**4. Conclusions and outlook**

**3.4. Linking hydrological and plant ecological processes in evolving landscapes**

62 Hydrology of Artificial and Controlled Experiments

The spatiotemporal interplay between water and vegetation dynamics, and their feedbacks to physicochemical landscape (Section 3.2) and microbial community (Section 3.3) organization, profoundly impacts the evolution of a hillslope and its cycling of mass and energy. Hydrological processes exert primary controls on the establishment, distribution, structure, and function of ecosystems, while biotic processes directly (e.g., through transpiration) and indirectly (e.g., through alteration of soil properties) affect the cycling of water through the landscape [110, 111]. A substantial body of ecohydrological research has examined plantwater interactions with respect to one-dimensional (vertical) water and nutrient fluxes at the patch scale [112], however, without incorporating lateral redistribution of water and nutrients imposed by hillslope morphology. Similarly, biogeography has been mindful of spatial patterns of drivers of vegetation distribution but has paid little attention to the inherent coevolution of the physical and biological realms as a process that drives the form and function of the biological and physical landscape. Due to their large scale and imposed gradients in topography and environmental conditions, as well as their climate control and monitoring capabilities, the LEO hillslopes provide the unique opportunity to tackle the gaps in our understanding of how physical-biological interactions drive landscape evolution in space and time. Working at the hillslope scale forces integration between one- and two-dimensional conceptualizations of ecohydrological processes and provides the topological structures that connect patches on the landscape by gravitational fluxes organized by hillslope morphology. From the patch or pedon perspective, the hillslope provides nonlocal controls on water and nutrient fluxes, while local controls at the patch scale influence downslope patches in the ecohydrological system.

The basic elements that define hillslope morphology, such as shape, gradient, aspect, and slope complexity (i.e., nonuniformity), affect water and energy availability (e.g., [3]). Hillslope shape expresses the convergence or divergence of surface flow paths in the planform (across slope) and profile (normal to slope) directions and therefore relates directly to soil moisture redistribution. Hillslope shape and gradient both affect runoff processes and erosion rates. Hillslope aspect directly influences irradiance and hence energy availability for evapotranspiration. Complex interactions at the hillslope scale between topography, soil development, runoff processes, and vegetation create self-reinforcing positive feedbacks in ecohydrological processes that must be considered to develop a comprehensive understanding of ecohydrological patterns and processes.

The effects of vegetation on physical processes will depend on the structure of the community [25]. One might hypothesize that shallow-rooted plants would have a much less significant impact on the ecohydrology of a hillslope than a deep-rooted shrub because they lack a physical integration with as much of the soil profile. But are ecohydrological process more influenced by percent cover of the soil (presumably higher in a lower-stature forb or grassland system), higher photosynthetic function that derives organic acids that can drive soil processes, or simply the water use efficiency of the vegetation, regardless of type? Abovegroundbelowground linkages are so inherently complex that when we add discussion of connections among soil pedons in space or consider the various members of a vegetative community, how little we know about the ecohydrology at the hillslope scale becomes glaringly apparent.

This chapter has presented the research infrastructure, facilities, and initial experimental results of the Landscape Evolution Observatory (LEO) project at the Biosphere 2. LEO is a carefully designed and massively outfitted macrocosm experiment of an unprecedented scale and ambition of scope. Each of the three model landscapes emulates a pristine, sloping zero-order basin consisting of more than 500 metric tons of homogenous basaltic tephra housed within climate-controlled bays. The infrastructure operates dense arrays of more than 1900 sensors and samplers per landscape that are complemented by state-of-the-art research support systems, including an isotope and trace gas analysis network, electrical resistivity tomography instrumentation, high-resolution remote imaging systems, and advanced analytical capabilities for analyzing liquids and solids. The combined capacity of these structures allows tracking states, fluxes, and pathways of water, energy, and critical elements such as carbon at sub-meter to landscape scales, arguably representing the most successful attempt to closing hydro-biogeochemical budgets for a hillslope-size system to date. The system importantly allows key developmental processes to be rigorously tracked, including changes in subsurface and the development of microbial and ultimately vascular plant communities.

LEO is fully operational and has recently (October 2016) entered its 10-year long institutional experiment. During this experiment, variable climate forcing (mainly rainfall treatments) will drive the initially simple, abiotic model landscapes into life-sustaining ecosystems. After a first phase of bare soil surface conditions that is scheduled to last approximately 2 to 3 years, the landscapes will be colonized by vascular plants able to germinate and grow on the poorly developed LEO soil. While the landscapes evolve to increasingly complex states, Earth scientists will have the opportunity to iteratively build knowledge on the interactions and feedbacks between hydrological, geochemical, geomorphological, microbial, and ecological processes that control landscape form and function, and to formalize this knowledge into distributed coupled-process models and closure relations at the hillslope-scale. The threefold replication of initial landscape conditions and climate treatment will thereby allow to develop and rigorously test (i.e., to accept or reject) laws of fundamental natural processes (e.g., flow and transport) at space-time scales relevant for prediction. In later phases, varying experimental treatments across the replicate slopes (e.g., different rainfall distribution, temperature or CO<sup>2</sup> levels) may drive divergent landscape evolutionary trajectories, which allow further evaluation and refinement of the knowledge and predictive capabilities gained.

**Author details**

Nate Abramson<sup>1</sup>

Matej Durcik5

Raina M. Maier<sup>7</sup>

Markus Tuller7

Craig Rasmussen<sup>7</sup>

Baltimore, MD, USA

AZ, USA

AZ, USA

AZ, USA

**References**

Till H. M. Volkmann<sup>1</sup>

Greg A. Barron-Gafford<sup>3</sup>

David D. Breshears6,8, Aaron Bugaj1

, Ty P. A. Ferre<sup>5</sup>

\*, Aditi Sengupta1

, Antonio A. Meira Neto<sup>5</sup>

, Russell K. Monson<sup>6</sup>

, Joost L. M. van Haren<sup>1</sup>

\*Address all correspondence to: tillv@email.arizona.edu 1 University of Arizona, Biosphere 2, Tucson, AZ, USA

9 United States Geological Survey, Menlo Park, CA, USA

Water Resources Research. 2015;**51**(7):4903-4922

11 University of Arizona, Department of Geosciences, Tucson, AZ, USA

, Ciaran J. Harman<sup>4</sup>

, Joaquin Ruiz1,11, Scott R. Saleska<sup>8</sup>

2 Georgia State University, Department of Geosciences, Atlanta, GA, USA

3 University of Arizona, School of Geography and Development, Tucson, AZ, USA

4 Johns Hopkins University, Department of Geography and Environmental Engineering,

5 University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson,

6 University of Arizona, School of Natural Resources and the Environment, Tucson,

7 University of Arizona, Department of Soil, Water and Environmental Science, Tucson,

10 University of California at Irvine, Center for Environmental Biology, Irvine, CA, USA

8 University of Arizona, Department of Ecology and Evolutionary Biology, Tucson, AZ, USA

[1] Troch PA, Carrillo GA, Heidbüchel I, Rajagopal S, Switanek M, Volkmann THM, et al. Dealing with landscape heterogeneity in watershed hydrology: A review of recent prog-

[2] Troch PA, Lahmers T, Meira A, Mukherjee R, Pedersen JW, Roy T, et al. Catchment coevolution: A useful framework for improving predictions of hydrological change?

ress toward new hydrological theory. Geography Compass. 2009;**3**(1):375-392

, Edward A. Hunt1

, Luke A. Pangle<sup>2</sup>

, Yadi Wang<sup>7</sup>

, Xubin Zeng<sup>5</sup>

, Guo-Yue Niu<sup>5</sup>

, Jon Chorover6,7, Alejandro Cueva1

, Katerina Dontsova<sup>1</sup>

, John R. Adams<sup>1</sup>

, Marcel G. Schaap7

and Peter A. Troch1,5

, Travis E. Huxman¹<sup>0</sup>

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution…

, Jon D. Pelletier<sup>11</sup>, Michael Pohlmann<sup>7</sup>

, Laura K. Meredith<sup>6</sup>

,

,

http://dx.doi.org/10.5772/intechopen.72325

, Minseok Kim<sup>4</sup>

,

,

, Stephen B. DeLong<sup>9</sup>

, Michael Sibayan1

,

,

65

,

The LEO infrastructure is designed as a community resource with open data availability and seeks to foster broad interdisciplinary collaboration and science planning. During the next 10 years, scientists from across the world will have the opportunity to propose smaller research projects that can be implemented without loss of objectives of the institutional experiment. For instance, researchers who would like to study certain rainfall-runoff dynamics can propose a sequence of rain events, or those commanding specific measurement or analysis capabilities are welcome to integrate those into existing efforts. Similarly, the reader is encouraged to contact the authors to share their ideas about research opportunities with respect to the planned evolutionary forcing of the landscapes. For example, the composition of the seed pool for the upcoming vascular plant colonization is still under debate. By rapidly iterating dense experimental measurement with community-based planning, data analysis, and model development, we envision that our understanding and ability to predict the coevolution of hydrological, biogeochemical, and ecological processes and their interactions under variable climate can be significantly improved. This vision will be tested when we ultimately extrapolate our understanding of abiotic-biotic system coevolution into the complex reality of natural environments to meet the challenge of predicting landscape-scale response to global change.
