Annual biomass spatial data for southern California (2001-2021): Above- and belowground, standing dead, and litter.

Biomass estimates for shrub-dominated ecosystems in southern California have been generated at national and statewide extents. However, existing data tend to underestimate biomass in shrub vegetation types are limited to one point in time, or estimate aboveground live biomass only. In this study, we extended our previously developed estimates of aboveground live biomass (AGLBM) based on the empirical relationship of plot-based field biomass measurements to Landsat normalized difference vegetation index (NDVI) and multiple environmental factors to include other vegetative pools of biomass. AGLBM estimates were made by extracting plot values from elevation, solar radiation, aspect, slope, soil type, landform, climatic water deficit, evapotranspiration, and precipitation rasters and then using a random forest model to estimate per-pixel AGLBM across our southern California study area. By substituting year-specific Landsat NDVI and precipitation data, we created a stack of annual AGLBM raster layers for each year from 2001 to 2021. Using these AGLBM data as a foundation, we developed decision rules to estimate belowground, standing dead, and litter biomass pools. These rules were based on relationships between AGLBM and the biomass of the other vegetative pools derived primarily from peer-reviewed literature and an existing spatial data set. For shrub vegetation types (our primary focus), rules were based on literature estimates by the postfire regeneration strategy of each species (obligate seeder, facultative seeder, obligate resprouter). Similarly, for nonshrub vegetation types (grasslands, woodlands) we used literature and existing spatial data sets specific to each vegetation type to define rules to estimate the other pools from AGLBM. Using a Python language script that accessed Environmental Systems Research Institute raster geographic information system utilities, we applied decision rules to create raster layers for each of the non-AGLBM pools for the years 2001-2021. The resulting spatial data archive contains a zipped file for each year; each of these files contains four 32-bit tiff files for each of the four biomass pools (AGLBM, standing dead, litter, and belowground). The biomass units are grams per square meter (g/m2 ). We estimated the uncertainty of our biomass data by conducting a Monte Carlo analysis of the inputs used to generate the data. Our Monte Carlo technique used randomly generated values for each of the literature-based and spatial inputs based on their expected distribution. We conducted 200 Monte Carlo iterations, which produced percentage uncertainty values for each of the biomass pools. Results showed, using 2010 as an example, mean biomass for the study area and percentage uncertainty for each of the pools as follows: AGLBM (905.4 g/m2 , 14.4%); standing dead (644.9 g/m2 , 1.3%); litter (731.2 g/m2 , 1.2%); and belowground (776.2 g/m2 , 17.2%). Because our methods are consistently applied across each year, the data produced can be used to inform changes in biomass pools due to disturbance and subsequent recovery. As such, these data provide an important contribution to supporting the management of shrub-dominated ecosystems for monitoring trends in carbon storage and assessing the impacts of wildfire and management activities, such as fuel management and restoration. There are no copyright restrictions on the data set; please cite this paper and the data package when using these data.

Large ecosystem-scale effects of restoration fail to mitigate impacts of land-use legacies in longleaf pine savannas.

Ecological restoration is a global priority, with potential to reverse biodiversity declines and promote ecosystem functioning. Yet, successful restoration is challenged by lingering legacies of past land-use activities, which are pervasive on lands available for restoration. Although legacies can persist for centuries following cessation of human land uses such as agriculture, we currently lack understanding of how land-use legacies affect entire ecosystems, how they influence restoration outcomes, or whether restoration can mitigate legacy effects. Using a large-scale experiment, we evaluated how restoration by tree thinning and land-use legacies from prior cultivation and subsequent conversion to pine plantations affect fire-suppressed longleaf pine savannas. We evaluated 45 ecological properties across four categories: 1) abiotic attributes, 2) organism abundances, 3) species diversity, and 4) species interactions. The effects of restoration and land-use legacies were pervasive, shaping all categories of properties, with restoration effects roughly twice the magnitude of legacy effects. Restoration effects were of comparable magnitude in savannas with and without a history of intensive human land use; however, restoration did not mitigate numerous legacy effects present prior to restoration. As a result, savannas with a history of intensive human land use supported altered properties, especially related to soils, even after restoration. The signature of past human land-use activities can be remarkably persistent in the face of intensive restoration, influencing the outcome of restoration across diverse ecological properties. Understanding and mitigating land-use legacies will maximize the potential to restore degraded ecosystems.

Mistletoes and their eucalypt hosts differ in the response of leaf functional traits to climatic moisture supply.

Trade-offs between photosynthesis and the costs of resource capture inform economic strategies of plants across environmental gradients and result in predictable variation in leaf traits. However, understudied functional groups like hemiparasites that involve dramatically different strategies for resource capture may have traits that deviate from expectations. We measured leaf traits related to gas exchange in mistletoes and their eucalypt hosts along a climatic gradient in relative moisture supply, measured as the ratio of precipitation to pan evaporation (P/Ep), in Victoria, Australia. We compared traits for mistletoes vs. hosts as functions of relative moisture supply and examined trait-trait correlations in both groups. Eucalypt leaf traits responded strongly to decreasing P/Ep, consistent with economic theory. Leaf area and specific leaf area (SLA) decreased along the P/Ep gradient, while C:N ratio, leaf thickness, N per area, and δ13C all increased. Mistletoes responded overall less strongly to P/Ep based on multivariate analyses; individual traits sometimes shifted in parallel with those of hosts, but SLA, leaf thickness, and N per area showed no significant change across the gradient. For mistletoes, leaf thickness was inversely related to leaf dry matter content (LDMC), with no relationship between SLA and mass-based N. In mistletoes, reduced costs of transpiration (reflecting their lack of roots) and abundant succulent leaf tissue help account for observed differences from their eucalypt hosts. Trait-based analysis of atypical functional types such as mistletoes help refine hypotheses based on plant economics and specialized adaptations to resource limitation.