Abstract Worsening climate change impacts are amplifying the need for accurate estimates of vegetation structure and aboveground biomass density (AGBD) to assess changes in biodiversity and carbon storage. In Australia, increasing wildfire frequency and interest in the role of forests in the carbon cycle necessitates biomass mapping across large geographic extents to monitor forest change. The availability of spaceborne Light Detection and Ranging optimised for vegetation structure mapping through the Global Ecosystem Dynamics Investigation (GEDI) provides an opportunity for large-scale forest AGBD estimates of higher accuracy. This study assessed the use of the GEDI canopy height product to predict woody AGBD across five vegetation types in Western Australia: tall eucalypt forests, eucalypt open‒woodlands, low-lying heathland, tropical eucalypt savannas, and tussock and hummock grasslands. Canopy height models were developed using random forest regressions trained on GEDI canopy height discrete point data. Predictor variables included spectral bands and vegetation indices derived from synthetic aperture radar Sentinel‒1 data, and multispectral Landsat and Sentinel‒2 data. AGBD was subsequently estimated using power-law models derived by relating the predicted canopy heights to field AGBD plots. Mapping was conducted for 2020 and 2021. The accuracy of canopy height predictions varied with height quantiles; models underestimated the height of taller trees and overestimated the height of smaller trees. A similar underestimation and overestimation trend was observed for the AGBD estimates. The mean carbon stock was estimated at 69.0 ± 12.0 MgCha−1 in the tall eucalypt forests of the Warren region; 33.8 ± 5.0 MgCha−1 for the open eucalypt woodlands in the South Jarrah region; 7.1 ± 1.4 MgCha−1 for the heathland and shrublands in the Geraldton Sandplains region; 43.9 ± 4.9 MgCha−1 for the Kimberley eucalypt savanna; and 3.9 ± 1.0 MgCha−1 for the Kimberley savanna grasslands. This approach provides a useful framework for the future development of this process for fire management, and habitat health monitoring.

Abstract Significant uncertainties persist concerning how Arctic soil tundra carbon emission responds to environmental changes. In this study, 24 cores were sampled from drier (high centre polygons and rims) and wetter (low centre polygons and troughs) permafrost tundra ecosystems. We examined how soil CO2 and CH4 fluxes responded to laboratory-based manipulations of soil temperature (and associated thaw depth) and water table depth, representing current and projected conditions in the Arctic. Similar soil CO2 respiration rates occurred in both the drier and the wetter sites, suggesting that a significant proportion of soil CO2 emission occurs via anaerobic respiration under water-saturated conditions in these Arctic tundra ecosystems. In the absence of vegetation, soil CO2 respiration rates decreased sharply within the first 7 weeks of the experiment, while CH4 emissions remained stable for the entire 26 weeks of the experiment. These patterns suggest that soil CO2 emission is more related to plant input than CH4 production and emission. The stable and substantial CH4 emission observed over the entire course of the experiment suggests that temperature limitations, rather than labile carbon limitations, play a predominant role in CH4 production in deeper soil layers. This is likely due to the presence of a substantial source of labile carbon in these carbon-rich soils. The small soil temperature difference (a median difference of 1 °C) and a more substantial thaw depth difference (a median difference of 6 cm) between the high and low temperature treatments resulted in a non-significant difference between soil CO2 and CH4 emissions. Although hydrology continued to be the primary factor influencing CH4 emissions, these emissions remained low in the drier ecosystem, even with a water table at the surface. This result suggests the potential absence of a methanogenic microbial community in high-centre polygon and rim ecosystems. Overall, our results suggest that the temperature increases reported for these Arctic regions are not responsible for increases in carbon losses. Instead, it is the changes in hydrology that exert significant control over soil CO2 and CH4 emissions.

Abstract Community-based monitoring (CBM) is increasingly cited as a means of collecting valuable baseline data that can contribute to our understanding of environmental change whilst supporting Indigenous governance and self-determination in research. However, current environmental CBM models have specific limitations that impact program effectiveness and the progression of research stages beyond data collection. Here, we highlight key aspects that limit the progression of Arctic CBM programs which include funding constraints, organisational structures, and operational processes. Exemplars from collaborative environmental research conducted in the acutely climate change impacted Hamlet of Tuktoyaktuk, Inuvialuit Settlement Region (ISR), Canada, are used to identify co-developed solutions to address these challenges. These learnings from experience-based collaborations feed into a new solution-orientated model of environmental community-based research (CBR) that emphasises continuity between and community ownership in all research stages to enable a more complete research workflow. Clear recommendations are provided to develop a more coherent approach to achieving this model, which can be adapted to guide the development of successful environmental CBR programs in different research and place-based contexts.

Abstract Biodiversity-structure relationships (BSRs), which describe the correlation between biodiversity and three-dimensional forest structure, have been used to map spatial patterns in biodiversity based on forest structural attributes derived from lidar. However, with the advent of spaceborne lidar like the Global Ecosystem Dynamics Investigation (GEDI), investigators are confronted with how to predict biodiversity from discrete GEDI footprints, sampled discontinuously across the Earth surface and often spatially offset from where diversity was measured in the field. In this study, we used National Ecological Observation Network data in a hierarchical modeling framework to assess how spatially-coincident BSRs (where field-observed taxonomic diversity measurements and structural data from airborne lidar coincide at a single plot) compare with BSRs based on statistical aggregates of proximate, but spatially-dispersed GEDI samples of structure. Despite substantial ecoregional variation, results confirm cross-biome consistency in the relationship between plant/tree alpha diversity and spatially-coincident lidar data, including structural data from outside the field plot where diversity was measured. Moreover, we found that generalized forest structural profiles derived from GEDI footprint aggregates were consistently related to tree alpha diversity, as well as cross-biome patterns in beta and gamma diversity. These findings suggest that characteristic forest structural profiles generated from aggregated GEDI footprints are effective for BSR diversity prediction without incorporation of more standard predictors of biodiversity like climate, topography, or optical reflectance. Cross-scale comparisons between airborne- and GEDI-derived structural profiles provide guidance for balancing scale-dependent trade-offs between spatial proximity and sample size for BSR-based prediction with GEDI gridded products. This study fills a critical gap in our understanding of how generalized forest structural attributes can be used to infer specific field-observed biodiversity patterns, including those not directly observable from remote sensing instruments. Moreover, it bolsters the empirical basis for global-scale biodiversity prediction with GEDI spaceborne lidar.

Abstract The stratified nature of tropical forest structure had been noted by early explorers, but until recent use of satellite-based LiDAR (GEDI, or Global Ecosystems Dynamics Investigation LiDAR), it was not possible to quantify stratification across all tropical forests. Understanding stratification is important because by some estimates, a majority of the world’s species inhabit tropical forest canopies. Stratification can modify vertical microenvironment, and thus can affect a species’ susceptibility to anthropogenic climate change. Here we find that, based on analyzing each GEDI 25 m diameter footprint in tropical forests (after screening for human impact), most footprints (60%–90%) do not have multiple layers of vegetation. The most common forest structure has a minimum plant area index (PAI) at ∼40 m followed by an increase in PAI until ∼15 m followed by a decline in PAI to the ground layer (described hereafter as a one peak footprint). There are large geographic patterns to forest structure within the Amazon basin (ranging between 60% and 90% one peak) and between the Amazon (79 ± 9% sd) and SE Asia or Africa (72 ± 14% v 73 ± 11%). The number of canopy layers is significantly correlated with tree height (r 2 = 0.12) and forest biomass (r 2 = 0.14). Environmental variables such as maximum temperature (T max) (r 2 = 0.05), vapor pressure deficit (VPD) (r 2 = 0.03) and soil fertility proxies (e.g. total cation exchange capacity −r 2 = 0.01) were also statistically significant but less strongly correlated given the complex and heterogeneous local structural to regional climatic interactions. Certain boundaries, like the Pebas Formation and Ecoregions, clearly delineate continental scale structural changes. More broadly, deviation from more ideal conditions (e.g. lower fertility or higher temperatures) leads to shorter, less stratified forests with lower biomass.

Abstract Habitat fragmentation is causing an increasing amount of species loss around the world and creates problems at the population level. Many species are left as only small and isolated populations, which are vulnerable to genetic erosion and inbreeding depression. Here we present a study on the alpine blue-sowthistle (Cicerbita alpina). Due to intensive grazing the species is very rare in Scotland, where it occurs at only four small, montane sites, has never been reported to reproduce and is in need of conservation interventions. As the species can grow clonally it is unknown how many individuals remain and whether populations are affected by genetic isolation. We (1) quantified genetic diversity, inbreeding and between-population differentiation in Scotland and Norway using 15 microsatellite loci, and (2) experimentally translocated plants to new sites. Genetic diversity in Scotland was low (H E: 0.35; Allelic Richness: 1.84; 4 sites) compared to Norway (H E: 0.52; Allelic Richness: 2.56; 5 sites). The transplants were able to grow at new sites and are therefore not restricted to steep, montane ledges. While grazing is likely to be the main factor preventing range expansion, long-term genetic isolation has possibly further lowered population viability. To avoid local extinction of this species, conservation translocations and genetic rescue might be appropriate conservation interventions, but this needs to be further tested in a controlled environment and away from wild sites to avoid potential risks of outbreeding depression.

Abstract In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori, thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future.

Abstract Plant species around the world are negatively affected by habitat fragmentation and climate change. Montane willow populations in the UK have declined primarily due to grazing, as well as climate change and muirburn in certain areas. Only small, isolated populations remain, scattered across steep ledges where shrubs escape most grazing animals. We explored the genetic effects of habitat fragmentation on gene flow and genetic diversity in the largest remaining patches in the UK, which lie in Scotland, for two now restricted and rare montane willow species—Salix myrsinites and Salix lapponum. Using ten microsatellite loci and an almost complete genetic inventory in the central Cairngorms area (S. myrsinites n = 186, S. lapponum n = 91) we showed that genetic diversity (heterozygosity and allelic richness) is relatively high in both species, particularly high for the decaploid S. myrsinites, and clonal reproduction low. Historic gene flow between populations could be demonstrated. Significant inbreeding was detected in both species and observed seed set and numbers of juveniles in the field are low, possibly indicating signs of inbreeding depression. Both species have extremely low numbers of individuals at each site, with many being smaller than ten, and in some cases combined with skewed sex-ratios (mainly female biased). This will likely cause more severe reproductive failures in the next generations unless population numbers are increased. Reinforcing populations of both species under low grazing pressure with new, unrelated individuals, as well as creating new stepping-stone populations will be necessary to help the recovery of these species. Results from this study will inform restoration work in Scotland aiming to create continuous woodland habitats from pinewoods at lower altitudes through to higher altitude downy birch woodlands merging with montane willows.