Intellectual Merit

Global warming necessitates monitoring of land use and land change as ecological stressors influence top-down and bottom-up trophic cascades. Variable climatic conditions, including inter-annual seasonal vegetative growth differences, require adaptive management of large herbivores to mitigate adverse impacts on plant communities and primary ecological processes. Modeled estimates of temperate grassland gross primary productivity and net primary productivity generally do not account for grazer offtake1. This gap in scientific knowledge begs for enhanced estimates of available forage following estimated ungulate offtake to maintain landscape ecological carrying capacity (ECC). Estimating carrying capacity with Big Data can assist conservation initiatives, such as with the U.S. national mammal bison (Bison bison), through measurable Big Data driven algorithms for estimating bison ECC across North America.

According to optimal foraging theory, animals seek to maximize fitness by maximizing nutrient intake per foraging time and habitat selection theory states that animals will select for habitat with resources necessary to maximize fitness2, 3, 4. Unless perturbed plant communities tend to develop and persist along environmental gradients of climate, topography, and soil type with associated soil biota5. We know that some plants are more resistant to environmental disturbance and that some species are more resilient following cessation of disturbance6. Drought can intensify disturbance in terms of forage availability and microorganism nutrient processing7,8.  Global increase in land and sea temperatures indicate an increase in U.S. northwestern regional annual average temperatures by 2˚F by 2030 and as much as 5˚F by 2050 9. Though elevated atmospheric CO₂ would favor C₃ plants climate variability could promote expansion of exotics and weedy species9. Warming climate could affect the ECC of semi-arid mixed-grass landscapes, such as the American Prairie Reserve and National Bison Range in Montana, by enhancing risks of ecological disturbance. Depending on intensity, duration and seasonal timing, grazing can re-structure communities, such that formerly dominant species decline in abundance and opportunistic species establish to fill the niche6, 10. In this way, bison can exert top-down trophic control and thereby increase diversity and structure landscape heterogeneity11.

During summer, a study on fine-scale dietary preferences of free-ranging bison indicated frequency independent selectively of forage to maximize nutrient intake12. A seasonal shift in bison diet suggests that bison adapt their forage consumption by selecting high nutrient plants during the growing season a finding that is consistent with the forage maturation hypothesis13, 14. In Wind Cave National Park grasses grazed by bison within prairie dog (Cynomylus dovicianucso) colonies consistently had higher leaf nitrogen concentrations than grasses in colonial areas without bison grazing and bison preferentially returned to graze high nutrient forage15, 16. In a Kansas tallgrass prairie study bison grazing altered fine scale grassland heterogeneity by changing plant community structure, i.e., decline in community dominance and rise in species richness and diversity11. According to an Alberta study, summer grazing altered local community structure by increasing the biomass of forbs by 10-20% and decreasing that of rough fescue (Festuca campestris Rydb.) by 30%10. 

While the impact of grazing on plant communities is spatially and temporally relative, changes in plant community composition due to grazing can affect the soil base and underlying ecological processes17, 18. Reversible transitions within a stable state indicate that ecological processes are intact and return to former community structure and function is possible with removal of stressors18,. However, if system self-repair is not possible after removal of stressors an ecological threshold has been crossed and a new stable state has established18. Changes in community dominance, as documented by field surveys and defined by the Natural Resource Conservation Service (NRCS) ecological site description, can be interpreted as a tool for identifying a potential ecological state shift and, if present, changes in ecological processes can be detected and quantified18, 19, 20. Accordingly, our focus should be on maintaining or restoring impaired ecological processes and less on holding to historical plant community groups18. Altered or impaired ecological processes can rebound when vegetation communities recover via human adjustment and balancing of ungulate stocking rates in response to quantified available forage estimates18, 21, 22, 23. 

Disturbance ecology and ungulate management are not mutually exclusive considering the uncertainty surrounding global warming and bi-directional trophic cascade effects. Unintended overgrazing consequently affects ecological processes and can in turn affect bison herd fitness. From a systems perspective, management is part of a larger study to investigate bison impacts on ecological processes and the mechanisms that manifest in vegetation community dynamics and production. Concerns surrounding climate change and its terrestrial trophic cascade effects resulting from hydrologic regime shifts are paramount, especially on enclosed ranges where preferred grazing habitat represents only a fraction of available space.  Nationwide, bison are generally managed on enclosed ranges where inter-annual estimates of bison ECC would serve a culturally significant and systems-oriented management approach. For example, Montana grasslands are ideal for case studies because diverse histories of bison management strategies exist on numerous private lands, sovereign tribal nations, and government agency managed habitats. 

Estimating carrying capacity with Big Data exemplifies the feasibility of joining applied research with ecological theory to gain insight into future application of effective range management practices. Multivariate applications for estimating year-round ungulate ECC can assist both wildlife and livestock managers by way of measurable decision support. We can now gain strong inference into bi-directional trophic cascade effects that are in large part controlled by humans. For example, landscape ecology and range management is a crucial part of the ultimate conservation goal of fitness and genetic integrity of bison. Enter Estimating Carrying Capacity with Big Data (ECCwBD), a user-friendly application rooted in systems ecology and environmental science concepts relevant to mitigating global warming trophic cascade effects by way of assisting conservation, resource inventory and strategic animal management practices24,.

Survivingenious LLC maintains ECCwBD by developing code relevant to assisting agricultural, conservation, resource inventory and strategic animal management practices via branched algorithmic summarization and statistical inference application toolsets. Streamlined cloud-based integration of data with automated and/or human observed, updatable inputs offers flexibility. Ecological or any otherwise client defined models of interest developed to answer client-based questions increases applicability of responsive model frameworks. Reflective prediction with responsive models, persistently updated with near real time data, can increase efficiency for multiple sectors including agricultural, science and engineering. Expedited analysis happens as client defined models based on historical data, KPIs and random effects per field/department are updated and respond with estimates of current productivity. Further development includes, independent analytical applications and/or website creation to host updatable online applications and databases. 

DLB ~ Survivingenious LLC

LITERATURE CITED

1NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC) at the USGS Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota. 2020 https://lpdaac.usgs.gov 

2Werner, E. E. and D. J. Hall 1974. Optimal Foraging and the Size Selection of Prey by the Bluegill Sunfish (Lepomis Macrochirus). Ecology 55(5):1042-1052.

3Abercrombie, M., et al. 1966. A Dictionary of Biology. London: Penguin Reference Books.

4Ashton D. C., et al. 2011. Predictive Species and Habitat Modeling in Landscape Ecology. Springer.

5Westoby, M., B. Walker, and I. Noy-Meir. Opportunistic Management for Rangelands Not at Equilibrium. Journal of Range Management 42(4):266-274.

6Whittaker, R. H. 1953. A consideration of climax theory: the climax as a population and pattern. Ecological Monographs 23:41-78.

7Brown J. R. and J. Thorpe, 2008. Rangeland forage availability and management in times of drought – A case study of pastoralists in Afar, Ethiopia. Journal of Arid Environments 139:67-75.

8Vilchez, S., Manzanera, M, 2011. Biotechnological uses of desiccation-tolerant microorganisms for the rhizoremediation of soils subjected to seasonal drought. Applied Microbiology and Biotechnology 91:1297-1304.

9Brown J. R. and J. Thorpe, 2008. Responding Rationally to Uncertainty. Rangelands 30(3):3-6.

10Bork, E., et al., 2012. Seasonal Patterns of Forage Availability in the Fescue Grasslands Under Contrasting Grazing Histories. Rangeland Ecology and Management. 65:47-55.

11Veen, G. F., et al., 2008. Influence of grazing and fire frequency on small-scale plant community structure and resource variability in native tallgrass prairie. Oikos 117:859-866.

12Fortin, D. et al. 2003. Foraging Ecology of Bison at the Landscape and Plant Community Levels: The Applicability of Energy Maximization Principles. Oecologia 134(2):219-227.

13Bergmann, G. T., et al. 2015. Seasonal Shifts in Diet and Gut Microbiota of the American Bison (Bison bison). PLOS ONE | DOI:10.1371/journal.pone.0142409.

14Hebblewhite, M., et al., 2008. A Multi-Scale Test of the Forage Maturation Hypothesis in a Partially Migratory Ungulate Population. Ecological Monographs 78(2):141-166.

15Cid, M. S., et al. 1991. Vegetational Responses of a Mixed-Grass Prairie Site following Exclusion of Prairie Dogs and Bison. Society of Range Management 44(2):100-105.

16Krueger, K., 1986. Feeding Relationships Among Bison, Pronghorn, and Prairie Dogs: An Experimental Analysis. Ecological Society of America 67(3):760-770.

17Pineiro, G., et al. 2010. An Assessment of Grazing Effects on Soil Carbon Stocks in Grasslands. Rangeland Ecology and Management 63:000–000 | January 2010 | DOI: 10.2111/08-255.1.

18Stringham, T. K., et al., 2003. State and transition modeling: An ecological process approach. Journal of Range Management 56:106-113.

19Marlow C.B., et al. 2014. National Bison Range Habitat Condition Assessment. Animal and Range Science Department, Montana State University.

20USDA NRCS, 2006. Plant Guide. http://plants.usda.gov/plantguide.

21Hejda, M., et al. 2009. Impact of invasive plants on the species richness, diversity and composition of invaded communities. Journal of Ecology 97:393-403.

22Mueggler, W. F. 1974. Rate and Pattern of Vigor Recovery in Idaho Fescue and Bluebunch Wheatgrass. Journal of Range Management. 28(3):198-204.

23Manier D.J. and N.T. Hobbs 2006. Large herbivores influence the composition and diversity of shrub-steppe  communities in the Rocky Mountains, USA. Oecologia 146:641-651.