Module 8

Global Comparison

A quantitative synthesis across all biomes — net primary productivity, area, carbon storage, biodiversity, and climate-change exposure — in a single reference view. Values are representative; see per-biome modules for full sourcing.

1. NPP, Area & Carbon Stock

Python

script.py45 lines

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

biomes = ['Coral reef','Tropical rainforest','Tropical savanna','Temperate forest',
          'Grassland','Boreal forest','Tundra','Open ocean','Desert']
npp  = [2500, 2200, 900, 700, 400, 360, 140, 125, 45]
area = [0.6, 17, 15, 11, 37, 17, 8, 332, 55]    # M km^2
c_pool = [2, 340, 330, 160, 300, 550, 400, 1000, 50]  # soil+biomass C, stylised Gt

fig, axes = plt.subplots(1, 3, figsize=(17, 6), 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, axis='x')

ax = axes[0]
idx = np.argsort(npp)[::-1]
ax.barh([biomes[i] for i in idx], [npp[i] for i in idx],
        color='#34d399', edgecolor='#bbf7d0')
ax.invert_yaxis()
ax.set_xlabel('NPP (g C m-2 yr-1)', color='#bbf7d0')
ax.set_title('Primary productivity', color='#fde68a', fontweight='bold')

ax = axes[1]
idx = np.argsort(area)[::-1]
ax.barh([biomes[i] for i in idx], [area[i] for i in idx],
        color='#fbbf24', edgecolor='#bbf7d0')
ax.invert_yaxis()
ax.set_xlabel('Area (M km^2)', color='#bbf7d0')
ax.set_title('Biome area', color='#fde68a', fontweight='bold')

ax = axes[2]
idx = np.argsort(c_pool)[::-1]
ax.barh([biomes[i] for i in idx], [c_pool[i] for i in idx],
        color='#a78bfa', edgecolor='#bbf7d0')
ax.invert_yaxis()
ax.set_xlabel('Carbon stock (Gt C)', color='#bbf7d0')
ax.set_title('Carbon stock (soil+biomass)', color='#fde68a', fontweight='bold')

plt.tight_layout()
plt.savefig('output.png', dpi=120, bbox_inches='tight', facecolor='#0a1a0d')
print('NPP: coral reef > tropical rainforest >> tundra ~ open ocean >> desert')
print('Area: open ocean > grassland > desert > boreal ~ tropical forest')
print('C stock: oceans largest (deep carbon), boreal soils highest terrestrial')

Click Run to execute the Python code

Code will be executed with Python 3 on the server

2. Comprehensive Summary Table

Biome	Area (M km²)	MAT (°C)	MAP (mm)	NPP	Soil	Vegetation
Tropical rainforest	~17	25–28	2000–4000	2200	Oxisol / Ultisol	Broadleaf evergreen
Temperate forest	~11	5–15	750–1500	600–800	Alfisol / Mollisol	Deciduous hardwoods
Grassland / savanna	~52	10–28	300–1500	400–900	Mollisol / Vertisol	Grasses, forbs
Desert	~55	20–35	<250	45	Aridisol	Succulents, annuals
Boreal forest	~17	−10–5	300–900	360	Spodosol / Histosol	Conifer trees
Tundra	~8	−25–5	50–250	140	Gelisol	Mosses, sedges, shrubs
Mediterranean	~2.5	10–20	300–700	500–800	Alfisol / Entisol	Sclerophyllous shrubs
Freshwater	~2	Variable	Variable	250	Aquic	Aquatic macrophytes
Coral reef	~0.6	23–29 (water)	—	2500	Calcium carbonate	Scleractinian corals
Open ocean	~332	−2–30 (water)	—	125	—	Phytoplankton

NPP in g C m^-2 yr^-1.

3. Climate-Change Projections (RCP8.5 by 2100)

Tropical forest: increased drought frequency; Amazon dieback risk in southeast arc (Nobre 2016).
Temperate forest: poleward range shifts up to ~500 km; increased fire risk; species-range mismatches with interacting pollinators.
Grassland / savanna: bush encroachment in many regions; altered fire regimes; C4-to-C3 shifts under elevated CO₂.
Desert: expansion 4–11%; increased dust storms; Sahelian greening (unusually) with higher CO₂.
Boreal forest: northward expansion (~5–8 km decade^-1); insect outbreaks; severe wildfire seasons.
Tundra: shrubification; 30–60% area reduction by 2100; permafrost-C release.
Aquatic: coral bleaching every 2–3 yr globally; ocean acidification; deoxygenation; polar ocean warming 3°C+.

4. Conservation Status (WWF Global 200)

The WWF’s Global 200 analysis (Olson 2001) identified 233 ecoregions of exceptional biodiversity value across the world’s biomes. Of these, ~73% are either critically endangered, endangered, or vulnerable. Highest-threat biomes: Mediterranean forests (>90% converted), temperate broadleaf forests, and tropical dry forests. Lowest-threat biomes by conversion: tundra, boreal forest (but rapidly warming), deep pelagic.

5. Course Synthesis

Eight modules traced Earth’s major biomes from tropical rainforest through temperate forest, grassland, desert, boreal forest, tundra, and aquatic systems back to a comparative synthesis. The overarching pattern is that two climate variables — temperature and precipitation — predict biome identity worldwide, while secondary drivers (fire, soil, biogeographic history) refine the picture. Every biome is now being reshaped by anthropogenic pressure, most acutely climate change and land-use. Understanding biomes is the prerequisite for understanding what a future Earth’s biosphere will look like.