Savanna Sites Research Articles

Severe fire regimes decrease resilience of ectothermic populations

Abstract Understanding populations' responses to environmental change is crucial for mitigating human‐induced disturbances. Here, we test hypotheses regarding how three essential components of demographic resilience (resistance, compensation and recovery) co‐vary along the distinct life histories of three lizard species exposed to variable, prescribed fire regimes. Using a Bayesian hierarchical framework, we estimate vital rates (survival, growth and reproduction) with 14 years of monthly individual‐level data and mark‐recapture models to parameterize stochastic integral projection models from five sites in Brazilian savannas, each historically subjected to different fire regimes. With these models, we investigate how weather, microclimate and ecophysiological traits of each species influence their vital rates, emergent life history traits and demographic resilience components in varying fire regimes. Overall, weather and microclimate are better predictors of the species' vital rates, rather than their ecophysiological traits. Our findings reveal that severe fire regimes increase populations' resistance but decrease compensation or recovery abilities. Instead, populations have higher compensatory and recovery abilities at intermediate degrees of fire severity. Additionally, we identify generation time and reproductive output as predictors of resilience trends across fire regimes and climate. Our analyses demonstrate that the probability and quantity of monthly reproduction are the proximal drivers of demographic resilience across the three species. Our findings suggest that populations surpass a tipping point in severe fire regimes and achieve an alternative stable state to persist. Thus, higher heterogeneity in fire regimes can increase the reproductive aspects and resilience of different populations and avoid high‐severity regimes that homogenize the environment. Despite being more resistant, species with long generation times and low reproductive output take longer to recover and cannot compensate as much as species with faster paces of life. We emphasize how reproductive constraints, such as viviparity and fixed clutch sizes, impact the ability of ectothermic populations to benefit and recover from disturbances, underscoring their relevance in conservation assessments.

Beyond fire: Flower production naturally occurs and is also influenced by leaf removal in a Neotropical savanna herb.

Several herbaceous species exhibit mass flowering after fires in Neotropical savannas. However, unequivocal evidence of fire dependency and the consequences for plant reproduction are lacking. In nutrient-poor fire-prone savannas, the damage caused by fire and by other means (e.g., leaf removal, but not necessarily having a negative impact) constrains the maintenance and expansion of plant population by affecting the ability of individuals to recover. Therefore, the compensatory responses of plants to both damages should be convergent in such environments. Using Bulbostylis paradoxa-reported to be fire-dependent to flower-as a model, we investigated the role of fire and leaf removal in anticipating the flowering and reproduction periods, and its possible consequences on seedling establishment. We monitored 70 burned individuals, 70 damaged/clipped, and 35 without damage to estimate time for flowering, seed quality and germination parameters. To expand our sampling coverage, we examined high-resolution images from herbarium collections in the SpeciesLink database. For each herbarium image, we recorded the presence or absence of a fire scar, the month of flowering, and the number of flowering stalks. Bulbostylis paradoxa was fire-stimulated but not dependent on fire to flower, with 65.7% of the individuals flowering in the burned area, 48.6% in the clipped, and 11.4% in the control. This was consistent with the analysis of the herbarium images in which 85.7% of the specimens with flowers had fire scars and 14.3% did not. Burned individuals synchronized flowering and produced more viable seeds. However, the seeds might face a period of unsuitable ecological conditions after early to mid-dry season fires. Flowering of unburned plants was synchronized with the onset of the rainy season. Flexibility in flowering and vegetative reproduction by fragmentation confer to this species, and most likely other plants from the herbaceous layer, the capability of site occupation and population persistence in burned and unburned savanna sites.

Influence of soil properties on woody vegetation structure, diversity and seasonality in Neotropical savannas

AbstractUnderstanding how savanna soil properties influence vegetation diversity and function is a major challenge in ecological studies. We investigated the effects of soil properties on woody species density, richness, composition, and vegetative phenology (inferred by the Normalized Difference Vegetation Index (NDVI)) in two alluvial and two interfluvial savanna sites (1 block of 10 plots of 20 × 50 m in each site), in the Brazilian Cerrado. We showed that plots in alluvial savannas present less fertile soils and have lower plant densities and species richness and higher seasonality of NDVI than plots in the interfluvial savannas. The species composition of the sites was associated with the P, Fe, K, and Mn content of the soil. Soil K, Fe, and Ca contents were the main variables associated with plant density in a linear mixed model (LMM) that explained 79% of data variability (r2c = 0.79%), and K, Fe, and Al were the main predictors to explain species richness (r2c = 0.81%). Soil K, pH, and Silt were the best predictors of the seasonality in NDVI (r2c = 0.14%). We highlight the all‐encompassing effect of K soil content on species density, richness, composition, and NDVI and argue that this macronutrient and a few other soil properties (e.g., P, Fe, Al, and Silt) are the main factors mediating plant responses to water and nutrient stress in woody savanna communities occurring in the Cerrado–Amazônia transition.

Alternating Conditional Expectations: Introducing a Non‐Parametric Statistical Method to Interpret Long‐Term Greenhouse Gas Flux Measurements Over Semi‐Arid and Wetland Ecosystems

AbstractWe explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO2) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO2 and methane (CH4) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide.

Using phenology to unravel differential soil water use and productivity in a semiarid savanna

AbstractSavannas are water‐limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna‐wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, <0–30 cm and deep, >30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components.

Drivers of wood decay in tropical ecosystems: Termites versus microbes along spatial, temporal and experimental precipitation gradients

Abstract Models estimating decomposition rates of dead wood across space and time are mainly based on studies carried out in temperate zones where microbes are dominant drivers of decomposition. However, most dead wood biomass is found in tropical ecosystems, where termites are also important wood consumers. Given the dependence of microbial decomposition on moisture with termite decomposition thought to be more resilient to dry conditions, the relative importance of these decomposition agents is expected to shift along gradients in precipitation that affect wood moisture. Here, we investigated the relative roles of microbes and termites in wood decomposition across precipitation gradients in space, time and with a simulated drought experiment in tropical Australia. We deployed mesh bags with non‐native pine wood blocks, allowing termite access to half the bags. Bags were collected every 6 months (end of wet and dry seasons) over a 4‐year period across five sites along a rainfall gradient (ranging from savanna to wet sclerophyll to rainforest) and within a simulated drought experiment at the wettest site. We expected microbial decomposition to proceed faster in wet conditions with greater relative influence of termites in dry conditions. Consistent with expectations, microbial‐mediated wood decomposition was slowest in dry savanna sites, dry seasons and simulated drought conditions. Wood blocks discovered by termites decomposed 16–36% faster than blocks undiscovered by termites regardless of precipitation levels. Concurrently, termites were 10 times more likely to discover wood in dry savanna compared with wet rainforest sites, compensating for slow microbial decomposition in savannas. For wood discovered by termites, seasonality and drought did not significantly affect decomposition rates. Taken together, we found that spatial and seasonal variation in precipitation is important in shaping wood decomposition rates as driven by termites and microbes, although these different gradients do not equally impact decomposition agents. As we better understand how climate change will affect precipitation regimes across the tropics, our results can improve predictions of how wood decomposition agents will shift with potential for altering carbon fluxes. Read the free Plain Language Summary for this article on the Journal blog.

Mapping Cerrado remnants in an anthropized landscape in southeast Brazil

In the eastern São Paulo state, Brazil, a disjoint tropical savanna (Cerrado) site occurs in Vale do Paraíba Paulista. Considering the degradation of Cerrado in the region and that currently LULC mapping is not accurate enough to properly map Cerrado vegetation in an anthropized landscape, we aimed to locate Cerrado remnants in the region and to evaluate the conservation status of these remnants and its main anthropic pressures. We hypothesized that Cerrado pacthes in Vale do Paraíba Paulista were small, irregular in shape, disconnected from each other, and threatened by agriculture and urban expansion, which we found. We also expected that woody formations of Cerrado would predominate in the region, what we observed. Different Cerrado formations covered an area of 3153.35 ha in Vale do Paraíba Paulista, only about 1.5% of original extension, and remnants located within private properties. This study highlighted Cerrado occurrence in Vale do Paraíba Paulista and the need for conservation public policies for this biome in the region.

Interannual variability of spring and summer monsoon growing season carbon exchange at a semiarid savanna over nearly two decades

Eddy covariance measurements of land-atmosphere energy, carbon, and water exchange now span multiple decades at some sites, supporting an improved understanding of flux interannual variability (IAV) and its ecophysiological and physical controls. Most eddy covariance IAV studies have focused on temperate forest ecosystems, where carbon fluxes are large and flux records are longest – but also where IAV is much lower than in dryland regions, which have been identified as an essential driver of the trend and variability in the global terrestrial carbon sink. In this study, we leveraged 19 years of continuous micrometeorological measurements at the AmeriFlux US-SRM mesquite savanna site in southern Arizona, USA to quantify the IAV, trends, and drivers of carbon fluxes during the distinct spring and summer growing seasons. We also assessed the ability of modern satellite and land surface models to capture the IAV of seasonal water and carbon fluxes. Annual net ecosystem production (NEP) was small and highly variable (23 +/- 64 gC m − 2 yr−1). Precipitation and associated measures of water availability determined most of the variability in NEP, largely through their influence on annual and seasonal gross ecosystem productivity (GEP) as opposed to ecosystem respiration (ER). Root-zone soil moisture captured between 73% (spring) and 85% (summer) of GEP variability and between 73% (spring) and 58% (summer) of ER variability. Throughout the study period, soil moisture and greenness increased with associated increases in GEP, ER and NEP. These trends were strongly influenced by very productive and wet summer growing seasons during the last two years, which were characterized by abundant understory grass cover. Typically, less than half of the variability in growing season GEP and evapotranspiration was captured by satellite-based estimates and land surface model simulations with local site forcing and calibration, highlighting the ongoing utility of long-term datasets to support careful model testing and improvement.

Changes in arbuscular mycorrhizal fungal communities, mycorrhizal soil infectivity, and phosphorus availability under Chromolaena odorata (Asteraceae) invasions in a West-African forest-savanna ecotone.

Substantial areas of agricultural lands in Sub-Saharan Africa have been invaded by Chromolaena odorata (Asteraceae), but the consequences for arbuscular mycorrhiza fungi (AMF) remains poorly understood. This study explores changes in diverse AMF community attributes and soil available phosphorus following C. odorata invasion in forest and savanna fragments in Côte d'Ivoire (West Africa). Invaded-forest (COF) and savanna (COS) sites were compared to adjacent natural forest (FOR) and savanna (SAV) fragments, respectively. Physico-chemical variables and AMF spore density parameters were determined for soil samples from 0-20cm depth. An 18S ribosomal RNA metabarcoding analysis of AMF communities was conducted. In addition, cowpea (Vigna unguiculata)was grown on soils collected from these sites under greenhouse conditions for determination of soil mycorrhizal infectivity. Noticeable changes in the composition of AMF communities in C. odorata relative to nearby forest and savanna non-invaded sites were observed. AMF-specific richness in COS (47 species) was lower than that in SAV (57 species) while it was higher in COF (68 species) than in FOR (63 species). COF and COS differed in AMF specific composition (Dissimilarity index = 50.6%). Chromolaena odorata invasions resulted in increased relative abundances of the genera Claroideoglomus and Glomus in COF, a decreased relative abundance of Paraglomus in COS and decreased relative abundances of Ambispora in both COF and COS. Total and healthy spore densities, cowpea root colonization intensity and soil available P were all higher in invaded sites than in natural ecosystems. Remarkably, although these values were different in FOR and SAV, they turned out to be similar in COF and COS (4.6 and 4.2 total spores g-1 soil, 2.3 and 2.0 healthy spores g-1 soil, and 52.6 and 51.6% root colonization, respectively) suggesting a C. odorata-specific effect. These findings indicate that soil mycorrhizal potential and phosphorus availability have improved following C. odorata invasion.

The impacts of Cape porcupines on woody plant mortality

AbstractIn terrestrial ecosystems, the activities of semi‐fossorial animals such as Cape porcupines have important landscape effects that may manifest in the dry season when the availability of above‐ground forage becomes limiting. We investigated the effects of foraging activities of Cape porcupines on savanna landscapes. We measured the size (surface area and depth) of foraging holes of porcupines located at the base of trees in the dry season in two mesic savanna sites at Roodeplaat Farm and Bisley Valley Nature Reserve in South Africa. We also recorded plant and animal activities inside the foraging holes for 3 months. The depth of foraging holes beneath small trees (Vachellia nilotica) was greater than depths beneath old trees (V. robusta and D. rotundifolia). This resulted in the subsequent death of most (>50%) small impacted trees in the dry season at Bisley. The surface area of foraging holes for older trees was greater than that for small trees and even greater for old holes. This study showed that porcupines kill trees or expose them to secondary attacks. The physical impacts of semi‐fossorial herbivores in savannas can be significant, with contributions to direct and indirect landscape transformation and restoration.

Towards a General Monitoring System for Terrestrial Primary Production: A Test Spanning the European Drought of 2018

(1) Land surface models require inputs of temperature and moisture variables to generate predictions of gross primary production (GPP). Differences between leaf and air temperature vary temporally and spatially and may be especially pronounced under conditions of low soil moisture availability. The Sentinel-3 satellite mission offers estimates of the land surface temperature (LST), which for vegetated pixels can be adopted as the canopy temperature. Could remotely sensed estimates of LST offer a parsimonious input to models by combining information on leaf temperature and hydration? (2) Using a light use efficiency model that requires only a handful of input variables, we generated GPP simulations for comparison with eddy-covariance inferred estimates available from flux sites within the Integrated Carbon Observation System. Remotely sensed LST and greenness data were input from Sentinel-3. Gridded air temperature data were obtained from the European Centre for Medium-Range Weather Forecasts. We chose the years 2018–2019 to exploit the natural experiment of a pronounced European drought. (3) Simulated GPP showed good agreement with flux-derived estimates. During dry conditions, simulations forced with LST performed better than those with air temperature for shrubland, grassland and savanna sites. (4) This study advances the prospect for a global GPP monitoring system that will rely primarily on remotely sensed inputs.

Fire Impacts and Dynamics of Seasonally Dry Tropical Forest of East Java, Indonesia

(1) Background: Seasonally dry tropical forests (SDTFs) are globally important ecosystems which receive less research attention compared to tropical rainforests but are equally under serious threat. The objectives of this paper are to characterize the vegetation structure, diversity and composition of SDTF of Baluran National Park, East Java, Indonesia, and to assess the impact of burning this SDTF and its post-fire recovery. (2) Methods: In the field, we measured floristic composition and dominance at sites with different fire histories in both SDTF and adjacent savannas of Baluran. Remote sensing image analysis was also employed using the MODIS burn area product and various thematic maps. (3) Results: SDTF at Baluran has moderately high tree cover, is less diverse in species than rainforest, and has a prominent vegetative response to fire, especially in the tree layer. The immediate post-fire period in SDTF featured lower densities of tree seedlings and saplings, more grasses and herbs, and lower species richness than older unburned forest. Species composition varied with fire age and vegetation type, with relatively rapid recovery with time since fire evident, although there was some convergence of long-unburned savanna and SDTF sites in terms of floristics. (4) Conclusions: The SDTF of Baluran recovers after fire principally via resprouting but also via seedling regeneration, with structural attributes returning more quickly (<10 years) than floristic composition (>10 years). We did not find consistent evidence of ecosystem transitions between SDTF and savanna despite a small number of long-unburned savanna sites having floristic similarities to dry forest (particularly in terms of characteristic tree species), and we identify the need for more study to determine the degree and mechanisms of forest–savanna transitions in the region, with a future research agenda outlined. Relatively large areas of savanna–dry forest transitions demonstrated from remote sensing analyses were primarily attributed to spread of Acacia nilotica (an alien invasive small tree or shrub) into long-unburned savanna, and its decline in areas where the species is being successfully controlled via burning and cutting. Knowledge of such ecological shifting is important for the ecosystem management, especially in terms of their usage by large mammals.

Landscape structure shapes the diversity of plant reproductive traits in agricultural landscapes in the Brazilian Cerrado

The replacement of native vegetation by crops and pasturelands compromises the functional diversity of plants and negatively influence ecosystem functions such as pollination and seed dispersal. Here, we investigate the effects of landscape structure on the diversity of functional traits in agricultural landscapes in the Brazilian Cerrado. We sampled the woody plant community in 49 sites in forests and savannas, and analyzed the density and richness of pollination and seed dispersal syndromes. We performed model selection using Akaike Information Criterion to test whether landscape variables such as habitat amount, percentage of agriculture and pasture, patch and edge densities, and compositional heterogeneity at different spatial scales influence the density and richness of woody plant functional traits related to seed dispersal and pollination syndromes. The amount of forest and patch density were the landscape predictors that explained most of the diversity of plant functional traits. The amount of agricultural and savanna as well as edge density and landscape heterogeneity also affected functional traits. Our results suggest that habitat amount and configuration in the landscapes drive the diversity of functional traits, pointing that maintaining habitats within Cerrado agricultural landscapes is determinant for the plant’s functional traits diversity. Furthermore, a heterogeneous mosaic may favor the density or richness of plants pollinated by insects and hummingbirds. The continuous loss and fragmentation of habitats may lead to loss of ecological functions compromising the provision of ecosystems services in agricultural landscapes in the Cerrado ecoregion.

Soil carbon storage potential of acid soils of Colombia's Eastern High Plains

Improving soil organic carbon (SOC) storage enhances soil quality and mitigates climate change. Agricultural and livestock specialists increasingly view tropical grasslands as a potential target for storing more soil carbon while boosting productivity. Earlier research in the 1990s showed the promise of improving SOC storage in the Eastern High Plains of Colombia. But these studies were limited to two experimental stations, without focusing on conditions on farms or under variable management. This research examined whether those early studies did indeed reflect possibilities for improving SOC storage and livestock productivity. We measured SOC stocks at one of the experiment stations from previous research and on farms throughout the study area in Colombia's Eastern High Plains. Complementarily our team sampled other predominant land uses to map SOC storage across the nearly 1 million ha study area. Using that information, we also constructed scenarios suggesting changes in SOC and productivity based on land-use changes. The high SOC accumulation found at experimental sites in the 1990s declined 24 years later. However, SOC storage was over 27 Mg ha−1 yr−1 higher than reference native savanna sites, with an accumulation rate of 0.96 Mg ha−1 yr−1. On farms under variable management, improved pastures stored 10 Mg ha−1 more SOC than degraded pastures or native savanna. For the whole region, we estimate that carbon storage observed across soils and land use of the 1 million ha study area could store 0.08 Gt of carbon down to 1 m depth, with wide variation across the region. While the SOC measured in grasslands in the early 1990s did not persist under inadequate management over the period of two decades, the potential to accumulate SOC of Colombia's Eastern High Plains through appropriate management is high, pointing to a sustainable livestock strategy that boosts productivity and reduces emissions.

One year of spectroscopic high‐frequency measurements of atmospheric CO2, CH4, H2O and δ13C‐CO2 at an Australian Savanna site

AbstractWe provide a 1‐year dataset of atmospheric surface CO2, CH4 and H2O concentrations and δ13C‐CO2 values from an Australian savanna site. These semi‐arid ecosystems act as carbon sinks in wet years but the persistence of the sink in dry years is uncertain. The dataset can be used to constrain uncertainties in modelling of greenhouse gas budgets, improve algorithms for satellite measurements and characterize the role of vegetation and soil in modulating atmospheric CO2 concentrations. We found pronounced seasonal variations in daily mean CO2 concentrations with an increase (by 5–7 ppmv) after the first rainfall of the wet season in early December with peak concentrations maintained until late January. The CO2 increase reflected the initiation of rapid microbial respiration from soil and vegetation sources upon initial wetting. As the wet season progressed, daily CO2 concentrations were variable, but generally decreased back to dry season levels as CO2 assimilation by photosynthesis increased. Mean daily concentrations of CH4 increased in the wet season by up to 0.2 ppmv relative to dry season levels as the soil profile became waterlogged after heavy rainfall events. During the dry season there was regular cycling between maximum CO2/minimum δ13C‐CO2 at night and minimum CO2/maximum δ13C‐CO2 during the day. In the wet season diel patterns were less regular in response to variable cloud cover and rainfall. CO2 isotope data showed that in the wet season, surface CO2 was predominantly a two‐component mixture influenced by C3 plant assimilation (day) and soil/plant respiration (night), while regional background air from higher altitudes represented an additional CO2 source in the dry season. Higher wind speeds during the dry season increased vertical mixing compared to the wet season. In addition, night‐time advection of high‐altitude air during low temperature conditions also promoted mixing in the dry season.

Herb–subshrub diversity in open savanna sites with distinct fire regimes in the Jalapão region, Brazil

AbstractThe fire regime is essential in creating a mosaic of plant structure and diversity in South American open savannas, especially favouring herbs. However, studies investigating diversity patterns in Neotropical savannas rarely focus on the herb–subshrub layer. This study investigated the variation of the herb–subshrub layer under contrasting fire regimes in the most conserved site within the Cerrado Domain, the Jalapão region, Brazil. We selected four sites of open savanna physiognomy with similar topographic, climatic and edaphic features: three burned every 2 years, while the fourth site has remained unburned for at least the last 10 years. We randomly distributed 15 plots of 4 m2 in each site and identified all herbs and subshrubs in each plot to estimate density, richness, alpha diversity and species composition. The unburned site had lower herb–subshrub density, richness and diversity than the frequently burned sites. Species composition varied between frequently burned and unburned sites, partially explained by the fire frequency across sites. Although other ecological factors may explain the patterns detected, we cannot rule out the importance of fire in structuring plant communities in the Jalapão region. As in other savannas, our study in the Cerrado Domain reinforces the essential role of the fire regimes in modifying and maintaining the diversity of herbaceous plants at the landscape scale.

Understanding and reducing the uncertainties of land surface energy flux partitioning within CMIP6 land models

Land surfaces dissipate energy through latent (LE) and sensible (H) heat fluxes that modulate atmospheric temperature and humidity, which in return affect land surface vegetation and soil processes. Within this two-way land-atmosphere coupling, surface energy partitioning (LE versus H) plays a central role in connecting the land and atmosphere states and fluxes. However, considerably large uncertainties still exist in earth system land models, i.e. the phase 6 of the Coupled Model Intercomparison Project (CMIP6). Further, the underlying controls from climate and biological factors on surface energy partitioning over different biome types are not well understood. In this study, we combined machine learning (ML) and causal inference models to investigate and reduce the uncertainties (i.e., parametric, structural, and forcing uncertainties) of CMIP6 simulated evaporative fraction (defined as LE / (LE + H)) across 64 FLUXNET sites that cover five major biomes. We found that CMIP6 model ensembles overestimated evaporative fraction with considerable spread at deciduous broadleaf forest, evergreen needleleaf forest, and savanna sites. Accounting for the biases from all related surface climate and biological driving variables, the CMIP6 model simulated EF could be largely improved (e.g., R between model and observed EF improved from 0.47 to 0.66), with leaf area index, vapor pressure deficit, and precipitation dominated the model improvement. Furthermore, ML-based parameterization generally showed a promising opportunity to further reduce model biases (e.g., R improved from 0.66 to 0.80) in spite of the limited improvement at evergreen broadleaf forest sites where model bias may be dominated by structural imperfection. This study provided an effective framework to understand and reduce model uncertainties in simulating land surface energy flux partitioning and, more importantly, highlighted the need of effective model structure improvement for the next generation earth system land model development.

Bedrock Vadose Zone Storage Dynamics Under Extreme Drought: Consequences for Plant Water Availability, Recharge, and Runoff

AbstractBedrock vadose zone water storage (i.e., rock moisture) dynamics are rarely observed but potentially key to understanding drought responses. Exploiting a borehole network at a Mediterranean blue oak savanna site—Rancho Venada—we document how water storage capacity in deeply weathered bedrock profiles regulates woody plant water availability and groundwater recharge. The site is in the Northern California Coast Range within steeply dipping turbidites. In a wet year (water year 2019; 647 mm of precipitation), rock moisture was quickly replenished to a characteristic storage capacity, recharging groundwater that emerged at springs to generate streamflow. In the subsequent rainless summer growing season, rock moisture was depleted by about 93 mm. In two drought years that followed (212 and 121 mm of precipitation) the total amount of rock moisture gained each winter was about 54 and 20 mm, respectively, and declines were documented exceeding these amounts, resulting in progressively lower rock moisture content. Oaks, which are rooted into bedrock, demonstrated signs of water stress in drought, including reduced transpiration rates and extremely low water potentials. In the 2020–2021 drought, precipitation did not exceed storage capacity, resulting in variable belowground water storage, increased plant water stress, and no recharge or runoff. Rock moisture deficits (rather than soil moisture deficits) explain these responses.

Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient?

Abstract. Most terrestrial biosphere models (TBMs) rely on more or less detailed information about the properties of the local vegetation. In contrast, optimality-based models require much less information about the local vegetation as they are designed to predict vegetation properties based on general principles related to natural selection and physiological limits. Although such models are not expected to reproduce current vegetation behaviour as closely as models that use local information, they promise to predict the behaviour of natural vegetation under future conditions, including the effects of physiological plasticity and shifts of species composition, which are difficult to capture by extrapolation of past observations. A previous model intercomparison using conventional TBMs revealed a range of deficiencies in reproducing water and carbon fluxes for savanna sites along a precipitation gradient of the North Australian Tropical Transect (Whitley et al., 2016). Here, we examine the ability of an optimality-based model (the Vegetation Optimality Model, VOM) to predict vegetation behaviour for the same savanna sites. The VOM optimizes key vegetation properties such as foliage cover, rooting depth and water use parameters in order to maximize the net carbon profit (NCP), defined as the difference between total carbon taken up by photosynthesis minus the carbon invested in construction and maintenance of plant organs. Despite a reduced need for input data, the VOM performed similarly to or better than the conventional TBMs in terms of reproducing the seasonal amplitude and mean annual fluxes recorded by flux towers at the different sites. It had a relative error of 0.08 for the seasonal amplitude in ET and was among the three best models tested with the smallest relative error in the seasonal amplitude of gross primary productivity (GPP). Nevertheless, the VOM displayed some persistent deviations from observations, especially for GPP, namely an underestimation of dry season evapotranspiration at the wettest site, suggesting that the hydrological assumptions (free drainage) have a strong influence on the results. Furthermore, our study exposes a persistent overprediction of vegetation cover and carbon uptake during the wet seasons by the VOM. Our analysis revealed several areas for improvement in the VOM and the applied optimality theory, including a better representation of the hydrological settings as well as the costs and benefits related to plant water transport and light capture by the canopy. The results of this study imply that vegetation optimality is a promising approach to explain vegetation dynamics and the resulting fluxes. It provides a way to derive vegetation properties independently of observations and allows for a more insightful evaluation of model shortcomings as no calibration or site-specific information is required.

Influence of modifications (from AoB2015 to v0.5) in the Vegetation Optimality Model

Abstract. The Vegetation Optimality Model (VOM, Schymanski et al., 2009, 2015) is an optimality-based, coupled water–vegetation model that predicts vegetation properties and behaviour based on optimality theory rather than calibrating vegetation properties or prescribing them based on observations, as most conventional models do. Several updates to previous applications of the VOM have been made for the study in the accompanying paper of Nijzink et al. (2022), where we assess whether optimality theory can alleviate common shortcomings of conventional models, as identified in a previous model inter-comparison study along the North Australian Tropical Transect (NATT, Whitley et al., 2016). Therefore, we assess in this technical paper how the updates to the model and input data would have affected the original results of Schymanski et al. (2015), and we implemented these changes one at a time. The model updates included extended input data, the use of variable atmospheric CO2 levels, modified soil properties, implementation of free drainage conditions, and the addition of grass rooting depths to the optimized vegetation properties. A systematic assessment of these changes was carried out by adding each individual modification to the original version of the VOM at the flux tower site of Howard Springs, Australia. The analysis revealed that the implemented changes affected the simulation of mean annual evapotranspiration (ET) and gross primary productivity (GPP) by no more than 20 %, with the largest effects caused by the newly imposed free drainage conditions and modified soil texture. Free drainage conditions led to an underestimation of ET and GPP in comparison with the results of Schymanski et al. (2015), whereas more fine-grained soil textures increased the water storage in the soil and resulted in increased GPP. Although part of the effect of free drainage was compensated for by the updated soil texture, when combining all changes, the resulting effect on the simulated fluxes was still dominated by the effect of implementing free drainage conditions. Eventually, the relative error for the mean annual ET, in comparison with flux tower observations, changed from an 8.4 % overestimation to an 10.2 % underestimation, whereas the relative errors for the mean annual GPP remained similar, with an overestimation that slightly reduced from 17.8 % to 14.7 %. The sensitivity to free drainage conditions suggests that a realistic representation of groundwater dynamics is very important for predicting ET and GPP at a tropical open-forest savanna site as investigated here. The modest changes in model outputs highlighted the robustness of the optimization approach that is central to the VOM architecture.