Module 4

Deserts

Deserts are regions where potential evapotranspiration exceeds precipitation (P/PET < 0.2 for hyperarid to ~0.5 semi-arid). They cover ~33% of Earth’s land surface. Far from barren, deserts host organisms whose physiological solutions to desiccation — CAM photosynthesis, metabolic water, deep taproots, seed dormancy — rival any engineering achievement.

1. Four Formation Mechanisms

Subtropical high-pressure: Hadley-cell descending air at 15–30° latitude produces persistent subsidence and cloud-free skies. Produces the Sahara, Arabian, Kalahari, Australian, Atacama-adjacent zones. The largest deserts on Earth are of this type.
Rain-shadow: moist maritime air rises on windward slopes of mountain ranges, precipitates on the ascent, and descends dry on the leeward side. Mojave (Sierra Nevada rain shadow), Patagonian (Andes rain shadow), Great Basin (Sierra Nevada + Cascades).
Cold-current coastal: cold upwelled ocean waters stabilise the overlying air and suppress convection. The world’s driest deserts — Atacama, Namib — form by this mechanism. Rainfall in the Atacama averages <1 mm/yr in interior locations.
Continental interior: distance from ocean moisture sources. Gobi desert, central Asian steppes, Great Basin.

2. CAM Photosynthesis

Crassulacean Acid Metabolism evolved convergently in >400 plant families including Cactaceae, Agavaceae, Crassulaceae, Bromeliaceae, and many orchids. Stomata open only at night (when evaporative demand is low); PEP carboxylase fixes CO₂ as malate, stored in large vacuoles:

\[ \text{Night:}\ \text{CO}_2 + \text{PEP} \xrightarrow{\text{PEPcase}} \text{malate (vacuole)} \]

\[ \text{Day:}\ \text{malate} \xrightarrow{\text{NADP-MDH}} \text{CO}_2 + \text{Calvin cycle (stomata closed)} \]

Water-use efficiency reaches 10× that of C3at the cost of lower absolute carbon gain — a classic speed/efficiency trade-off. CAM species are dominant in severe deserts and in epiphytic habitats (many tropical orchids) where water supply is irregular.

Simulation: CAM Gas Exchange

Python

script.py51 lines

import numpy as np, matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

# CAM cycle: stomata open at night, closed by day
hours = np.arange(0, 24)
# Light
light = np.clip(np.sin(np.pi * (hours - 6) / 12), 0, 1)
# Stomatal conductance (C3 follows light; CAM opens opposite)
gs_C3 = 0.9 * light + 0.05
gs_CAM = 0.9 * (1 - light) + 0.05
# Malate accumulation in CAM: rises at night, falls during day
malate = np.zeros(24)
for h in range(24):
    if h > 18 or h < 6: malate[h] = malate[h-1] + 0.08
    else: malate[h] = malate[h-1] - 0.08
malate = np.clip(malate, 0, 1)

fig, axes = plt.subplots(1, 3, figsize=(17, 5), facecolor='#0a1a0d')
for ax in axes:
    ax.set_facecolor('#111e14'); ax.tick_params(colors='#bbf7d0')
    for s in ax.spines.values(): s.set_color('#334155')
    ax.grid(True, color='#334155', alpha=0.3)

axes[0].plot(hours, light, color='#fbbf24', lw=2.5, label='PAR')
axes[0].plot(hours, gs_C3, color='#60a5fa', lw=2.5, label='C3 stomata')
axes[0].plot(hours, gs_CAM, color='#34d399', lw=2.5, label='CAM stomata')
axes[0].set_xlabel('Hour', color='#bbf7d0')
axes[0].set_ylabel('Relative', color='#bbf7d0')
axes[0].set_title('CAM: night opening, day closure',
                  color='#fde68a', fontweight='bold')
axes[0].legend(facecolor='#1e293b', edgecolor='#334155', labelcolor='#cbd5e1')

axes[1].plot(hours, malate, color='#a78bfa', lw=2.5)
axes[1].set_xlabel('Hour', color='#bbf7d0')
axes[1].set_ylabel('Vacuolar malate (mM)', color='#bbf7d0')
axes[1].set_title('Malate accumulates at night, depletes by day',
                  color='#fde68a', fontweight='bold')

# WUE comparison
labels = ['C3 (wheat)', 'C4 (sugarcane)', 'CAM (cactus)']
wue = [3.0, 6.0, 30.0]
axes[2].bar(labels, wue, color=['#60a5fa','#f59e0b','#34d399'], edgecolor='#bbf7d0')
axes[2].set_ylabel('WUE (mmol CO2 / mol H2O)', color='#bbf7d0')
axes[2].set_title('CAM: 10x C3 water-use efficiency',
                  color='#fde68a', fontweight='bold')

plt.tight_layout()
plt.savefig('output.png', dpi=120, bbox_inches='tight', facecolor='#0a1a0d')
print('CAM: PEPcase fixes CO2 as malate at night; Calvin cycle runs in daylight with stomata closed')
print('Stylized for cacti (Cactaceae), agaves, pineapple, many orchids, epiphytic bromeliads')

Click Run to execute the Python code

Code will be executed with Python 3 on the server

3. Animal Adaptations

Adaptation	Plant examples	Animal examples
Water storage (succulent)	Cacti, Euphorbias	Sonoran desert toad
Deep roots	Mesquite (50 m taproots)	—
Nocturnal activity	Moonflower	Kangaroo rat, fennec fox, scorpions
Metabolic water	—	Kangaroo rat (0 free-water intake; camel; oryx)
Waxy cuticle / CAM	Agave, Aloe	Reptile epidermal lipids
Seed dormancy	Desert ephemerals (100-yr viability)	Fairy-shrimp cryptobiosis

4. Desertification

Human-accelerated desertification — the expansion of desert-like conditions into non-desert drylands — threatens ~3.6 billion people. The Sahel (southern edge of Sahara) is the most-studied case: drought + overgrazing + land-use change reduced vegetative cover ~30% between 1950 and 1980. Since 1980, increased rainfall and afforestation (Great Green Wall) have produced partial greening. UNCCD 2015 estimates 40% of Earth’s land is affected by some form of degradation.

Key References

• Schmidt-Nielsen, K. (1964). Desert Animals: Physiological Problems of Heat and Water. Oxford UP.

• Nobel, P. S. (1991). Physicochemical and Environmental Plant Physiology. Academic Press.

• Reynolds, J. F. et al. (2007). “Global desertification: building a science for dryland development.” Science, 316, 847–851.

• Winter, K. & Smith, J. A. C. (1996). Crassulacean Acid Metabolism. Springer.

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