Macroecological Theory and Mountain Ecosystem Biodiversity Patterns

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Research Primer

Background

Macroecology asks how patterns of biological diversity, abundance, and energy use scale across space, time, and habitat. Rather than focusing on a single species in a single place, macroecologists look for general laws that hold across forests, meadows, deserts, and tundra. In the mountains around the Rocky Mountain Biological Laboratory (RMBL) in Gothic, Colorado, this perspective has been especially powerful. Steep elevation gradients, sharp boundaries between meadow and sagebrush, and decades of long-term experimental warming make the Gunnison Basin a natural laboratory for testing whether broad ecological theories can predict how mountain communities are organized and how they respond to change.

A few key concepts run through the work that follows. The species-area relationship describes how the number of species found in a survey grows with the size of the area sampled, often following a simple power law. The maximum entropy theory of ecology (METE) is a mathematical framework that predicts species-area curves, the distribution of how many individuals each species has, and the distribution of metabolic rates among individuals using only a few community-level totals (area, total abundance, total species richness, and total energy use). Closely related is the idea of upscaling: using theory to extrapolate from a handful of small plots to whole landscapes. Plant functional groups (for example, deep-rooted forbs versus shallow-rooted forbs, or shrubs versus grasses) are a way of grouping species by their ecological roles so that community-level changes become tractable.

Finally, mountain ecosystems do not just respond to climate; they feed back on it. Climate-ecosystem feedbacks emerge when warming changes which plants dominate, how much carbon their litter holds, and how quickly soils release CO2. Litter quality (its carbon-to-nitrogen ratio and lignin content) controls how fast dead plant material decomposes, linking community shifts to soil carbon storage. Together, these concepts let researchers move from single plots to whole biomes, and from this year's flowers to century-scale carbon budgets.

Foundational work

The field has two strong roots at RMBL. The first is a long-running infrared warming experiment in a montane meadow above Gothic, where overhead heaters have continuously raised air temperature for decades. Early reports showed that this modest heat addition advanced snowmelt by about a week, raised summer soil temperatures by up to 3 degrees C, and dried soils by up to 25 percent, with the strongest effects in already-dry, sparsely vegetated zones (Harte et al., 1995). This work, together with a broader conceptual framework for warming experiments (Shaver et al., 2000), established that climate impacts in mountain meadows are mediated by snow timing and soil moisture, not just temperature alone.

The second root is the development of general macroecological theory. Harte and Kinzig (Harte & Kinzig, 1997) showed that species-area relationships imply predictable patterns of endemism and species turnover across landscapes. This line of work matured into METE, which uses maximum entropy inference to derive species-area curves, abundance distributions, and energy distributions from a small number of community totals (Harte et al., 2009); (Harte & Newman, 2014). A complementary essay argued that ecology advances fastest when it builds efficient, first-principles theories that make many predictions from few assumptions (Marquet & Harte, 2014).

Key findings

The RMBL warming experiment has produced a remarkably consistent picture of how a montane meadow reorganizes under climate stress. Heating advances snowmelt and dries the soil, which in turn shifts the plant community from forbs and grasses toward woody shrubs, especially sagebrush (Harte et al., 1995). This dominance shift drives substantial soil carbon loss: a ten-year heating experiment reduced soil organic matter by roughly 200 g C per square meter, largely because shrub-dominated communities produce less and lower-quality litter (pub_id:1933). Litter chemistry, particularly the lignin-to-nitrogen ratio, turned out to be a stronger control on decomposition than the direct temperature effects of warming (Shaw & Harte, 2001). The cascade extends to other organisms: plants in earlier-melting plots suffered more damage from a wider range of pathogens and herbivores (Roy et al., 2004), and continued warming has driven at least one alpine forb to local extinction in a heated plot (pub_id:728).

These mountain results connect to global patterns. Across biomes from desert to forest, primary production tracks precipitation and converges to a common maximum efficiency in the driest years (Huxman et al., 2004). In tundra worldwide, plot-scale vegetation change matches recent summer warming (Elmendorf et al., 2012), and community plant height has risen with warming even as other traits lag (Bjorkman et al., 2018). The RMBL findings on shrub expansion, altered carbon cycling, and shifts in functional traits fit squarely within these biome-wide trends.

On the theoretical side, METE has had striking empirical successes. A universal species-area curve collapses data from many ecosystems onto a single shape determined by average abundance per species (Harte et al., 2009), and the same framework can be used to estimate over twenty thousand arthropod species in a tropical reserve from a dozen tiny plots (pub_id:1002). METE also predicts the distribution of metabolic rates across individuals (Harte & Newman, 2014), and an integrated equation of state now links species richness, abundance, biomass, and energy flow with high accuracy across forty-two datasets (Harte et al., 2022). Importantly, in the relatively undisturbed parts of the Gunnison meadow, both heated and control plots followed METE predictions, suggesting the theory captures something fundamental about how communities organize themselves (pub_id:1399).

Current frontier

Research since 2020 has shifted from describing patterns to understanding why theory sometimes fails. A six-year study of a stressed alpine plant community showed that as mortality climbed and recruitment fell, both the species-area relationship and the abundance distribution drifted further from METE's static predictions (Franzman et al., 2021). This motivated DynaMETE, a hybrid framework that adds explicit demographic mechanisms to maximum entropy inference, allowing predictions for ecosystems undergoing disturbance rather than only those at equilibrium (Harte et al., 2021).

In parallel, recent experiments at RMBL are probing the belowground and microclimate dimensions of mountain change. Long-term warming has been shown to decouple plants from their fungal partners, reducing root-associated symbionts by 17 to 20 percent while boosting free-living soil saprophytes, and pushing plant communities toward more conservative, woody-dominated traits (Souza et al., 2026). Studies of soil carbon under combined warming, snowmelt advance, and species removal show carbon redistributing among soil layers rather than disappearing outright, a more nuanced picture than early experiments suggested (pub_id:262). Fine-scale microclimate work across the Gunnison Valley, meanwhile, finds that near-surface conditions are often more extreme than regional climate models suggest, with elevation and canopy cover only partially buffering organisms from temperature extremes (Martineau, 2020).

Open questions

Major questions remain. How can macroecological theory be extended to predict not just static patterns but the trajectories of communities undergoing rapid change, and how well will DynaMETE-style frameworks generalize beyond the Gunnison meadow? When warming decouples plants from soil microbes and shifts dominance from forbs to shrubs, are the resulting carbon losses transient or permanent, and which functional groups will compensate for the species being lost? How tightly does microclimate at the scale an organism actually experiences track the regional climate signals used in most projections, and what does that mismatch mean for forecasts of range shifts and local extinction? Answering these questions over the next decade will likely require tighter integration of long-term experiments, landscape-scale microclimate sensor networks, and theory that explicitly links demography, energy flow, and biogeochemistry.

References

Bjorkman, A. D., et al. (2018). Plant functional trait change across a warming tundra biome. Nature. →

Climate Warming Drives Local Extinction: Evidence from Observation and Experimentation (2018). →

Elmendorf, S. C., et al. (2012). Plot-scale evidence of tundra vegetation change and links to recent summer warming. Nature Climate Change. →

Franzman, J., et al. (2021). Shifting macroecological patterns and static theory failure in a stressed alpine plant community. Ecosphere. →

Harte, J., & Kinzig, A. P. (1997). On the implications of species-area relationships for endemism, spatial turnover, and food web patterns. Oikos. →

Harte, J., & Newman, E. A. (2014). Maximum information entropy: a foundation for ecological theory. Trends in Ecology and Evolution. →

Harte, J., et al. (2022). An equation of state unifies diversity, productivity, abundance and biomass. Communications Biology. →

Harte, J., Smith, A. B., & Storch, D. (2009). Biodiversity scales from plots to biomes with a universal species-area curve. Ecology Letters. →

Harte, J., Torn, M. S., Chang, F.-R., Feifarek, B., Kinzig, A. P., Shaw, R., & Shen, K. (1995). Global warming and soil microclimate: results from a meadow-warming experiment. Ecological Applications. →

Harte, J., Umemura, K., & Brush, M. (2021). DynaMETE: a hybrid MaxEnt-plus-mechanism theory of dynamic macroecology. Ecology Letters. →

Huxman, T. E., et al. (2004). Convergence across biomes to a common rain-use efficiency. Nature. →

Inferring Regional-Scale Species Diversity from Small-Plot Censuses (2015). →

Marquet, P. A., & Harte, J. (2014). On theory in ecology. BioScience. →

Martineau, A. (2020). Predictors and Strength of Microclimate Buffering in the Gunnison Valley. →

Plant community composition mediates both large transient decline and predicted long-term recovery of soil carbon under climate warming (2002). →

Roy, B. A., Gusewell, S., & Harte, J. (2004). Response of plant pathogens and herbivores to a warming experiment. Ecology. →

Shaver, G. R., et al. (2000). Global warming and terrestrial ecosystems: a conceptual framework for analysis. BioScience. →

Shaw, M. R., & Harte, J. (2001). Response of nitrogen cycling to simulated climate change: differential responses along a subalpine ecotone. Global Change Biology. →

Souza, L., et al. (2026). Experimental warming decouples plant-fungal symbiont interactions and leads to a more conservative ecosystem. PNAS. →

Testing the maximum entropy theory of ecology in the warming meadow (2011). →

Waldron, K. (2023). Exploring the impact of climate change on soil carbon storage in montane meadows. →

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