatest declines in tree coverage occurred in many residential areas following the start of the urban renewal efforts in 1957. Current tree planting efforts targeted at homeowners could drive disparities in future tree cover since several areas of Utica with low tree have a high proportion of renter occupied homes and a low median household income. Convolutional Neural Network approaches for image segmentation of aerial imagery are a helpful tool in understanding patterns in changes in tree and impervious surfaces. A better understanding of the legacies of historical policies and neighborhood-scale changes in land cover can assist in highlighting priorities for urban forest management and justice-oriented urban forestry approaches to urban tree planting.

Vegetation type is an important predictor of the arctic summer land surface energy budget.

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm-2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

Temporal shifts in iso/anisohydry revealed from daily observations of plant water potential in a dominant desert shrub.

Plant species are characterized along a spectrum of isohydry to anisohydry depending on their regulation of water potential (Ψ), but the plasticity of hydraulic strategies is largely unknown. The role of environmental drivers was evaluated in the hydraulic behavior of Larrea tridentata, a drought-tolerant desert shrub that withstands a wide range of environmental conditions. With a 1.5 yr time-series of 2324 in situ measurements of daily predawn and midday Ψ, the temporal variability of hydraulic behavior was explored in relation to soil water supply, atmospheric demand and temperature. Hydraulic behavior in Larrea was highly dynamic, ranging from partial isohydry to extreme anisohydry. Larrea exhibited extreme anisohydry under wet soil conditions corresponding to periods of high productivity, whereas partial isohydry was exhibited after prolonged dry or cold conditions, when productivity was low. Environmental conditions can strongly influence plant hydraulic behavior at relatively fast timescales, which enhances our understanding of plant drought responses. Although species may exhibit a dominant hydraulic behavior, variable environmental conditions can prompt plasticity in Ψ regulation, particularly for species in seasonally dry climates.

Understory vegetation mediates permafrost active layer dynamics and carbon dioxide fluxes in open-canopy larch forests of northeastern Siberia.

Arctic ecosystems are characterized by a broad range of plant functional types that are highly heterogeneous at small (~1-2 m) spatial scales. Climatic changes can impact vegetation distribution directly, and also indirectly via impacts on disturbance regimes. Consequent changes in vegetation structure and function have implications for surface energy dynamics that may alter permafrost thermal dynamics, and are therefore of interest in the context of permafrost related climate feedbacks. In this study we examine small-scale heterogeneity in soil thermal properties and ecosystem carbon and water fluxes associated with varying understory vegetation in open-canopy larch forests in northeastern Siberia. We found that lichen mats comprise 16% of understory vegetation cover on average in open canopy larch forests, and lichen abundance was inversely related to canopy cover. Relative to adjacent areas dominated by shrubs and moss, lichen mats had 2-3 times deeper permafrost thaw depths and surface soils warmer by 1-2°C in summer and less than 1°C in autumn. Despite deeper thaw depths, ecosystem respiration did not differ across vegetation types, indicating that autotrophic respiration likely dominates areas with shrubs and moss. Summertime net ecosystem exchange of CO2 was negative (i.e. net uptake) in areas with high shrub cover, while positive (i.e. net loss) in lichen mats and areas with less shrub cover. Our results highlight relationships between vegetation and soil thermal dynamics in permafrost ecosystems, and underscore the necessity of considering both vegetation and permafrost dynamics in shaping carbon cycling in permafrost ecosystems.

The diversity of experimental organisms in biomedical research may be influenced by biomedical funding.

Contrary to concerns of some critics, we present evidence that biomedical research is not dominated by a small handful of model organisms. An exhaustive analysis of research literature suggests that the diversity of experimental organisms in biomedical research has increased substantially since 1975. There has been a longstanding worry that organism-centric funding policies can lead to biases in experimental organism choice, and thus negatively impact the direction of research and the interpretation of results. Critics have argued that a focus on model organisms has unduly constrained the diversity of experimental organisms. The availability of large electronic databases of scientific literature, combined with interest in quantitative methods among philosophers of science, presents new opportunities for data-driven investigations into organism choice in biomedical research. The diversity of organisms used in NIH-funded research may be considerably lower than in the broader biomedical sciences, and may be subject to greater constraints on organism choice.

Seasonal stomatal behavior of a common desert shrub and the influence of plant neighbors.

Stomata simultaneously regulate plant carbon gain and water loss, and patterns of stomatal conductance (g(s)) provide insight into water use strategies. In arid systems, g(s) varies seasonally based on factors such as water availability and temperature. Moreover, the presence and species identity of neighboring plants likely affects g(s) of the focal plant by altering available soil water and microclimate conditions. We investigated stomatal behavior in Larrea tridentata, a drought-tolerant, evergreen shrub occurring throughout the arid southwestern United States. We measured g(s) in Larrea over multiple seasons in the presence of neighbors representing different woody species. The data were analyzed in the context of a commonly used phenomenological model that relates g(s) to vapor pressure deficit (D) to understand spatial and temporal differences in stomatal behavior. We found that g(s) in Larrea was affected by neighborhood association, and these effects varied seasonally. The greatest effect of neighborhood association on g(s) occurred during the winter period, where Larrea growing alone (without neighbors) had higher g(s) compared to Larrea growing with neighbors. Larrea's stomatal sensitivity to D and reference conductance (i.e., g(s) at D = 1 kPa) also differed significantly among different neighbor associations. Random effects indicated reference g(s) varied over short time scales (daily), while stomatal sensitivity showed little daily or seasonal variation, but was notably affected by neighbor associations such that neighboring species, especially trees, reduced Larrea's sensitivity to D. Overall, seasonal dynamics and neighborhood conditions appear critical to understanding temporal and spatial variation in Larrea's physiological behavior.