Chapter 58: Communities and Ecosystems: Ecological Organization on Large Scales

Patterns of Species Richness and Species Diversity

Learning Outcomes

1. Identify the latitudinal gradient of species richness.

2. List and describe three hypotheses for observed patterns of species richness.

3. Core SKILL: Calculate the Shannon diversity index and the effective number of species.

Introduction to Community Ecology

Community ecology focuses on the factors that influence the number of different species in a community, commonly referred to as species richness. A critical observation in ecology is that species richness varies globally along a latitudinal gradient. This pattern shows a general increase in species richness from polar regions to temperate zones, peaking in tropical areas. For example, the species richness among North American birds shows an increase from Arctic Canada to Panama, as depicted in Figure 58.1. This trend is also observed in various taxa, including mammals, amphibians, reptiles, and plants.

Latitudinal Gradient Influence

While the latitudinal gradient is a significant factor in species richness, other influences include topographical variations. Areas with more mountains provide greater habitat diversity, which can elevate species richness. An example is seen in the United States, where the mountainous West boasts a higher bird species richness than the Eastern regions. Additionally, the peninsular effect describes how species richness diminishes with distance from the main landmass.

Figure 58.1

The figure illustrates species richness among North American birds, with contour lines denoting equal numbers of species within given areas. Distinct colors represent incremental changes in bird species richness, emphasizing the marked latitudinal gradient toward the tropics and illustrating high diversity in regions like California, which features extensive topographical and habitat diversity.

Hypotheses for Patterns of Species Richness

Several hypotheses have been proposed to explain the latitudinal gradient in species richness, primarily focusing on three key factors: time, area, and productivity. Importantly, these hypotheses are not mutually exclusive and can interact to influence species richness in various ways.

Species-Time Hypothesis

The species-time hypothesis posits that communities gain species over time. In this context, tropical communities are often more diverse because they are older than temperate communities. This is attributed to historical events, such as the Ice Ages, which periodically decimated species in temperate zones, leading to a younger biodiversity in these regions. Many species in temperate areas have thus had less time to evolve and diversify. The hypothesis suggests that temperate regions have fewer species because their communities are recovering from extinction events caused by glacial activity.

An example supporting this hypothesis comes from research by ecologist H. John Birks, who found a significant correlation between the number of insect species found on various British trees and the length of time those trees had been established since the last Ice Age. By using radiocarbon dating of pollen from lake sediments, Birks established that tree species in Britain had been present for no longer than 13,000 years, correlating tree age with insect species diversity.

Figure 58.2a

This figure displays the relationship between insect species richness on British trees and the duration of habitation since the last Ice Age.

Limitations of the Species-Time Hypothesis

Despite its insights regarding terrestrial organisms, the species-time hypothesis faces limitations in explaining marine biodiversity. For instance, marine organisms have the potential to redistribute quickly following glaciation, but a contrast in latitudinal gradients of species richness persists in marine habitats.

Species-Area Hypothesis

The species-area hypothesis suggests larger areas support a greater number of species due to higher population capacities and habitat diversity. Ecologist Donald Strong's studies in 1974 demonstrated that insect richness on British trees exhibited a stronger correlation with the area geographic range of tree species compared to the time of habitation since the last Ice Age. This relationship fosters the concept known as the species-area effect, where species numbers increase with area size.

However, the species-area hypothesis cannot adequately account for situations where regions with vast areas, such as Asia, exhibit low species richness, nor can it explain low richness in the tundra biome or open oceans, which are substantial in size but lacking biodiversity.

Species-Productivity Hypothesis

The species-productivity hypothesis indicates that higher plant productivity leads to increased species richness. In ecological terms, productivity refers to the mass of plant material generated over time. Enhanced plant productivity results in greater numbers of herbivores, which in turn fosters an increase in predator, parasite, and scavenger species. Several environmental factors, including temperature and rainfall, influence plant productivity. For example, research conducted by David Currie in 1987 suggested that tree species richness in North America is best predicted by evapotranspiration rates, influenced by solar energy and moisture levels.

Figure 58.3

Figure 58.3 illustrates that tree species richness is positively correlated to evapotranspiration rates, highest in the southeastern regions of North America, which are warm and moist.

Shannon Diversity Index

As discussions of species richness evolve, it becomes essential for ecologists to assess not only the total number of species within a community but their distribution and relative abundance. For instance, consider two hypothetical communities, A and B, each with two species and a total of 100 individuals:

• Community A: 99 individuals of species 1, 1 individual of species 2.

• Community B: 50 individuals of species 1, 50 individuals of species 2.

In these examples, both communities exhibit the same species richness. However, Community B demonstrates greater diversity due to the more even distribution of individuals across species. To quantify this, ecologists use diversity indices, with the Shannon diversity index ($H_s$) being the most widely adopted.

Calculation of the Shannon Diversity Index

The Shannon diversity index is formulated as:
$H<em>s = -\sum P</em>i \ln P<em>i$ where $Pi$ represents the proportion of individuals corresponding to species i in the community. The natural logarithm ($ ext{ln}$) is utilized in the calculation, and the summation symbol ($\Sigma$) indicates the sum across all species.

Example Calculation

To illustrate the calculation, consider a hypothetical community containing 5 species comprising a total of 100 individuals. The calculations follow:

• Species 1: 50 individuals, $P1 = 50/100 = 0.5$, $ ext{ln}(0.5) = -0.693$, $P1 \ln P_1 = -0.347$.

• Species 2: 30 individuals, $P2 = 0.3$, $ ext{ln}(0.3) = -1.204$, $P2 \ln P_2 = -0.361$.

• Species 3: 10 individuals, $P3 = 0.1$, $ ext{ln}(0.1) = -2.302$, $P3 \ln P_3 = -0.230$.

• Species 4: 9 individuals, $P4 = 0.09$, $ ext{ln}(0.09) = -2.408$, $P4 \ln P_4 = -0.217$.

• Species 5: 1 individual, $P5 = 0.01$, $ ext{ln}(0.01) = -4.605$, $P5 \ln P_5 = -0.046$.

The total sum of these calculations results in:
$H<em>s = -\sum P</em>i \ln P_i = 1.201.$

Interpreting the Shannon Diversity Index

Values generated from the Shannon diversity index typically range between 1.5 and 3.5, with higher index values denoting greater community diversity. A challenge in comparing diversity indices arises, as they may yield values that can misleadingly suggest variation in diversity.

Effective Number of Species

To enhance comparative analysis, researchers may calculate the effective number of species, which translates diversity index values into equivalent whole numbers of species. For the Shannon diversity index, the effective number of species is derived by taking the exponential function of the index value. For instance, if $H_s = 1.609$, then the effective number of species is:
$e^{1.609} = 5.0,$
paralleling the actual count of species in the community.

Conversely, when $H_s = 1.201$, the effective number of species evaluates to:
$e^{1.201} = 3.323,$
indicating variation where a community with an effective number of species of 5.0 proves to be approximately 50.5% more diverse than one with 3.323 species.

Species Richness and Community Stability

Learning Outcome

1. Describe the diversity-stability hypothesis, and explain the evidence supporting it.

Community Stability

A community is often perceived as stable when there is little to no detectible change in the number of species and their abundances over a specified time period. Such stability can also be described as the community being in equilibrium. Community stability is a fundamental concept for ecologists, as a decline in stability over time may signal potential problems within the ecosystem. For instance, the introduction of an invasive species, such as the zebra mussel (Dreissena polymorpha), which has proliferated in the Great Lakes, can lead to undesirable reductions in the populations of invertebrate species inhabiting that region.

Diversity-Stability Hypothesis

Definition and Origin

The diversity-stability hypothesis posits that species-rich communities exhibit greater stability than those with fewer species. This concept was primarily advocated by ecologist Charles Elton in the 1950s, who proposed that a disturbance in a community with high species richness would be buffered by the large number of interacting species present. Thus, the effects of the disturbance would not be as detrimental as in a community with fewer species.

Example of Elton's Hypothesis

For example, if an introduced predator were to invade a species-poor community, it would lead to higher extinction rates compared to its impact on a species-rich community, where the predator’s effect would be mitigated through interactions with a diverse range of species. Elton argued that pest outbreaks are often observed in cultivated or disturbed land, which typically comprises species-poor communities.

Counterarguments

Despite Elton’s hypothesis, some ecologists have refuted the straightforward association between diversity and stability. They presented instances of introduced species that have become pests even in species-rich environments, as seen with rabbits in Australia and pigs in North America. These ecologists contend that the outbreaks of pests in disturbed or cultivated land stem from the absence of natural enemies among introduced species, rather than from the lower number of native species. Conversely, native species and their natural predators have co-evolved, maintaining a balanced predator-prey dynamic that prevents native populations, such as rabbits in Europe and North America, from reaching pest proportions.

Empirical Evidence from Field Studies

Tilman's Study

In 1996, David Tilman investigated the relationship between species richness and community stability through an extensive study that lasted 11 years, involving 207 grassland plots across Minnesota that exhibited varied levels of species richness. Each year, the biomass of every plant species within each plot was meticulously measured.

Coefficient of Variation

A statistical measure known as the coefficient of variation was employed to evaluate the degree of variability in biomass from year to year. The coefficient of variation is defined as the ratio of the standard deviation to the mean. A lower coefficient of variation signifies greater community stability.

Findings

Tilman's results indicated that year-to-year variability in plant community biomass was significantly diminished in plots with higher species richness, thus corroborating the diversity-stability hypothesis that greater species richness positively impacts community stability.

Figure: Biomass variation versus species richness from Tilman's 11-year study illustrated that sites with higher species richness showed reduced variation in community biomass.

Core Concept: Community Stability

Community stability encompasses not only the capacity to withstand disturbances but also the ability to recover from changes induced by such disturbances. For instance, in Tilman's observations, it was suggested that species-rich communities are more inclined to harbor disturbance-resistant species. When a disturbance occurs, these species can flourish and offset the loss of species vulnerable to disturbances.

Example of Disturbance Recovery

An instance of this concept can be observed in scenarios where climate change-induced conditions, such as drought, affect competitively dominant species that prosper under usual conditions. Consequently, drought-resistant species can increase in biomass, effectively replacing the lost sensitive species and stabilizing the total biomass of the community.

Long-Term Community Responses

While ecologists recognize a correlation between species richness and community stability, it is important to acknowledge that communities may experience substantial disturbances over extended periods. The resultant shifts in community composition and structure following a significant disturbance are predictable and are referred to as succession, which will be addressed in a subsequent section.

58.3 Succession: Community Change

Learning Outcomes

1. Distinguish between primary and secondary succession.

2. Compare and contrast facilitation, inhibition, and tolerance as mechanisms of succession.

Definition of Succession

Succession describes the gradual and continuous change in species composition of a community following a disturbance.

Primary Succession

Definition

Primary succession refers to succession that occurs on a newly exposed site that has no biological legacy, meaning it lacks plants, animals, or microbes.

Examples

• Bare ground created by volcanic eruptions.

• Sediment produced by glacial retreat.

Processes Involved

• In primary succession on land, plants are required to build soil.

• This process can take a long time, often hundreds of years due to the need for soil development.

Current Status

Only a small proportion of Earth's surface is currently undergoing primary succession. Examples include:

• New lava flows in Indonesia and Hawaii.

• Newly created coastal sand dunes.

Secondary Succession

Definition

Secondary succession occurs on a site that has previously supported life but has been disturbed by events such as fire, tornado, hurricane, flood, or farming.

Conditions

• Soil often remains intact.

• Disturbances may not kill all native species; some plants and soil organisms persist.

Example of Secondary Succession

• Abandoned farmland: Following cessation of farming, vegetation patterns may differ from those developed after primary succession.

• Plowing, fertilizers, herbicides, and pesticides may alter the soil, allowing nitrogen-rich species to proliferate more quickly than they would in primary succession areas.

Role of Disturbance

• Fire is a common precursor to secondary succession.

• Post-fire soil can be enriched with ashes or decomposing materials promoting fast-growing herbaceous plants that require high light exposure.

• Over time, slower-growing, shade-tolerant trees begin to colonize the area, eventually outcompeting earlier successional species.

Importance of Fire in Ecosystems

• Many plant species depend on periodic fires to maintain suitable habitats, contributing to species diversity.

• A mosaic of burned and unburned areas promotes greater biodiversity compared to a continuous unburned area.

Theoretical Framework of Succession

Frederic Clements and Successional Theory

• Frederic Clements is often recognized as the founder of successional theory in the early 20th century.

• Clements suggested that succession proceeds through distinct stages leading to a climax community.

• He emphasized a process termed facilitation, where earlier species create favorable conditions for later species.

• Although disturbances can reverse a community's succession stage, the general direction is towards increased complexity and stability.

Mechanisms of Succession

Facilitation

Definition

Facilitation posits that each colonizing species alters the environment in a way that makes it more favorable for subsequent species.

Process Overview

• Each species, as it colonizes, modifies local conditions, making them better suited for successive species, leading to a climax community.

Example of Facilitation

• Succession on sand dunes:

  • Formation of dunes begins with sand blown inland by wind, creating new habitats.

  • Early colonizers (pioneer species like beach grass, Ammophila breviligulata) stabilize the dunes and contribute organic matter, improving conditions for later successional species.

  • As succession progresses, mixed-species pine forests may develop after several hundred years.

Inhibition

Definition

Inhibition suggests that early colonists can prevent later species from colonizing.

Example of Inhibition

• In New Jersey farm fields, litter from early successional species like Setaria faberi inhibits the establishment of later species like Erigeron annuus.

  • The presence of litter blocks germination and growth of later arrivals.

Relevance in Marine Environments

• In marine intertidal zones, where space is limited, early colonizers such as Ulva can prevent colonization by later species.

• Experiments by ecologist Wayne Sousa revealed that when early species like Ulva were removed, later colonizers could establish more quickly, indicating inhibition is significant in such systems.

Tolerance

Definition

Tolerance implies that early colonists neither facilitate nor inhibit later colonists and that succession proceeds in an orderly manner based on species’ tolerances to competition.

Research Basis

• Proposed by Connell and Slatyer in 1977, supported by Frank Egler's studies in the 1950s.

  • Egler showcased that the species capable of germination or regeneration first dictates the sequence of succession, highlighting the role of pre-existing seeds and roots in the soil.

Competitive Dynamics

• Species with lower competition tolerance thrive early on when resources are abundant, while more competition-tolerant species appear later.

Comparison of Succession Models

Key Distinctions

• Facilitation: Early species enhance conditions for latter species.

• Inhibition: Early species hinder the establishment of later species.

• Tolerance: Early colonizers neither help nor hinder subsequent colonizers.

Visual Representation

Figure 58.8 illustrates the three models, highlighting how species interactions in succession differ:

• Facilitation Model (A): The previous species assists the next in replacement.

• Inhibition Model (B): Previous species inhibits new colonization.

• Tolerance Model (C): Fresh colonizers are neither aided nor disrupted by existing species.

These models collectively provide insight into the complexity and dynamics of ecological succession.

58.4 Island Biogeography

Learning Outcomes

1. CoreSKILL: Interpret a graph illustrating the equilibrium model of island biogeography.

2. List the three predictions of the model and discuss how well the evidence supports each one.

Introduction to Island Biogeography

In newly formed habitats such as volcanic islands, succession may be influenced not only by the concepts of facilitation, inhibition, and tolerance but also by the ability of species from neighboring areas, such as a mainland, to colonize isolated areas, such as an island. In this context, species richness is affected by two key factors:

• The distance of isolated habitats from a source of potential colonists (e.g., mainland species)

• The size of the areas to be colonized.

In the 1960s, ecologists Robert MacArthur and E.O. Wilson developed a comprehensive model to explain the process of succession on new islands. This model, known as the equilibrium model of island biogeography, posits that the number of species on an island tends towards an equilibrium number determined by the balance between two primary factors:

1. Immigration rates of new species

2. Extinction rates of existing species.

The model has been applied extensively not only to newly formed oceanic islands but also to virtual islands, such as:

• Mountains surrounded by deserts

• Lakes surrounded by dry land

• Conservation areas surrounded by agricultural land or urban landscapes.

This section aims to explore island biogeography and evaluate the empirical support for the predictions made by the model.

The Island Biogeography Model

The equilibrium model of island biogeography proposes that:

• Species repeatedly colonize an island and can either thrive or go extinct.

• The rate of immigration of new species is highest when the island is uninhabited. As more species accumulate on the island, the immigration rate decreases since subsequent arrivals are more likely to represent species already present.

• The rate of extinction initially remains low after colonization because few species are present and many have large populations.

• As new species are added, the population sizes of some species diminish, increasing their risk of extinction.

Over time, the number of species stabilizes around an equilibrium value, denoted as S, where the rates of immigration and extinction balance. Even though species may continue to arrive and become extinct, the total number of species (S) remains relatively constant.

Graphical Representation of the Model

MacArthur and Wilson hypothesized that when plotted graphically, both the immigration and extinction rates would be represented as curves due to several factors:

• Immigration Curve:
  Species arrive at islands at varying rates; some species like those with efficient seed-dispersal mechanisms and winged animals colonize rapidly, while others take longer to arrive. This results in a steep initial immigration curve that flattens as more species occupy the island.

• Extinction Curve:
  The extinction rate increases due to heightened competition as more species occupy the island, leading to an accelerating rate of extinction.

The result is visualized in the graphs shown in Figure 58.9a and Figure 58.9b where:

• Part (a) shows the equilibrium number of species (S) influenced by immigration and extinction rates.

• Part (b) illustrates how the equilibrium number (S) varies with island size and proximity to the mainland.

  • Increased distance from the mainland decreases immigration rates.

  • Increased island area decreases extinction rates.

Predictions of the Equilibrium Model

1. Species-Area Relationships

The species-area effect states that the number of species should increase with the area of the island because:

• Larger islands have larger population sizes, which are inherently less susceptible to extinction.

• This prediction is quantitatively supported by studies including analyses conducted in the West Indies, where ecologists Robert Ricklefs and Irby Lovette examined 19 islands varying in size from 13 to 1510 km² and found a positive correlation between area and species richness.

2. Species-Distance Relationships

This prediction states that the number of species decreases as the distance from the mainland increases. MacArthur and Wilson’s studies, particularly involving lowland forest bird species in Polynesia, showed that:

• The number of species correlated with proximity to New Guinea, a source pool for many bird species.

• As distance from New Guinea increased, the percentage of bird species found on nearby islands decreased significantly, corroborating the prediction.

3. Species Turnover

Species turnover refers to the replacement of species over time within a given habitat. This prediction suggests that:

• While the total number of species might remain constant, the identity of species should show considerable variation over time.

• Although turnover analyses historically indicated low rates (less than 1% per year or less than one species per year), indicating turnover is primarily composed of transient immigrants that do not establish, more recent research suggests turnover may be even lower.

This low turnover rate implies that colonization patterns are not random; specific species tend to be the first to colonize, followed by others in the same sequence, thus providing limited support for the third prediction.

Applications of the Model

The principles derived from the island biogeography model have practical applications in conservation biology, particularly in the design of wildlife preserves. Wildlife preserves can be conceptualized as islands amid human-modified landscapes (agricultural fields, urban areas), where understanding species interactions, immigration, and extinction dynamics can inform better conservation strategies. The relevance of these concepts will be elaborated upon in Chapter 60.

Food Webs and Energy Flow

Learning Outcomes

1. Compare and Contrast Food Chains and Food Webs: Identify and differentiate between primary producers, and primary, secondary, and tertiary consumers.

2. Core Skill: Calculate the efficiency of consumers as energy transformers through two methodologies.

3. Types of Ecological Pyramids: List and describe various ecological pyramids.

Overview of Ecosystem Ecology

Ecosystem ecology is concerned with analyzing the movement of energy and nutrients among organisms and their communities. It has been shown that key factors affecting species richness include the amount of available energy and the complex feeding relationships between organisms. These relationships are often illustrated through food chains and food webs.

Food Chains

A food chain is a linear representation of energy flow, demonstrating how energy from one organism is transferred to the next. Each organism in a food chain sees energy flow as unidirectional.

Food Webs

In contrast, a food web is a more intricate depiction of various food chains that are interconnected. It presents a comprehensive view of feeding relationships within an ecosystem, which allows for a better understanding of the complexity of ecosystem interactions. Two significant features of food webs include:

• Chain Length: Refers to the number of steps or links between levels in the food chain.

• Pyramid of Numbers: A structural model illustrating the number of organisms at each trophic level.

Trophic Levels in Food Chains

Each level of a food chain is termed a trophic level. The term "trophic" is derived from the Greek word "trophos," meaning feeder. Different species feed on different trophic levels, with arrows indicating energy flow from one trophic level to the next in a food-chain diagram (See Figure 58.12).

Primary Producers

• Definition: Autotrophs that harvest light or chemical energy to synthesize organic substances.

• Examples: Plants, algae, photosynthetic bacteria.

• Primary producers form the foundational level of all food chains, creating energy-rich organic molecules necessary for survival of other organisms.

Consumers

1. Heterotrophs: Organisms that consume organic molecules to obtain energy. They are categorized as follows:

   • Primary Consumers (Herbivores): Feed directly on primary producers, including most animals, some protists, and certain parasitic plants such as mistletoe.

   • Secondary Consumers (Carnivores): Consume primary consumers.

   • Tertiary Consumers (Secondary Carnivores): Feed on secondary consumers.

Energy Flow and Detritivores

Energy enters a food chain through primary producers via photosynthesis. However, not all energy is utilized; many organisms die before being consumed. Much of the energy from primary producers is unconsumed and instead decomposed, resulting in detritus, which comprises dead organic matter. Detritivores, such as carrion beetles, derive energy from this detritus. Additionally, Decomposers like fungi and bacteria process organic material at all trophic levels, ensuring nutrient cycling.

Complexity of Feeding Relationships

Feeding relationships in nature tend to be intricate. For example, various herbivore species may feed on identical plant species, while herbivores themselves feed on a mix of plant types. In ecosystems like the African savanna, multiple predator species enjoy a wide array of prey, creating a complex food web (See Figure 58.13).

Characteristics of Food Webs

Chain Length

• Definition: The chain length represents the sum of links between trophic levels.

• Example: A food chain consisting of a lion feeding on a zebra and the zebra feeding on grass has a chain length of two.

• Typical Length: Food webs generally feature short chain lengths, often five or fewer links. Factors contributing to this include poor digestibility of prey and energy loss as heat during assimilation, limiting energy transfer efficiency.

Energy Transfer Efficiency

On average, about 10% of the energy remains available between trophic levels as energy depletes through metabolic processes. This aligns with the concept that as one moves up trophic levels, the energy available diminishes significantly (Refer to Figure 58.14).

Measuring Efficiency of Consumers

Ecologists measure the efficiency of energy transformation by consumers through two metrics: production efficiency and trophic-level transfer efficiency.

Production Efficiency

• Definition: The percentage of energy assimilated by an organism that is converted into new biomass.

• Formula:
  $\text{Production Efficiency} = \left( \frac{\text{Net Productivity}}{\text{Assimilation}} \right) \times 100$

• Here, Net Productivity represents the energy stored in biomass over time, while Assimilation indicates total energy intake minus energy lost in feces.

• Invertebrates and microorganisms tend to exhibit higher production efficiencies (10-40%). In contrast, vertebrates generally show lower efficiencies (1-2%) due to greater metabolic expenditure.

Trophic-Level Transfer Efficiency

• Definition: The efficiency at which energy is transferred from one trophic level to the next.

• Formula:
  $\text{Trophic-Level Transfer Efficiency} = \left( \frac{\text{Production at trophic level } n}{\text{Production at trophic level } n-1} \right) \times 100$

• For example, if zooplankton (trophic level n) has a production of 14 g/m² and phytoplankton (trophic level n-1) has 100 g/m², the transfer efficiency is 14%. Trophic-level transfer efficiency averages around 10%.

Ecological Pyramids

Ecological pyramids graphically illustrate the distribution of numbers, biomass, or energy across different trophic levels. Three notable types include:

1. Pyramid of Numbers: Represents the count of individual organisms at each trophic level, typically showing a decline from the base to the apex (as evidenced by studies akin to Figure 58.16a).

2. Pyramid of Biomass: Displays the total mass of living material at each trophic level, potentially mitigating inaccuracies of numbers representing biomass distribution.

3. Pyramid of Energy: Illustrates energy production rates at various trophic levels. This model affirms thermodynamic laws, indicating higher energy production at lower trophic levels (as portrayed in Figure 58.16c).

Despite the general trend, exceptions exist. For example, a single oak tree can support a diversity of herbivorous species, contradicting assumptions about pyramid structure. This leads to concepts like an inverted pyramid of numbers where a single producer sustains numerous consumers.

Core Concept: Within trophic levels, energy is lost to organismal maintenance, while between trophic levels, energy loss occurs due to transfer inefficiencies.

58.6 Biomass Production in Ecosystems

Learning Outcomes

1. Describe the factors that limit primary production in terrestrial and aquatic ecosystems.

2. Explain the fate of most primary production.

3. Describe the distribution of Earth's biomass across different types of organisms and locations.

Overview of Biomass Production in Ecosystems

Biomass production in ecosystems predominantly refers to the output of primary producers, which includes plants, algae, and cyanobacteria. There are two key terms in this context:

• Gross Primary Production (GPP): This is the total amount of carbon fixed during photosynthesis by primary producers in an ecosystem.

• Net Primary Production (NPP): NPP is defined as GPP minus the energy expended during cellular respiration (R) by photosynthetic organisms. The formula is given as:
  $NPP = GPP - R$
  NPP represents the amount of energy available to primary consumers within an ecosystem. Throughout this discussion, unless specified otherwise, the term "primary production" will primarily refer to NPP.

Primary Production in Terrestrial Ecosystems

Determinants of Primary Production

In terrestrial ecosystems, several critical factors influence primary production:

1. Water: Water availability is a significant factor determining primary production, showing an almost linear increase in productivity with annual precipitation, especially in arid regions.

2. Temperature: Temperature impacts production by accelerating or slowing down the metabolic rates of plants.

3. Nutrient Availability: The presence of key nutrients, particularly nitrogen and phosphorus in usable forms, is essential for enhancing primary production. For instance, farmers often apply fertilizers to promote the growth of annual crops.

Case Study: Hudson Bay Experiment

In 1984, ecologists Susan Cargill, Robert Jefferies, and colleagues illustrated how both nitrogen and phosphorus can limit production in salt marsh environments. Their findings revealed:

• Without adequate nitrogen, the addition of phosphorus did not enhance biomass production; nitrogen was identified as the limiting factor.

• Upon adding nitrogen and making it no longer limiting, phosphorus transformed into the limiting factor.

• The greatest increase in production occurred upon the addition of both nutrients, validating Liebig's Law of the Minimum, which posits that the biomass of a species is constrained by the most limited resource.

Primary Production in Aquatic Ecosystems

Factors Limiting Primary Production

In aquatic ecosystems, primary production is largely constrained by:

1. Light Availability: Water absorbs light, limiting depths at which photosynthesis can occur. By 1 meter, over half of the incident solar radiation is absorbed, and only about 5-10% remains by 20 meters.

2. Nutrient Availability: The primary nutrients affecting production are also nitrogen and phosphorus, available in exceedingly low concentrations in marine environments; for example, seawater contains approximately 0.00005% nitrogen compared to 0.5% in soils.

Natural Enrichment through Upwelling

Enrichment of aquatic systems with nutrients usually occurs in areas of upwelling, where nutrient-rich cold water rises to the surface from the ocean floor due to strong currents. Prominent upwelling areas include:

• Antarctic regions

• Coasts of Peru

• California
  This phenomenon supports productive ecosystems rich in marine life.

Nutrient Overload and Algal Blooms

Excess nutrient supply can lead to adverse effects, notably algal blooms. These blooms can create dead zones as bacteria degrade the dead algae, consuming oxygen in the water, resulting in low oxygen areas that threaten aquatic life. An example includes the Gulf of Mexico's dead zone, measuring about 22,000 km² (8,500 mi²), primarily caused by nutrient-rich runoff from the Mississippi River.

Variation in Primary Production Across Earth

Understanding Variability in Production

Grasping which factors limit primary production allows ecologists to comprehend global variations in mean net primary production. Modern productivity estimates employ satellite technology to measure the electromagnetic radiation reflected from various vegetation types on Earth's surface. High chlorophyll concentrations often reflect productive aquatic areas. Some notably productive regions are:

• Continental margins where river nutrients enter the ocean.

• Upwelling zones that enrich surface waters with nutrients.

• Northern oceans benefiting from vertical water mixing.

Comparison of Land and Marine Productivity

• Forests: Forests worldwide, particularly temperate forests, exhibit high productivity. However, temperate regions often surpass tropical forests in terms of production despite tropical forests having favorable climates. This is due to rapid soil weathering in tropics leading to low nutrient availability.

• Prairies and Savannas: Highly productive due to annual decomposition returning nutrients to the soil.

• Deserts and Tundras: These biomes demonstrate low productivity due to insufficient water or low temperatures, respectively. Wetlands are exceptionally productive due to ample water and nutrient levels.

Relationship Between Primary and Secondary Production

There is a significant correlation between primary and secondary production, typically measuring herbivore biomass. Increased plant biomass often corresponds to higher consumer biomass, yet evidence shows that a considerable part of primary production is consumed by detritivores rather than herbivores.

Case Study: Georgia Salt Marsh

In 1962, ecologist John Teal analyzed energy flow within a Georgia salt marsh ecosystem:

• Primary producers (Spartina plants and marine algae) capture about 6% of sunlight, with 77.6% of that energy used for respiration, leading to only 22.4% accumulated in biomass.

• Most organic material dies and decomposes in place, forming detritus consumed by detritivores (mainly bacteria), nematodes, and crabs.

• Herbivores (insect herbivores) consume only a small fraction, around 0.6% of the plant production, with spiders further consuming a trivial amount.

Energy Flow Diagram

The following diagram illustrates the energy flow dynamics within the salt marsh ecosystem:

• Plants and Algae: Capture 6.1% of sunlight.

• Detritivores: Consume the majority of decayed biomass.

• Herbivores: Consume significantly less (0.6%).

• The remaining biomass is exported by tides and decomposed by bacteria.

Earth's Biomass Distribution Across Taxa and Locations

An understanding of the factors limiting primary production and the fate of primary producers provides insights into the global distribution of biomass. In 2018, researchers estimated the total biomass distribution on Earth:

• Approximately 550 Gt C distributed mainly as follows:

  • Land Plants: 80% of global biomass, notably trees, includes:

  • Stems and tree trunks: 320 Gt C

  • Roots and leaves: 130 Gt C

  • Bacteria: 15% of global biomass.

  • Animals: A meager 2 Gt C, even though insect taxa are the most diverse.

• Particularly, marine species like Antarctic krill contribute comparably to human or cattle biomass.

Biome-Specific Biomass Estimates

Land biomass is measured at 470 Gt C, while marine biomass is low at 6 Gt C. This disparity indicates that despite oceans covering a vast portion of Earth's surface, terrestrial producers yield significantly greater biomass. Additionally, marine primary production supports higher levels of consumer biomass than the biomass of producers due to the slow turnover rate of consumer species compared to that of primary producers.

Trophic Level Biomass Distribution

In terms of biomass across trophic levels, land primary producer biomass exceeds that of consumers. In contrast, marine primary production is around 1 Gt C, supporting approximately 5 Gt C of consumer biomass. The inverted biomass pyramid illustrates that consumer biomass turns over slowly while producers experience rapid turnover, characterized by a timescale on the order of days compared to years for many fish species.