First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness model, the greenness and radiation model and a light use efficiency model. The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3 to 65 percent). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation, root-mean-square error, and Bayesian information criterion. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models. The results of this study show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.Comment: Accepted manuscript; 12 pages, 4 tables, 9 figure

Upside-down fluxes Down Under: CO2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest

Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800mm and a mean annual temperature of 18°C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225gCm−2yr−1 on average, with a standard deviation of 108gCm−2yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2= 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.The Australian Education Investment Fund, Australian Terrestrial Ecosystem Research Network, Australian Research Council and Hawkesbury Institute for the Environment at Western Sydney University supported this work. We thank Jason Beringer, Helen Cleugh, Ray Leuning and Eva van Gorsel for advice and support. Senani Karunaratne provided soil classification details

Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales

Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2 = 0.77) to interannual (R2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms

Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America

We use the terrestrial ecosystem model (TEM), a process-based model, to investigate how interactions between carbon (C) and nitrogen (N) dynamics affect predictions of net primary productivity (NPP) for potential vegetation in North America. Data on pool sizes and fluxes of C and N from intensively studied field sites are used to calibrate the model for each of 17 non-wetland vegetation types. We use information on climate, soils, and vegetation to make estimates for each of 11,299 non-wetland, 0.5° latitude × 0.5° longitude, grid cells in North America. The potential annual NPP and net N mineralization (NETNMIN) of North America are estimated to be 7.032 × 1015 g C yr−1 and 104.6 × 1012 g N yr−1, respectively. Both NPP and NETNMIN increase along gradients of increasing temperature and moisture in northern and temperate regions of the continent, respectively. Nitrogen limitation of productivity is weak in tropical forests, increasingly stronger in temperate and boreal forests, and very strong in tundra ecosystems. The degree to which productivity is limited by the availability of N also varies within ecosystems. Thus spatial resolution in estimating exchanges of C between the atmosphere and the terrestrial biosphere is improved by modeling the linkage between C and N dynamics. We also perform a factorial experiment with TEM on temperate mixed forest in North America to evaluate the importance of considering interactions between C and N dynamics in the response of NPP to an elevated temperature of 2°C. With the C cycle uncoupled from the N cycle, NPP decreases primarily because of higher plant respiration. However, with the C and N cycles coupled, NPP increases because productivity that is due to increased N availability more than offsets the higher costs of plant respiration. Thus, to investigate how global change will affect biosphere-atmosphere interactions, process-based models need to consider linkages between the C and N cycles

EFFECTS OF LAND COVER, WATER REDISTRIBUTION, AND TEMPERATURE ON ECOSYSTEM PROCESSES IN THE SOUTH PLATTE BASIN

Over one‐third of the land area in the South Platte Basin of Colorado, Nebraska, and Wyoming, has been converted to croplands. Irrigated cropland now comprises 8% of the basin, while dry croplands make up 31%. We used the RHESSys model to compare the changes in plant productivity and vegetation‐related hydrological processes that occurred as a result of either land cover alteration or directional temperature changes (−2°C, +4°C). Land cover change exerted more control over annual plant productivity and water fluxes for converted grasslands, while the effect of temperature changes on productivity and water fluxes was stronger in the mountain vegetation. Throughout the basin, land cover change increased the annual loss of water to the atmosphere by 114 mm via evaporation and transpiration, an increase of 37%. Both irrigated and nonirrigated grains became active earlier in the year than shortgrass steppe, leading to a seasonal shift in water losses to the atmosphere. Basin‐wide photosynthesis increased by 80% due to grain production. In contrast, a 4°C warming scenario caused annual transpiration to increase by only 3% and annual evaporation to increase by 28%, for a total increase of 71 mm. Warming decreased basin‐wide photosynthesis by 16%. There is a large elevational range from east to west in the South Platte Basin, which encompasses the western edge of the Great Plains and the eastern front of the Rocky Mountains. This elevational gain is accompanied by great changes in topographic complexity, vegetation type, and climate. Shortgrass steppe and crops found at elevations between 850 and 1800 m give way to coniferous forests and tundra between 1800 and 4000 m. Climate is increasingly dominated by winter snow precipitation with increasing elevation, and the timing of snowmelt influences tundra and forest ecosystem productivity, soil moisture, and downstream discharge. Mean annual precipitation of \u3c500 mm on the plains below 1800 m is far less than potential evapotranspiration of 1000–1500 mm and is insufficient for optimum plant productivity. The changes in water flux and photosynthesis from conversion of steppe to cropland are the result of redistribution of snowmelt water from the mountains and groundwater pumping through irrigation projects

Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters

Ecosystem models are useful tools for evaluating environmental controls on carbon and water cycles under past or future conditions. In this paper we compare annual carbon and water fluxes from nine boreal spruce forest ecosystem models in a series of sensitivity simulations. For each comparison, a single climate driver or forest site parameter was altered in a separate sensitivity run. Driver and parameter changes were prescribed principally to be large enough to identify and isolate any major differences in model responses, while also remaining within the range of variability that the boreal forest biome may be exposed to over a time period of several decades. The models simulated plant production, autotrophic and heterotrophic respiration, and evapotranspiration (ET) for a black spruce site in the boreal forest of central Canada (56°N). Results revealed that there were common model responses in gross primary production, plant respiration, and ET fluxes to prescribed changes in air temperature or surface irradiance and to decreased precipitation amounts. The models were also similar in their responses to variations in canopy leaf area, leaf nitrogen content, and surface organic layer thickness. The models had different sensitivities to certain parameters, namely the net primary production response to increased CO2 levels, and the response of soil microbial respiration to precipitation inputs and soil wetness. These differences can be explained by the type (or absence) of photosynthesis-CO2 response curves in the models and by response algorithms of litter and humus decomposition to drying effects in organic soils of the boreal spruce ecosystem. Differences in the couplings of photosynthesis and soil respiration to nitrogen availability may also explain divergent model responses. Sensitivity comparisons imply that past conditions of the ecosystem represented in the models\u27 initial standing wood and soil carbon pools, including historical climate patterns and the time since the last major disturbance, can be as important as potential climatic changes to prediction of the annual ecosystem carbon balance in this boreal spruce forest

Overview of the Large-Scale Biosphere–Atmosphere Experiment in Amazonia Data Model Intercomparison Project (LBA-DMIP)

A fundamental question connecting terrestrial ecology and global climate change is the sensitivity of key terrestrial biomes to climatic variability and change. The Amazon region is such a key biome: it contains unparalleled biological diversity, a globally significant store of organic carbon, and it is a potent engine driving global cycles of water and energy. The importance of understanding how land surface dynamics of the Amazon region respond to climatic variability and change is widely appreciated, but despite significant recent advances, large gaps in our understanding remain. Understanding of energy and carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Land surface/ecosystem models have become important tools for extrapolating local observations and understanding to much larger terrestrial regions. They are also valuable tools to test hypothesis on ecosystem functioning. Funded by NASA under the auspices of the LBA (the Large-Scale Biosphere–Atmosphere Experiment in Amazonia), the LBA Data Model Intercomparison Project (LBA-DMIP) uses a comprehensive data set from an observational network of flux towers across the Amazon, and an ecosystem modeling community engaged in ongoing studies using a suite of different land surface and terrestrial ecosystem models to understand Amazon forest function. Here an overview of this project is presented accompanied by a description of the measurement sites, data, models and protocol

Impacts of climate change on rice production in Africa and causes of simulated yield changes

This study is the first of its kind to quantify possible effects of climate change on rice production in Africa. We simulated impacts on rice in irrigated systems (dry season and wet season) and rainfed systems (upland and lowland). We simulated the use of rice varieties with a higher temperature sum as adaptation option. We simulated rice yields for 4 RCP climate change scenarios and identified causes of yield declines. Without adaptation, shortening of the growing period due to higher temperatures had a negative impact on yields (−24% in RCP 8.5 in 2070 compared with the baseline year 2000). With varieties that have a high temperature sum, the length of the growing period would remain the same as under the baseline conditions. With this adaptation option rainfed rice yields would increase slightly (+8%) but they remain subject to water availability constraints. Irrigated rice yields in East Africa would increase (+25%) due to more favourable temperatures and due to CO2 fertilization. Wet season irrigated rice yields in West Africa were projected to change by −21% or +7% (without/with adaptation). Without adaptation irrigated rice yields in West Africa in the dry season would decrease by −45% with adaptation they would decrease significantly less (−15%). The main cause of this decline was reduced photosynthesis at extremely high temperatures. Simulated heat sterility hardly increased and was not found a major cause for yield decline. The implications for these findings are as follows. For East Africa to benefit from climate change, improved water and nutrient management will be needed to benefit fully from the more favourable temperatures and increased CO2 concentrations. For West Africa, more research is needed on photosynthesis processes at extreme temperatures and on adaptation options such as shifting sowing dates

Modeling oil palm monoculture and its associated impacts on land-atmosphere carbon, water and energy fluxes in Indonesia

In dieser Studie wird ein neues Modul “CLM-Palm” für mehrjährige Nutzpflanzen zur Modellierung einer funktionellen Gruppe (plant functional type) für Ölpalmen im Rahmen des Community Land Models (CLM4.5) entwickelt, um die Auswirkungen der Transformation eines tropischen Waldes in eine Ölpalmenplantage auf die Kohlenstoff-, Wasser- und Energieflüsse zwischen Land und Atmosphäre zu quantifizieren. Um die Morphologie der Ölpalme möglichst detailgetreu darzustellen (das heißt, dass ungefähr 40 Phytomere einen mehrschichtigen Kronenraum formen), wird in dem Modul CLM-Palm eine phänologische und  physiologische Parametrisierung auf Skalen unterhalb des Kronraums eingeführt, so dass jedem Phytomer sein eigenes prognostisches Blattwachstum und seine Erntekapazität zugeordnet wird, während Stamm und Wurzeln gemeinsam genutzt werden. Das Modul CLM-Palm wurde ausschließlich für Ölpalmen getestet, ist aber auch für andere Palmarten (z. B. Kokospalmen) interessant.  Im ersten Kapitel dieser Arbeit werden Hintergrund und Motivation dieser Arbeit vorgestellt. In Kapitel 2 wird die Entwicklung des Haupt- bzw. Kernmodells beschrieben,  inklusive Phänologie und Allokationsfunktionen zur Simulation des Wachstums und des Ertrags der Palme PFT, wodurch die Basis zur Modellierung  der biophysikalischen und biogeochemicalischen Kreisläufe innerhalb dieser Monokultur bereitgestellt wird. Die neuen Parameter für die Phänologie und die Allokation wurden sorgfältig mit Feldmessungen des Blattflächenindexes (LAI), des Ertrags und der Nettoprimärproduktion (NPP) verschiedener Ölpalmenplantagen auf Sumatra (Indonesien) kalibriert und validiert. Die Validierung zeigte die Eignung von CLM-Palm zur adäquaten Vorhersage des mittleren Blattwachstums und Ertrags für verschiedene Standorte und repräsentiert in ausreichendem Maß die signifikante Variabilität bezüglich des Stickstoffs und Alters von Standort zu Standort.  In Kapitel 3 wird die weitere Modellentwicklung und die Implementierung eines Norman-Mehrschichtmodells für den Strahlungstransport vorgestellt, das an den  mehrschichtigen Kronenraum der Ölpalme angepasst ist. Dieses Norman-Mehrschichtmodell des Strahlungstransports zeigte im Vergleich zu dem in CLM4.5 implementierten Standardmodell (basierend auf großen Blättern) bei der Simulation der Licht-Photosynthese-Kurve leichte Verbesserungen und hat  lediglich marginale Vorteile gegenüber dem ebenfalls in CLM4.5 implementierten alternativen statistischen Mehrschichtmodell.  Dennoch liefert das Norman-Modell eine detailliertere und realistischere Repräsentation des Belaubungszustands wie etwa dem dynamischen LAI, der Blattwinkelverteilung in verschiedenen Höhen, und ein ausgewogeneres Profil der absorbierten photosynthetisch aktiven Strahlung (PAR). Die Validierung mit Hilfe der Eddy-Kovarianz Flussdaten zeigte die Stärke von CLM-Palm bei der Simulation der Kohlenstoffflüsse, offenbarte aber auch Abweichungen in der simulierten Evapotranspiration (ET), dem sensiblen und dem latenten Wärmefluss (H und LE). Eine Reihe von hydrologischen Messungen im Kronenraum wird in Kapitel 4 beschrieben. Dies beinhaltet eine Adaption des in CLM4.5 eingebauten Standardmodells für Niederschlag, Interzeption und Speicherfunktionen für die speziellen Merkmale eines Ölpalmen-Kronenraums. Die überarbeitete Hydrologie des Kronenraums behob die Probleme bei der Simulation der Wasserflüsse (ET und Transpiration im Kronenraum) und verbesserte die Energieaufteilung zwischen H und LE. Kapitel 5 dokumentiert die Implementierung eines neuen dynamischen Modells für Stickstoff (nitrogen, N) in CLM-Palm zur Verbesserung der Simulation der C- und N-Dynamik, insbesondere mit Bezug auf den N-Düngeeffekte in landwirtschaftlich genutzten Systemen. Das dynamische N-Modell durchbricht die Limitierung des Standardmodells in CLM4.5, mit fixierter C-N-Stöchiometrie und erlaubt die Variation des C:N-Verhältnisses in lebendem Gewebe in Abhängigkeit der N-Verfügbarkeit und dem N-Bedarf der Pflanze.  Eine Reihe von Tests bezüglich der Düngung zeigte beispielhaft die Vorteile des dynamischen N-Modells, wie zum Beispiel die Verbesserung des Netto-Ökosystemaustauschs (net ecosystem exchange, NEE), ein realistischeres C:N-Verhältnis im Blatt, eine verbesserte Repräsentation der Effizienz des Stickstoffeinsatzes (nitrogen-use efficiency, NUE), sowie der Effekte von Düngung auf Wachstum und Ertrag. Abschließend wird in Kapitel 6 eine Anwendungsstudie gezeigt, in der die zentralen Modellentwicklungen aus den vorangegangenen Kapiteln verwendet werden. Eine junge und eine  erntereife Ölpalmenplantage sowie ein Primärregenwald wurden simuliert und verglichen. Sie wiesen klare Unterschiede in den C-Flüssen und in den biophysikalischen Merkmalen (z.B. ET und Oberflächentemperatur) auf. Ölpalmenplantagen können durch Wachstumsentwicklung (im Alter von etwa 4 Jahren)  ebenso hohe und darüber hinausgehende C-Assimilation und Wassernutzungsraten erreichen wie Regenwälder, haben jedoch im Allgemeinen eine höhere Oberflächentemperatur als eine bewaldete Fläche – dies gilt auch für erntereife Plantagen. Eine Simulation des Übergangs, die zwei Rotationsperioden mit Neubepflanzungen alle 25 Jahre umspannt, zeigte dass der Anbau von Ölpalmen auf längeren Zeitskalen lediglich in etwa die Hälfte des ursprünglichen C-Speichers der bewaldeten Fläche vor dem Kahlschlag  rückspeichern kann. Das im Boden gespeicherte C nimmt in einer bewirtschafteten Plantage aufgrund des begrenzten Streurücklaufs langsam und graduell ab. Insgesamt reduziert die Umwandlung eines Regenwaldes in eine Ölpalmenplantage die langfristigen C-Speicher und die Kapazität der Fläche zur C-Sequestrierung und trägt potentiell zur Erwärmung der Landoberfläche bei – trotz des schnellen Wachstums und der hohen C-Assimilationsrate einer stark gedüngten Plantage. Zur Einschätzung der regionalen und globalen Effekte der Ausbreitung der Kultivierung von Ölpalmen auf die Austauschprozesse zwischen Land und Atmosphäre und auf das Klima ist es notwendig eine Upscaling-Studie durchzuführen

Trade-offs Between Water Transport Capacity and Drought Resistance in Neotropical Canopy Liana and Tree Species

In tropical forest canopies, it is critical for upper shoots to efficiently provide water to leaves for physiological function while safely preventing loss of hydraulic conductivity due to cavitation during periods of soil water deficit or high evaporative demand. We compared hydraulic physiology of upper canopy trees and lianas in a seasonally dry tropical forest to test whether trade-offs between safety and efficiency of water transport shape differences in hydraulic function between these two major tropical woody growth forms. We found that lianas showed greater maximum stem-specific hydraulic conductivity than trees, but lost hydraulic conductivity at less negative water potentials than trees, resulting in a negative correlation and trade-off between safety and efficiency of water transport. Lianas also exhibited greater diurnal changes in leaf water potential than trees. The magnitude of diurnal water potential change was negatively correlated with sapwood capacitance, indicating that lianas are highly reliant on conducting capability to maintain leaf water status, whereas trees relied more on stored water in stems to maintain leaf water status. Leaf nitrogen concentration was related to maximum leaf-specific hydraulic conductivity only for lianas suggesting that greater water transport capacity is more tied to leaf processes in lianas compared to trees. Our results are consistent with a trade-off between safety and efficiency of water transport and may have implications for increasing liana abundance in neotropical forests