Heterogeneous Vegetation Research Articles

Forest Breeze - Cold Pool Interactions Drive Convective Organization over Heterogeneous Vegetation

Abstract Heterogeneous landscapes can influence the development of convection through the generation of thermally-driven mesoscale circulations. To assess the impacts of these circulations and their interaction with sea breezes, we simulated convection in an idealized coastal environment using the Regional Atmospheric Modeling System (RAMS). We compared simulations with striped patterns of surface vegetation to those of uniform vegetation to identify the importance of vegetation heterogeneity in impacting convective development. Under dry soil conditions representative of those during the TRACER and ESCAPE campaigns in June 2022, we found that these vegetation-induced circulations, referred to in literature as “forest breezes,” are more important than the sea breeze in determining the location of convection initiation. Convection and precipitation are also found to be favored over forests and suppressed over pasture and suburban landscapes as a result of greater surface sensible heat flux over the forest. Our findings also indicate that forest breezes are important for initiating convection along the boundaries of the forest, but that cold pools may play a key role in propagating the forest breezes toward the center of the forest stripe. In our simulations, the collisions of these breezes in the center of the forest stripe leads to uplift and strong convection there; however, a different width of the forest stripe would alter when the forest breezes collide, or whether they collide at all. The presence of these cold pools may therefore impact the “ideal stripe width”, the width of each vegetation stripe which maximizes domain-wide precipitation.

Modeling carbon dynamics from a heterogeneous watershed in the mid-Atlantic USA: A distributed-calibration and independent verification (DCIV) approach

The terrestrial ecosystem plays a vital role in regulating regional and global carbon budgets. Ecosystem models are extensively employed to estimate carbon fluxes across different spatial scales. However, there remains a need to reduce the uncertainties associated with model parameterization and input data. To address these limitations, we assessed a distributed-calibration and independent-verification (DCIV) approach that uses (1) remotely sensed net primary production (NPP) and evapotranspiration (ET) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), (2) multi-site eddy covariance net ecosystem exchange (NEE) data; and (3) field sampling of soil organic carbon (SOC) and aboveground biomass (ABG) data to improve the overall predictability of carbon fluxes for the different land use and land cover (LULC) types at a watershed scale. The DCIV approach was applied to an advanced version of the Soil and Water Assessment Tool (SWAT)-Carbon (or SWAT-C), equipped with Century-based SOC algorithms to simulate carbon dynamics for watersheds with heterogeneous vegetation. The objective of the modeling effort was to assess carbon stocks and fluxes under different land management scenarios for a 3000-acre experimental farm and forest preserve in the northeastern United States. Our study showed that a large SOC stock of at least 100 tons ha−1 is stored under mixed forest, deciduous, shrubland, and floodplain (grass). Our study also showed that converting floodplain (grass) to deciduous forest has the potential to increase CO2 uptake (-NEE) by an order of three magnitude and ABG by 77 %, leading to an increased SOC stock of 23 % after twenty years. Similarly, we found that converting ungrazed grassland to grazed pasture leads to a non-statistically decreasing trend of SOC, especially in the 0–30 cm soil layer. Thus, the methodology used in this study can be applied to improve carbon dynamic prediction from a heterogeneous watershed at a regional scale.

Testing of UV fluorescence marking with daily recaptures of a low-mobile bush-cricket species

The primary goal of developing new mark–release–recapture (MRR) methods is to make MMR more cost-effective and able to provide more information. To test the effectiveness of UV fluorescence marking, a case study was carried out on an Isophya costata population occurring in a mown grassland with a heterogeneous vegetation pattern. The marked individuals were examined daily, from the emergence of imagos until the mowing of the habitat. The 40 marked insects (20 males and 20 females) were recaptured in 206 cases over 16 days (32.2% of the potential maximal recaptures). The finding of males was 26.2% successful, and the finding of females was 38.1% successful. Females released in shorter and sparse vegetation were recaptured more than those released in dense vegetation or than males. Recaptures showed a significant decrease during the study period in almost all groups based on Mann–Kendall trend tests. Detections were made on the upper third of the vertical structure of the vegetation in 88% of cases. In most of the detections (males: 70%, females: 62%), the axis of the insect’s body was more likely to be located vertically. The results showed that the chance of detection is significantly reduced when the position of the insect’s body is facing the axis of UV illumination. Thus, the visibility of individuals can be greatly increased by marking all sides of the body.

Reindeer carcasses modulate vegetation composition and greenness in High-Arctic tundra.

Vertebrate carrion is an integral part of foodwebs in ecosystems and can impact biodiversity at the local as well as the landscape scale. However, very little knowledge currently exists about the ecological role of carrion in the Arctic ecosystems. We conducted a ground survey on the cover of five plant functional groups at paired reindeer carcass and control sites and analysed the relationship between cover and carcass presence in the Arctic tundra of Svalbard. Vegetation indices from Red-Green-Blue (RGB) imagery captured by drones complemented this, assessing plant productivity in terms of ‘spectral greening’ and modelling the relationship between vegetation index values and carcass distance. We show that graminoids capitalised most from carcass presence, whereas bryophytes and lichen showed decreases in cover. Woody plant and forb covers were not significantly impacted by carcass presence. The Red Green Blue Vegetation Index decreased locally at fresh carcasses (i.e. <1 year old) but showed an increase at more established carcass sites (i.e. >1 year). We show that carcasses have differential impacts on the plant functional groups of Svalbard’s tundra and induce a local ‘green-up’ through secondary succession within 2 metres of the carcass. Given their non-random distribution, carcasses may contribute to vegetation heterogeneity at landscape scales. This is relevant for understanding how climate change-induced reindeer mortalities will impact tundra plant community composition in the future.

Hidden Archaeological Remains in Heterogeneous Vegetation: A Crop Marks Study in Fortified Settlements of Northwestern Iberian Peninsula

This study evaluates the effectiveness of multispectral imaging via Unmanned Aerial Systems (UAS), in combination with advanced digital image processing techniques, for the detection and mapping of archaeological sites within diverse landscapes. The research focuses on six case studies located in the northwest of the Iberian Peninsula, a region marked by complex vegetation patterns and varying topography. The primary objective is to assess the potential of these non-invasive remote sensing techniques in identifying crop marks associated with buried structures from ancient, fortified settlements. By means of Principal Component Analysis (PCA) and vegetation indices, the study aims to pinpoint areas of interest that may indicate the presence of archaeological features, while effectively distinguishing them from modern disturbances or natural terrain variations. The research encountered several challenges, including seasonal variations in crop conditions and recent land-use changes. The methodology successfully identified distinct archaeological features. In some instances, natural vegetation variability, typically seen as an obstacle, enhanced the visibility of crop marks, aiding in the detection of underlying structures. These results offer a cost-effective and scalable option for preliminary archaeological surveys, particularly in refining survey methodologies and guiding future excavation efforts aimed at uncovering and preserving ancient, fortified settlements in the region.

Different responses of spatial heterogeneity of grassland vegetation to grazing intensity in northern China

Different responses of spatial heterogeneity of grassland vegetation to grazing intensity in northern China

Extracting Vegetation Phenology in Heterogeneous Drylands Using LiDAR and Landsat Temporal Decomposition: A Latitudinal Assessment of Waterholes Within the Cooper Creek, Australia

AbstractLand surface phenology (LSP) is useful to understand patterns of terrestrial ecosystems. Detecting LSP in drylands is more challenging when compared to agricultural and mesic environments due to vegetation heterogeneity, the presence of evergreen and seasonal species, and the dominant role of water (which is often received episodically with variable timing) in determining vegetation growth. In this study, LiDAR‐derived vegetation classes are defined to guide and improve the interpretation of LSP metrics extracted using temporally decomposed Landsat fPAR time series. This method was applied to waterholes within the Cooper Creek floodplain, in dryland Australia, which are important for ecological conservation. Results showed that phenology is mostly associated with the recurrent vegetation (approximately 80% of all identified phenological events) in all waterholes. However, during high streamflow periods, the number of phenological events associated with the persistent vegetation greatly increased (up to 40% of the identified events). Non‐annual phenology was also identified, with more than one phenological event occurring across a water year during high streamflow periods. The duration of the phenological events of the persistent vegetation exceeded one water year during periods of high streamflow. Phenological differences of the LiDAR‐derived vegetation classes occupying the riparian zone of the waterholes were also identified. Streamflow movement across the floodplain exerts an important influence on the vegetation phenology, as suggested by a lag in the phenology when comparing southern and northern waterholes. The method developed herein can be applied to other highly spatially heterogeneous ecosystems where vegetation species simultaneously present permanent and seasonal patterns.

Tracking Small Animals in Complex Landscapes: AComparison of Localisation Workflows for Automated Radio Telemetry Systems.

Automated radio telemetry systems (ARTS) have the potential to revolutionise our understanding of animal movement by providing a near-continuous record of individual locations in the wild. However, localisation errors in ARTS data can be very high, especially in natural landscapes with complex vegetation structure and topography. This curtails the research questions that may be addressed with this technology. We set up an ARTS grid in a valley with heterogeneous vegetation cover in the Colombian high Andes and applied an analytical pipeline to test the effectiveness of localisation methods. We performed calibration trials to simulate animal movement in high- or low-flight, or walking on the ground, and compared workflows with varying decisions related to signal cleaning, selection, smoothing, and interpretation, along with four multilateration approaches. We also quantified the influence of spatial features on the system's accuracy. Results showed large variation in localisation error, ranging between 0.4-43.4 m and 474-1929 m, depending on the localisation method used. We found that the selection of higher radio signal strengths and data smoothing based on the temporal autocorrelation are useful tools to improve accuracy. Moreover, terrain ruggedness, height of movement, vegetation type, and the location of animals inside or outside the grid area influence localisation error. In the case of our study system, thousands of location points were successfully estimated for two high-altitude hummingbird species that previously lacked movement data. Our case study on hummingbirds suggests ARTS grids can be used to estimate small animals' home ranges, associations with vegetation types, and seasonality in occurrence. We present a comparative localisation pipeline, highlighting the variety of possible decisions while processing radio signal data. Overall, this study provides guidance to improve the resolution of location estimates, broadening the application of this tracking technology in the study of the spatial ecology of wild populations.

Hyperspectral imaging for chloroplast movement detection.

We employed hyperspectral imaging to detect chloroplast positioning and assess its influence on common vegetation indices. In low blue light, chloroplasts move to cell walls perpendicular to the direction of the incident light. In high blue light, chloroplasts exhibit the avoidance response, moving to cell walls parallel to the light direction. Irradiation with high light results in significant changes in leaf reflectance and the shape of the reflectance spectrum. Using mutants with disrupted chloroplast movements, we found that blue-light-induced changes in the reflectance spectrum are mostly due to chloroplast relocations. We trained machine learning methods in the classification of leaves according to the chloroplast positioning, based on the reflectance spectra. The convolutional network showed low levels of misclassification of leaves irradiated with high light even when different species were used for training and testing, suggesting that reflectance spectra may be used to detect chloroplast avoidance in heterogeneous vegetation. We also examined the correlation between chloroplast positioning and values of indices of normalized-difference type for various combinations of wavelengths and identified an index sensitive to chloroplast positioning. We found that values of some of the vegetation indices, including those sensitive to the carotenoid levels, may be altered due to chloroplast rearrangements.

Analysis of the Influence of Driving Factors on Vegetation Changes Based on the Optimal-Parameter-Based Geographical Detector Model in the Yima Mining Area

The growth of vegetation directly maintains the ecological security of coal mining areas. It is of great significance to monitor the dynamic changes in vegetation in mining areas and study the driving factors of vegetation spatial division. This study focuses on the Yima mining area in Henan Province. Utilizing MODIS and multi-dimensional explanatory variable data, the Theil–Sen Median + Mann–Kendall trend analysis, variation index, Hurst index, and optimal-parameter-based geographical detector model (OPGD) are employed to analyze the spatiotemporal changes and future trends in the EVI (enhanced vegetation index) from 2000 to 2020. This study further investigates the underlying factors that contribute to the spatial variation in vegetation. The results indicate the following: (1) During the period studied, the Yima mining area was primarily characterized by a moderate-to-low vegetation cover. The area exhibited significant spatial variation, with a notable pattern of “western improvement and eastern degradation”. This pattern indicated that the areas that experienced improvement greatly outnumbered the areas that underwent degradation. Moreover, there was an inclination towards a deterioration in vegetation in the future. (2) Based on the optimal parameter geographic detector, it was found that 2 km was the optimal spatial scale for the analysis of the driving factors of vegetation change in this area. The optimal parameter combination was determined by employing five spatial data discretization methods and selecting an interval classification range of 5–10. This approach effectively addresses the subjective bias in spatial scales and data discretization, leading to enhanced accuracy in vegetation change analysis and the identification of its driving factors. (3) The spatial heterogeneity of vegetation is influenced by various factors, such as topography, socio-economic conditions, climate, etc. Among these factors, population density and mean annual temperature were the primary driving forces in the study area, with Q > 0.29 and elevation being the strongest explanatory factor (Q = 0.326). The interaction between temperature and night light was the most powerful explanation (Q = 0.541), and the average Q value of the interaction between the average annual temperature and other driving factors was 0.478, which was the strongest cofactor among the interactions. The interactions between any two factors enhanced their impact on the vegetation’s spatial changes, and each driving factor had its suitable range for affecting vegetative growth within this region. This research provides scientific support for conserving vegetation and restoring the ecological system.

The ephemeral microbiota: Ecological context and environmental variability drive the body surface microbiota composition of Magellanic penguins across subantarctic breeding colonies.

Environmental microbes routinely colonize wildlife body surface microbiota. However, animals experience dynamic environmental shifts throughout their daily routine. Yet, the effect of ecological shifts in wildlife body surface microbiota has been poorly explored. Here, we sequenced the hypervariable region V3-V4 of the 16S rRNA gene to characterize the body surface microbiota of wild Magellanic penguins (Spheniscus magellanicus) under two ecological contexts: (1) Penguins walking along the coast and (2) Penguins sheltered underground in their nest, across three subantarctic breeding colonies in the Magellan Strait, Chile. Despite ecological contexts, our results revealed that Moraxellaceae bacteria were the most predominant and abundant taxa associated with penguin body surfaces. Nevertheless, we detected colony-specific core bacteria associated with penguin bodies. The most abundant were: Deinococcus in the Contramaestre colony, Fusobacterium in the Tuckers 1 colony, and Clostridium sensu stricto 1 in the Tuckers 2 colony. Our results give a new perspective on the niche environmental hypothesis for wild seabirds. First, the ecological characteristics of each colony were associated with the microbial communities from the nest soil and the body surface of penguins inside the nests. For example, in the colonies with heterogenous vegetation cover (i.e. the Tuckers Islets), there was a similar microbial composition between the nest soil and the body surface of penguins. In contrast, on the more arid colony (Contramaestre), we detected differences in the microbial communities between the nest soil and the body surface of penguins.

Spatial Monte Carlo Simulation and Analysis of Climate Change Enhanced Fire and Projected Landscape-Scale Variation in Vegetation Heterogeneity

Spatial Monte Carlo Simulation and Analysis of Climate Change Enhanced Fire and Projected Landscape-Scale Variation in Vegetation Heterogeneity

Hyperspectral Leaf Area Index and Chlorophyll Retrieval over Forest and Row-Structured Vineyard Canopies

As an unprecedented stream of decametric hyperspectral observations becomes available from recent and upcoming spaceborne missions, effective algorithms are required to retrieve vegetation biophysical and biochemical variables such as leaf area index (LAI) and canopy chlorophyll content (CCC). In the context of missions such as the Environmental Mapping and Analysis Program (EnMAP), Precursore Iperspettrale della Missione Applicativa (PRISMA), Copernicus Hyperspectral Imaging Mission for the Environment (CHIME), and Surface Biology Geology (SBG), several retrieval algorithms have been developed based upon the turbid medium Scattering by Arbitrarily Inclined Leaves (SAIL) radiative transfer model. Whilst well suited to cereal crops, SAIL is known to perform comparatively poorly over more heterogeneous canopies (including forests and row-structured crops). In this paper, we investigate the application of hybrid radiative transfer models, including a modified version of SAIL (rowSAIL) and the Invertible Forest Reflectance Model (INFORM), to such canopies. Unlike SAIL, which assumes a horizontally homogeneous canopy, such models partition the canopy into geometric objects, which are themselves treated as turbid media. By enabling crown transmittance, foliage clumping, and shadowing to be represented, they provide a more realistic representation of heterogeneous vegetation. Using airborne hyperspectral data to simulate EnMAP observations over vineyard and deciduous broadleaf forest sites, we demonstrate that SAIL-based algorithms provide moderate retrieval accuracy for LAI (RMSD = 0.92–2.15, NRMSD = 40–67%, bias = −0.64–0.96) and CCC (RMSD = 0.27–1.27 g m−2, NRMSD = 64–84%, bias = −0.17–0.89 g m−2). The use of hybrid radiative transfer models (rowSAIL and INFORM) reduces bias in LAI (RMSD = 0.88–1.64, NRMSD = 27–64%, bias = −0.78–−0.13) and CCC (RMSD = 0.30–0.87 g m−2, NRMSD = 52–73%, bias = 0.03–0.42 g m−2) retrievals. Based on our results, at the canopy level, we recommend that hybrid radiative transfer models such as rowSAIL and INFORM are further adopted for hyperspectral biophysical and biochemical variable retrieval over heterogeneous vegetation.

Response of beetle communities to the heterogeneity of vegetation in high altitude habitats in north-western Argentina

Response of beetle communities to the heterogeneity of vegetation in high altitude habitats in north-western Argentina

Impacts of Wildlife Artificial Water Provisioning in an African Savannah Ecosystem: A Spatiotemporal Analysis

The use of artificial water points for wildlife in African savannah ecosystems has been widely criticised for affecting the distribution of wildlife and initiating changes in the heterogeneity of natural landscapes. We examined the spatiotemporal variations in the landscape before and after the installation of an artificial water point by integrating the analysis of vegetation and soil spectral response patterns with a supervised learning random forest model between 2002 and 2022 in Chobe Enclave, Northern Botswana. Our results revealed that the study area is characterised by animal species such as Equus quagga, Aepyceros melampus, and Loxodonta africana. The findings also showed that the main vegetation species in the study area landscape include Combretum elaeagnoides, Vachellia luederitzii, and Combretum hereroense. The artificial water point induced disturbances on a drought-vulnerable landscape which affected vegetation heterogeneity by degrading the historically dominant vegetation cover types such as Colophospermum mopane, Dichrostachys cinerea, and Cynodon dactylon. The immediate years following the artificial water point installation demonstrated the highest spectral response patterns by vegetation and soil features attributed to intense landscape disturbances due to abrupt high-density aggregation of wildlife around the water point. Landscapes were strongly homogenised in later years (2022), as shown by overly overlapping spectral patterns owing to an increase in dead plant-based material and senescent foliage due to vegetation toppling and trampling. The landscape disturbances disproportionately affected mopane-dominated woodlands compared to other vegetation species as indicated by statistically significant land cover change obtained from a random forest classification. The woodlands declined significantly (p < 0.05) within 0–0.5 km, 0.5–1 km, 1–5 km, and 5–10 km distances after the installation of the water point. The results of this study indicate that continuous nonstrategic and uninformed use of artificial water points for wildlife will trigger ecological alterations in savannah ecosystems.

Birds of Berlin: Changes in communities and guilds in the urban park "Tiergarten" since 1850.

Urbanization has far-reaching consequences on birds, and knowledge of the impacts on taxonomic and functional diversity is necessary to make cities as compatible as possible for species. Avian diversity in parks in urban centers has been investigated multiple times, but rarely so in long-term studies due to lacking data. The Tiergarten in Berlin is a large-scale park in the city center of great value for people and many species including birds. We compiled bird species lists since 1850 and from monitoring in 2022 in one dataset to investigate how bird communities and guilds have changed over time and how these alterations were influenced by the eventful history of the park's vegetation conditions. Long-term changes in species assemblages were analyzed with an ordination analysis, and changes in guild presence and functional richness were discussed with regard to landscape transitions. A gradual development of species assemblages yet only small changes in guild composition since 1850 was detected, whereas the 1950 community stands out with a drop in species richness and replacement of forest species with an open land community, which reflects the deforestation of the park during World War II. Consideration of habitat, lifestyle, trophic, and migration guilds revealed no sign of functional homogenization over the last 172 years (1850-2022). Despite the high frequentation of the park by humans it still allows for a high bird diversity due to the Tiergarten's sheer size and heterogeneity of vegetation and habitats. We recommend that the park is maintained and managed accordingly to preserve this condition and advise other urban parks to strive for these beneficial features.

Leaf carbon chemistry effectively manipulated soil microbial profiles and induced metabolic adjustments under different revegetation types in the loess Plateau, China

Microorganisms are essential components of underground life systems and drive elemental cycling between plants and soil. Yet, in the ecologically fragile Loess Plateau, scant attention has been paid to the response of microbial communities to organic carbon (C) chemistry of both leaves and soils under different revegetation conditions, as well as subsequent alternation in their C metabolic functions. Here, Fourier transform infrared (FTIR) spectrum, amplicon sequencing of 16S rRNA and ITS, and temporal incubation with Biolog-Eco 96 plates were combined to explore the vegetative heterogeneity of microbial community properties and metabolic functions, as well as their regulatory mechanisms in three typical revegetation types including Robinia pseudoacacia L. (RF), Caragana korshinskii KOM. (SL), and abandoned grassland (AG). We observed higher bacterial-to-fungal ratios (B: F = 270.18) and richer copiotrophic bacteria (Proteobacteria = 33.08%) in RF soil than those in AG soil, suggesting that microbes were dominated by r-strategists in soil under RF treatment, which is mainly related to long-term priming of highly bioavailable leaf C (higher proportion of aromatic and hydrophilic functional groups and lower hydrophobicity). Conversely, microbial taxa in AG soil, which was characterized by higher leaf organic C hydrophobicity (1.39), were dominated by relatively more abundant fungi (lower B: F ratio = 149.49) and oligotrophic bacteria (Actinobacteria = 29.30%). The co-occurrence network analysis showed that microbial interactive associations in RF and AG soil were more complex and connective than in SL soil. Furthermore, Biolog-Eco plate experiments revealed that microorganisms tended to utilize labile C compounds (carbohydrates and amino acids) in RF soil and resistant C compounds (polymers) in AG soil, which were consistent with the substrate adaptation strategies of predominant microbial trophic groups in different revegetation environments. Meanwhile, we observed greater microbial metabolic activity and diversity advantages in RF vegetation. Collectively, we suggest that besides the nutrient variables in the leaf-soil system, the long-term regulation of the microbial community by the C chemistry of the leaf sequentially alters the microbial metabolic profiles in a domino-like manner. RF afforestation is more conducive to restoring soil microbial fertility (including microbial abundance, diversity, interactive association, and metabolic capacity). Our study potentially paves the way for achieving well-managed soil health and accurate prediction of C pool dynamics in areas undergoing ecological restoration of the Loess Plateau.

Modern vegetation-climate relationships for pollen assemblages across the mountainous regions of southwestern China: Implications for palaeoenvironmental reconstruction

A comprehensive understanding of modern pollen transport processes is a prerequisite for utilizing fossil pollen to elucidate the evolution of palaeoclimates and palaeoenvironments, especially in areas such as southwestern China where complex mountainous topography results in vegetation heterogeneity. In this paper, we selected four vertical profiles in mountainous regions of southwestern China, each with distinct plant communities, to investigate the relationship between modern pollen rain, vegetation types and vegetation cover, and to quantify the influence of environmental factors. Results show that pollen assemblages are generally representative of regional plant communities, although long-distant transport of arboreal pollen by valley winds can introduce signals from a much wider area. The calibrated arboreal pollen percentage (AP) and ratio of arboreal pollen to non-arboreal pollen (AP/NAP) serves as reliable quantitative proxies for vegetation cover, highlighting the importance of appropriate calibration when interpreting fossil pollen assemblages. Climate is the primary determinant of pollen distribution across these mountains, with mean temperature of the coldest month (MTCM) playing the most prominent contribution. Additionally, the impact of vegetation cover and soil nutrients on pollen distribution are also significant. Our modern study improves the accuracy of pollen interpretation for palaeoenvironmental reconstruction in mountainous regions of southwestern China.

Remotely-sensed phenoclusters of Wisconsin’s forests, shrublands, and grasslands for biodiversity applications

Heterogeneous vegetation supports higher species richness than homogenous vegetation, which is why efficiently identifying heterogenous vegetation can be useful for biodiversity conservation. Satellite remote-sensing data provide an opportunity to generate vegetation heterogeneity metrics and to explore the phenology of vegetation patterns. Phenoclusters are vegetation types with similar phenological characteristics, and valuable for capturing vegetation habitat heterogeneity patterns. Our goal was to map phenoclusters for Wisconsin, USA, at 10-m spatial resolution based on land surface phenology metrics from EVI (Enhanced Vegetation Index) Sentinel-2 data. We characterized each phenocluster based on landcover composition and structure, phenology timing, and environmental factors, and compared them to bird species richness. We also calculated the diversity of phenoclusters at multiple spatial extents. We identified 14 phenoclusters in Wisconsin, each with distinct landcover composition and structure, and unique phenological characteristics. Our remotely-sensed phenoclusters effectively captured environmental gradients, with elevation and temperature emerging as the most important driving variables. Furthermore, the phenoclusters successfully captured bird biodiversity patterns, especially richness of forest and grassland specialist. Our results identified phenological patterns among Wisconsin’s forests, shrublands, and grasslands, capturing phenological timing both among and within the same tree species. Phenoclusters are a valuable tool for capturing vegetation habitat heterogeneity, phenology diversity and biodiversity patterns, as well as climate change effects.

Cross-scale analysis reveals interacting predictors of annual and perennial cover in Northern Great Basin rangelands.

Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity. We analyzed regional-scale and local-scale patterns of annual grass, perennial grass, and shrub cover, and examined to what extent plot-level variation was contingent on pasture-level predictions of site favorability. Annual grasses were widespread at burned and unburned sites alike, contrary to assumptions of annual grasses depending on fire, and more common at lower elevations and higher temperatures regionally, as well as on warmer slopes locally. Pasture-level grazing pressure interacted with temperature such that annual grass cover was associated positively with grazing pressure at higher temperatures but associated negatively with grazing pressure at lower temperatures. This suggests that pasture-level temperature and grazing relationships with annual grass abundance are complex and context dependent, although the causality of this relationship deserves further examination. At the plot-level within pastures, annual grass cover did not vary with grazing metrics, but perennial cover did; perennial grasses, for example, had lower cover closer to water sources, but higher cover at higher dung counts within a pasture, suggesting contrasting interpretations of these two grazing proxies. Importantly for predictions of ecosystem response to temperature change, we found that pasture-level and plot-level favorability interacted: perennial grasses had a higher plot-level cover on cooler slopes, and this difference across topography was starkest in pastures that were less favorable for perennial grasses regionally. Understanding the mechanisms behind cross-scale interactions and contingent responses of vegetation to grazing in these increasingly invaded ecosystems will be critical to land management in a changing world.