More deeply rooted species can access existing and newly thawed deep soilnitrogen [Keuper, 2012]. In addition, roots acclimated to low temperatures in deep soil may have higher nutrient uptake capacity than roots in warmer surface soils [Chapin, 1974]. However, nitrogen in deeper soil is available for plant acquisition for a relatively shorter period than nitrogen in near-surface soil because the active layer thaws and increases in thickness throughout the growing season. Shallow-rooting species access soil nitrogen nearer the surface, and do so in the context of stronger microbial competition, but with more abundant soil nitrogen and over longer periods during the growing season. Therefore, different tundra species may respond dramatically differently to climate warming-induced soil nitrogen availability changes. The trade offs and ecological significance of plant carbon investments to compete for nitrogen in relatively warm shallow soils with high microbial competition, or to access nitrogen in relatively cold deeper soils with less microbial competition warrant further investigation. Second, root nitrogen uptake capacity is also an important trait for nutrient competitiveness. Species with low nitrogen uptake capacity must develop dense or long-lived roots in order to acquire enough soil nitrogen. For example, Carex aquatilis’s fine roots live for multiple years, and the fine root to leaf biomass ratio can be as large as 16 [Iversen et al., 2015b]. In contrast, species with high nitrogen uptake capacity invest less carbon for the growth of relatively short-lived roots [Eissenstat et al., 2000]. Third, tundra species with different carbon allocation strategies may contribute differently to carbon-climate interactions. For example, Carex aquatilis may fix more carbon per unit additional nitrogen uptake than Eriophorum angustifolium,vertical growing towers because the former allocate more carbon to grow roots and root C:N ratios are much higher than leaves .
Carbon costs of constructing roots are commonly lower than above ground tissues [Poorter, 1994]. In addition, tissue lifespan [Withington et al., 2006], decomposability [Hobbie et al., 2010], maintenance respiration [Segal and Sullivan, 2014], and contribution to soil carbon accumulation [Hu et al., 2016] differ among leaves and roots. Integration of these essential root traits into ESMs will improve understanding of how arctic tundra plants will respond to climate warming, through informing the magnitude of warming-induced increases in nitrogen availability on tundra carbon production.Current ESM land models have rudimentary representations of plant traits because of a lack of mechanistic understanding of how those traits control plant and ecosystem bio-geochemical processes and a lack of trait data to structure and parameterize large-scale simulations. We have recommended several key traits, which should improve predictions of root nitrogen uptake and how arctic tundra plants may respond to warming-induced elevated nitrogen availability. Some knowledge of the global spatial distributions of several of the aforementioned root traits is available. For root biomass profiles, the first global database was presented by Jackson et al. [1996]. Zeng [2001] further analyzed those biomass profile data according to Plant Functional Types and derived PFT-based root distribution data needed for large-scale land models. Schenk and Jackson [2002] expanded the Jackson et al. [1996] data set to include 475 root biomass profiles. However, most of those profile data are from temperate regions .Moreover, the PFT-based root distributions have not been updated accordingly. A global-scale maximum rooting depth data set was synthesized by Canadell et al. [1996] and included 253 plant species.
They also aggregated maximum rooting depth data based on PFTs, which is readily applicable to large-scale land models. The rooting depth followed the order: forest > shrub > herbaceous plants > – crops. However, within-PFT variation was quite large. For example, the maximum rooting depth of tropical species was 68 m, while the mean of tropical evergreen plant maximum rooting depth was about 15 m. Particularly for arctic tundra, a more detailed rooting depth data set was developed by Iversen et al. [2015a]. Tundra maximum rooting depth ranged from 0.7 cm for a deciduous shrub species to 100 cm for a forb species . In general, evergreen shrub tundra has the shallowest rooting depth . Grass, forb, and deciduous shrub tundra have deeper root systems , and sedge tundra has the deepest roots . This data set casts doubt on land model PFT classifications for arctic tundra. For example, CLM and ALM represent arctic tundra with only two PFTs , which substantially under represents root traits across the wide range of dominant tundra species, including arctic grasses, sedges, forbs, deciduous shrubs, and evergreen shrubs [Chapin et al., 1996].Travel to space is limited by the expense of transporting resources beyond Earth’s gravity well. As a result, early metrics of usability for space systems, especially life support, favored mass as the primary decision factor. Following a request to “provide the designers of future missions with mature technologies and hardware designs, as well as extensive performance data justifying confidence that highly reliable Advanced Life Support Systems that meet mission constraints can be developed” by the 1997 NASA Research Council, the scope of the Equivalent System Mass framework was broadened to account for differences in the cost of resources. The general principle behind this early metric was to calculate the mass of all of the resources required to make the system work. ESM was expanded from theory to the practice of accounting for processes ranging from controls, agriculture, and recycling. Currently, ESM remains the standard metric for evaluating ALS technology development and systems.
It has been adopted for use in trade studies, as the metric for life support sizing, and has been incorporated into several tools.Previous efforts to quantify the cost in problems of mission planning/space logistics have relied on metrics based solely on the Initial Mass to Low Earth Orbit for constant commodity supply and demand or on carry along mass. In such logistics frameworks like Space Net and HabNet, the cost is kept simple to allow for the analysis of complex mission architectures with multiple mission segments. Comparatively, ESM has been most fully developed for ECLSS where the costs of capital equipment, power, operations, transport, and other things have been captured on a common unit scale of mass. While it provides a method for summing the weighted terms of many subsystems, there is no explicit ESM equation that captures total mission costs across systems in various stages of a complex mission. Thus the standard ESM approach faces limitations in that there exists no explicit language for capturing the set of all segments and there exists interdependent relationships between the decision variables within separate segments. Here, we see a trade-off in the complexity of the cost function for the complexity of the mission architecture. As plans for human exploration continue to be made in anticipation of returning to the moon and traveling to Mars, an added emphasis will be required for the optimization of mission architecture. As of now, the current instance of the ESM framework does not lend itself to use as an objective function in optimization over a mission—although this ESM has been proposed as the metric for mission optimization. The result is that this standard framework remains fixed for multi-stage missions and generally faces challenges in providing design or planning information based on subsystem risk. Thus,container vertical farming the ESM metric is not always helpful when comparing missions with differential reliability for systems in their proper context. That is, given two possible technologies for meeting a mission objective, the one that is less likely to fail might be a better choice. To demonstrate how to formally add reliability metrics to the ESM framework, we take the case of a new technology platform, bio-manufacturing, for which there are known and quantifiable reliability concerns and for which there are little in situ testing for space missions. In the following work, we propose an extended ESM framework to account for the proposed multi-stage missions and critical mission features, such as reliability. As the scope of human exploration missions has expanded, the need for new technology platforms has grown, and it has been proposed that these features best capture the potential of bio-manufacturing systems. We do not claim completion of xESM, but rather, we demonstrate progress along this trajectory in the form of a more generalized framework to account for multi-staged mission segments ; account for reliability; and feed into downstream optimization problems. We also note that this later progress is less developed in more in line with a discussion rather than a ready-to-use operational strategy.Figure 1 depicts three profiles with varied transit architectures. Profile 1 uses a single journey from Earth to Mars, and although it has been proposed in some forms, it is unlikely this architecture will be adopted due to the substantial mass demands of the transit ship and the ascent propellant required to leave Mars. In the case of Profile 2 , cargo can be predeployed to Mars through some number of predeployment missions.
Profile 2 introduces segments to a crewed mission to Mars which are not actually crewed, but instead are either purely cargo-based in which case only the M and V terms factor into the ESM cost, or autonomous where M, V, P, and C for uncrewed operations matter. Since cargo missions do not require life support systems, the M cost is reduced greatly, leading to a reduction in overall mission cost, especially for missions that require a great number of goods that can be pre-deployed. In the most likely Profile 3, crew transportation can be further broken down such that smaller crewed vehicles make the jump from planet to surface and viceversa, but the interplanetary transit is made on a larger craft to reduce the mass required for egress from planetary gravity wells. Previous ESM literature allows for varied equivalency factors based on mission staging, and in such cases, the ESM of distinct segments of a mission are calculated separately, then normalized through the use of location factors. However, ESM M for any set of systems is calculated using a single location factor Leq term as a multiplier. In this form, it is assumed that each subsystem is transported in a uniform fashion or that all parts of a subsystem would correspond to a single Leq term. The profile expansion in Fig. 1 shows that inventory can be transported in different segments using different crafts which changes the value of Leq. This is supported by non-ESM logistics methods.The three Cases in Fig. 4 consider the food system and the potential impact of agricultural biotechnology to supply astronauts with their caloric and nutritional needs. We assume that each of six CMs has a daily dry mass food requirement of 0.617kg/ CM-d. We use this requirement to calculate the prepackaged food requirements of the two transit legs of each mission scenario, as well as the extra 70 or 500 days of food for surface operations in Cases 2s and 2b respectively. Given the recently updated infrastructure costs associated with a Mars Surface Habitat Vehicle, we calculate ESM through consideration of the food subsystem including food, packaging, refrigeration, and processing. In Case 2s, we consider only the stored food requirements from Case 2 from Fig. 3. In Case 2b, we consider the stored food requirements during surface operations decreased from 500d to 70d and the remaining food was produced via agriculture. In a long-duration mission scenario in which food is grown during surface operations, and where literature suggests that a sizable initial hardware set would be required. This set could include hydroponic growth chambers, water filtration, refrigeration, etc. along with additional support hardware like pumps, filters, etc. In Case 3, we consider the transportation of the bio-manufacturing system during predeployment rather than with the crew. During initial transit as well as the return transit, the crew relies on prepackaged food—crop growth begins on the first day of surface operations, necessitating another ~70 days of predeployed food while the surface hardware grows the first crop. Variations in crop selection and growth conditions during surface operations have been proposed, butthis bounding assumption is consistent with crops such as lettuce and wheat. Like Cases 0–3, xESM costs for Cases 2s, 2b, and 3b are larger than their ESM alternative, however, in Case 2s and Case 2b , the xESM option is significantly larger than the ESM option for calculation. The difference between the xESM and ESM calculation results is an increased mass on the transit to Mars and reduced mass for surface operations and return transit.