Different Land Use Intensities in Grassland Ecosystems Drive Ecology of Microbial Communities Involved in Nitrogen Turnover in Soil

Understanding factors driving the ecology of N cycling microbial communities is of central importance for sustainable land use. In this study we report changes of abundance of denitrifiers, nitrifiers and nitrogen-fixing microorganisms (based on qPCR data for selected functional genes) in response to different land use intensity levels and the consequences for potential turnover rates. We investigated selected grassland sites being comparable with respect to soil type and climatic conditions, which have been continuously treated for many years as intensely used meadows (IM), intensely used mown pastures (IP) and extensively used pastures (EP), respectively. The obtained data were linked to above ground biodiversity pattern as well as water extractable fractions of nitrogen and carbon in soil. Shifts in land use intensity changed plant community composition from systems dominated by s-strategists in extensive managed grasslands to c-strategist dominated communities in intensive managed grasslands. Along the different types of land use intensity, the availability of inorganic nitrogen regulated the abundance of bacterial and archaeal ammonia oxidizers. In contrast, the amount of dissolved organic nitrogen determined the abundance of denitrifiers (nirS and nirK). The high abundance of nifH carrying bacteria at intensive managed sites gave evidence that the amounts of substrates as energy source outcompete the high availability of inorganic nitrogen in these sites. Overall, we revealed that abundance and function of microorganisms involved in key processes of inorganic N cycling (nitrification, denitrification and N fixation) might be independently regulated by different abiotic and biotic factors in response to land use intensity.

The ecological consequences of megafaunal loss: giant tortoises and wetland biodiversity

The giant tortoises of the Galapagos have become greatly depleted since European discovery of the islands in the 16th Century, with populations declining from an estimated 250000 to between 8000 and 14000 in the 1970s. Successful tortoise conservation efforts have focused on species recovery, but ecosystem conservation and restoration requires a better understanding of the wider ecological consequences of this drastic reduction in the archipelago's only large native herbivore. We report the first evidence from palaeoecological records of coprophilous fungal spores of the formerly more extensive geographical range of giant tortoises in the highlands of Santa Cruz Island. Upland tortoise populations on Santa Cruz declined 500-700years ago, likely the result of human impact or possible climatic change. Former freshwater wetlands, a now limited habitat-type, were found to have converted to Sphagnum bogs concomitant with tortoise loss, subsequently leading to the decline of several now-rare or extinct plant species.

The Interplay of Power and Trust in Platform Ecosystems of the Enterprise Application Software Industry

In recent years, the formerly oligopolistic Enterprise Application Software (EAS) industry began to disintegrate into focal inter-firm networks with one huge, powerful, and multi-national plat-form vendor as the center, surrounded by hundreds or even thousands of small, niche players that act as complementors. From a theoretical point of view, these platform ecosystems may be governed by two organizing principles - trust and power. However, it is neither from a practical nor from a theoretical perspective clear, how trust and power relate to each other, i.e. whether they act as complements or substitutes. This study tries to elaborate our understanding of the relationship of trust and power by exploring their interplay using multi-dimensional conceptual-izations of trust and power, and by investigating potential dynamics in this interplay over the course of a partnership. Based on an exploratory multiple-case study of seven dyadic partner-ships between four platform vendors, and seven complementors, we find six different patterns of how trust and power interact over time. These patterns bear important implications for the suc-cessful management of partnerships between platform vendors and complementors, and clarify the theoretical debate surrounding the relationship of trust and power.

Analyzing PL/1 Legacy Ecosystems: An Experience Report

This paper presents a case study of analyzing a legacy PL/1 ecosystem that has grown for 40 years to support the business needs of a large banking company. In order to support the stakeholders in analyzing it we developed St1-PL/1 — a tool that parses the code for association data and computes structural metrics which it then visualizes using top-down interactive exploration. Before building the tool and after demonstrating it to stakeholders we conducted several interviews to learn about legacy ecosystem analysis requirements. We briefly introduce the tool and then present results of analysing the case study. We show that although the vision for the future is to have an ecosystem architecture in which systems are as decoupled as possible the current state of the ecosystem is still removed from this. We also present some of the lessons learned during our experience discussions with stakeholders which include their interests in automatically assessing the quality of the legacy code.

Categorizing Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of the information needs of software developers who work in projects that are part of larger ecosystems. In an open- question survey we asked framework and library developers about their information needs with respect to both their upstream and downstream projects. We investigated what kind of information is required, why is it necessary, and how the developers obtain this information. The results show that the downstream needs are grouped into three categories roughly corresponding to the different stages in their relation with an upstream: selection, adop- tion, and co-evolution. The less numerous upstream needs are grouped into two categories: project statistics and code usage. The current practices part of the study shows that to sat- isfy many of these needs developers use non-specific tools and ad hoc methods. We believe that this is a largely unexplored area of research.

Nutrient additions affecting matter turnover in forest and pasture ecosystems

Nutrient inputs into ecosystems of the tropical mountain rainforest region are projected to further increase in the next decades. To investigate whether important ecosystem services such as nutrient cycling and matter turnover in native forests and pasture ecosystems show different patterns of response, two nutrient addition experiments have been established: NUMEX in the forest and FERPAST at the pasture. Both ecosystems already responded 1.5 years after the start of nutrient application (N, P, NP, Ca). Interestingly, most nutrients remained in the respective systems. While the pasture grass was co-limited by N and P, most tree species responded to P addition. Soil microbial biomass in the forest litter layer increased after NP fertilization pointing to nutrient co-limitation. In pasture soils, microorganisms were neither limited by N nor P. The results support the hypothesis that multiple and temporally variable nutrient limitations can coexist in tropical ecosystems.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Impact of an abrupt cooling event on interglacial methane emissions in northern peatlands

Rapid changes in atmospheric methane (CH4), temperature and precipitation are documented by Greenland ice core data both for glacial times (the so called Dansgaard-Oeschger (D-O) events) as well as for a cooling event in the early Holocene (the 8.2 kyr event). The onsets of D-O warm events are paralleled by abrupt increases in CH4 by up to 250 ppb in a few decades. Vice versa, the 8.2 kyr event is accompanied by an intermittent decrease in CH4 of about 80 ppb over 150 yr. The abrupt CH4 changes are thought to mainly originate from source emission variations in tropical and boreal wet ecosystems, but complex process oriented bottom-up model estimates of the changes in these ecosystems during rapid climate changes are still missing. Here we present simulations of CH4 emissions from northern peatlands with the LPJ-Bern dynamic global vegetation model. The model represents CH4 production and oxidation in soils and transport by ebullition, through plant aerenchyma, and by diffusion. Parameters are tuned to represent site emission data as well as inversion-based estimates of northern wetland emissions. The model is forced with climate input data from freshwater hosing experiments using the NCAR CSM1.4 climate model to simulate an abrupt cooling event. A concentration reduction of ~10 ppb is simulated per degree K change of mean northern hemispheric surface temperature in peatlands. Peatland emissions are equally sensitive to both changes in temperature and in precipitation. If simulated changes are taken as an analogy to the 8.2 kyr event, boreal peatland emissions alone could only explain 23 of the 80 ppb decline in atmospheric methane concentration. This points to a significant contribution to source changes from low latitude and tropical wetlands to this event.