Conservation Bio Midterm

Conservation Biology

-       the scientific study of the causes of biodiversity loss and the development of biological principles to prevent extinction and maintain evolutionary and ecological processes

o   Applying principles of ecology and evolutionary biology to preserve biodiversity

o   Includes: Genetics, natural resource fields (forestry, fishery biology, wildlife biology, wildlife biology)

Conservation Science

-       treats conservation problems as a social science

o   Includes: Public policy, ethics, sustainable development, philanthropy, sociology, psychology, communications, anthropology, agriculture, economics, conservation biology, climate science, public health

Conservation science vs Conservation biology

Conservation science views conservation problems as a social science and conservation biology is the scientific study of causes of biodiversity loss

Muir

Protect wilderness due to intrinsic value / because nature is beautiful!

Conservation ethic

Pinchot

Manage resources sustainably for human use → protect nature because we need it

Leopold

Think ecologically → view humans as part of the ecosystem we are protecting, wrote the land ethic

moral responsibility of humans to the natural world and how we are responsible for and to the land

Carson

Understanding human impacts on the ecosystem like pollution, habitat loss, pesticides

wrote “Silent Spring”

Soule

Build a formal scientific discipline to understand biodiversity loss

Soule’s Postulates

1. Evolution is ongoing

2. Ecological systems are dynamic and interconnected

3. Small populations are especially vulnerable to extinction

4. Conservation biology should integrate ecology, evolution, genetics, and population biology to understand and percent biodiversity loss

Genetic Diversity

Increase genetic diversity increases population viability

Includes allelic diversity, heterozygosity, standard genetic variation, and adapative capacity

Allelic Diversity

Total range of different inherited traits and DNA variations found within members of the same species

Heterozygosity

presence of two different alleles for a specific gene in an individual, one inherited from each parent, resulting in genetic variation

Standard Genetic Variation

The natural DNA differences in DNA sequences among individuals within a species or population

• Genetic diversity management seeks to preserve and enhance the variety of alleles within and among wildlife populations to safeguard their long term viability

Adaptive capacity

Ability of a system, institution, human, or organism to adjust to change, cope with consequences, moderate potential damage, or take advantage of new opportunities

• In context of ecosystems, it is the ability to maintain, recover, or adapt performance and function as climate conditions change

Species Diversity

comprised of richness and evenness

Species Richness

how many species are present in an area (doesn’t tell the full story of biodiversity

Species evenness

How evenly are individuals distributed among species?

Is the community dominated by one species

Endemism

Species are restricted to a particular geographic region

Functional diversity

variation in ecological roles

• species are linked in complex webs of interactions

• losing species can mean losing unique functions or evolutionary lineages

• Need to conserve interactions even if we do not fully understand them

Phylogenetic diversity

Amount of evolutionary history represented

• species are linked in complex webs of interactions

• losing species can mean losing unique functions or evolutionary lineages

• Need to conserve interactions even if we do not fully understand them

Ecosystem Diversity

Variation in ecosystem types, structure, and ecological processes

• includes habitat structure, species assemblages, energy flow, nutrient cycling

• Conserving ecosystems often protects many interacting species simultaneously

What is the Florida Panther a case study for?

Genetic diversity

Florida Panther Case Study

• 1967: listed as federally endangered, by 1990s <30 Florida panthers remained

  • Predicted extinction in 20 years

• Evidence for severe inbreeding depression: kinked tails, cowlicks, cardiac defects, poor semen quality, high disease prevalence, cryptorchidism in all males (one undescended testis)

• Conduct genetic rescue to increase genetic variability by introducing panthers from other populations

  • Questions to ask: 1) will it lead to outbreeding depression? 2) if we do it, which population should be the source

    • All north American panthers are genetically similar

    • DNA from museum samples showed Florida panthers as being more genetically diverse but not differentiated from Texas panthers

• 1995: 8 Texas females introduced

  • Offspring of released females lacked deformities

  • Hybrid offspring had a higher survival and expanded into new areas thought to be unsustainable

What are Hawaiian Honeycreepers a case study for?

Species diversity

Hawaiian Honeycreepers Case Study

• European rosefinch got introduced to Hawaii and diversified across Hawaii

  • 56 species only found in Hawaii

  • Developed different diet specializations

• Threatened by habitat loss, invasive predators (islands often are not home to many predators), avian malaria (from mosquitos)

  • As climate got warmer, mosquitoes could travel higher and infect more high-altitude birds

• Only 15 species of these birds now

What are Figs and Fig Wasps a case study for?

Functional and phylogenetic diversity

Figs and Fig Wasps

• During dry periods in seasonal rainforests, a very small number of plant species (figs) sustain the entire frugivore community for 3 months each year!

• Most fig species have only one specialist wasp pollinator

  • Fig is only place the wasp can reproduce

• Most figs only have 1 specialist wasp pollinator

  • If fig wasps went extinct, figs would not be able to cross-pollinate

• Loss of 5-10 different fig species in tropical dry forests could lead to eventual extinction of many / all fruit eating birds and mammals

  • Tropic cascade extinction

What are kelp forests a case study for?

Ecosystem diversity and trophic cascade

Kelp Forest Case Study

• Kelp provides habitat and food for species

  • Kelp are an ecosystem engineer

• Sea urchins overgraze kelp in absence of otters

• Without otters, the kelp forest ecosystem collapses

  • They are a keystone species

What is the difference between natural and human caused extinction

• Natural

  • Extinction has occurred throughout history of life

  • Extinction and speciation shape biodiversity

  • Most extinctions occur gradually (a few during mass extinction events)

  • Rate and causes are what matter most for conservation biology

• Human-caused

  • Current rates greatly exceed background

  • Human activity is main cause

  • More specific focus of conservation biology is preventing extinctions that are accelerated and anthropogenic

What are the drivers of biodiversity loss

• Habitat loss/fragmentation

  • Loss = reduction of habitat

  • Fragmentation = habitat divided into smaller and smaller chunks

  • Main threat to 85% of species of IUCN Red List

  • Fragmentation adds edge effects and isolation on top of lost area

  • Smaller, isolated populations face greater extinction risk

• Overexploitation

  • Harvesting individuals faster than reproduction can replace them

    • Especially dangerous for slow moving species

  • Includes: hunting, gathering, fishing, logging, and wildlife trade

• Invasive species

  • Species introduced outside of their native range that cause ecological or economic harm

  • Harm caused through altered ecological interactions  predation, competitive exclusion, disease transmission, hybridization with native relatives

    • Hybridization results in less genetic uniqueness

  • Island ecosystems very vulnerable

• Pollution

  • Chemical contaminants, excess nutrients, plastic debris, light and noise pollution

    • Acts directly through toxicity or accumulates up the food chain through bioaccumulation

  • Effects often indirect and delayed

• Climate change

  • Warming temps and shifting precipitation alter where suitable habitat is

  • Species shift ranges poleward and upslope, tracking suitable conditions

  • Timing shifts too, sometimes out of sync with dependent species

Outbreeding Depression

crosses between two genetically distant groups or populations result in reduction of fitness

Staghorn and Elkhorn Coral

Dominant reef-building species

Disease was introduced → white band coral introduced

Functional extinction → population too low for them to maintain reef structure in Florida so they can’t serve their role anymore

Ecosystem suffers as a consequence

Richness vs Eveness

Richness is the number of species present, simplest biodiversity measure, easy to calculate, ignores relative abundance

Eveness is how evenly individuals are distributed among species

Shannon vs Simpsons Indices

Both consider abundance in addition to the # of species present

• Shannon → more weight on rare species (increase as both richness and evenness increase

• Simpson → more weight on dominant species

Alpha, beta, gamma diversity

• Alpha = species richness within a site

• Beta = difference among sites (gamma / alpha)

• Gamma = total diversity across region

Endemism

Not all species are equally distributed

restricted ranges = elevated extinction risk

Functional Diversity

-       Diversity of ecological roles and traits

-       Communities with identical richness may function very differently

-       Ecosystem processes depend on interactions among species

-       Loss of key functional groups can disproportionately affect ecosystem stability

Phylogenetic diversity & EDGE

• Diversity of evolutionary history represented

• Evolutionarily Distinct and Globally Endangered

  • Prioritize species that represent a unique branch of the tree of life and face high rates of extinction

Latitudinal diversity gradient

• Richness generally increases from poles to equator

  • One of the oldest and most consistent patterns in ecology

• Observed across many taxonomic groups – plants, birds, amphibians, reef fishes, insects, etc.

• Tropical regions contain both high richness and many endemics

• Conservation efforts are disproportionately concentrated in tropical ecosystems

Biodiversity hotspots

High richness, high endemism, high threat

Designed to help prioritize conservation investments

IUCN Red List and its categories

Classification of how at risk a species is

o   Extinct

o   Extinct in wild

o   Critically endangered (threatened)

o   Endangered (threatened)

o   Vulnerable (threatened)

o   Near threatened

o   Least concern

o   Data deficient (need more data to decide their category)

o   Not evaluated (have not done any evaluation)

Species-area relationships

Geography shapes extinction risk

• species rand size varies widely

• Small ranges = high vulnerability

• Endemics are especially at risk

• Threats act spatially

What traits make a species more vulnerable to extinction?

• Small geographic range

  • Example: Devil’s Hole pupfish

• Low fecundity (biological capacity to produce offspring)

  • Example: Albatross

• Ecological specialist

  • Example: fig wasp

• High trophic level

  • Example: orca

• Large body size

  • Example: elephant

• Poor dispersal

  • Dispersal: movement of individual organisms away from birth site or current habitat to new location

  • Example: island snail

What are Amphibians Declines a case study of?

Compounding factors causing extinction risk

Amphibian Declines case study

• Amphibians are the most threatened vertebrate group

• Multiple interacting threats → chytrid fungus, climate change, habitat loss and fragmentation

  • Climate change and disease are interacting together

• Many amphibians have several vulnerability traits  small ranges, specialized habitats, limited dispersal

BIDE

• Birth

• Immigration

• Deaths

• Emigration

• Conservation action ultimately acts by changing one or more of these demographic processes

• (delta)N = B+I-D-E

Population growth terms λ and r

λ → rate of increase

• population growth over some finite time

r → growth rate

• population growth rate at any particular moment in time

Exponential vs Logistical growth

• Exponential Growth

  • Unconstrained growth, constant per-capita growth rate (r), J-shaped curve, useful baseline but never persists in nature

  • Example: bacteria culture

• Logistic growth

  • S-shaped curve, includes carrying capacity

  • Carrying capacity → not all populations can exponentially grow forever since they are bound to be limited by resources (competition, food limitation, space limitation)

  • Examples: deer

Carrying Capacity

not all populations can exponentially grow forever since they are bound to be limited by resources (competition, food limitation, space limitation)

Density Dependence

Conceptual curve of per capita growth vs population size

negative density dependence at high population sizes (deaths outweigh the births)

population growth rates are regulated by the population density

• Referring to any characteristic that varies with population density like resource limitations and shelter availability

Allee Effects

At very low population sizes → finding mates becomes difficult, cooperative behaviors break down, pollination declines, population growth can become negative

If population is too low, finding mates takes so much time and energy that reproduction becomes rarer and rarer and the population declines

Small populations may continue to decline even after threats are removed

Demographic vs Environmental Stochasticity

• Stochasticity: quality of being unpredictable, random, or governed by probability rather than a fixed deterministic plan  like populations

• Demographic: random variation among individuals

  • Due to survival, reproduction, sex ratio, & recruitment

  • More important in small populations

• Environmental: environmental variation affects entire populations

  • Examples: drought, hurricanes, wildfire, El Nino, coral bleaching

  • Greatest consequences for small populations

• All populations that experience stochasticity will eventually go extinct

Extinction Vortex

When habitat is lost and fragmented, populations get smaller and more isolated

Small populations lose genetic variation; reduces fitness and increases extinction risk

MVP

Minimum Viable Population

Smallest population expected to persist with an acceptably low risk of extinction over a specified time period

No universal MVP threshold → depends on life history and environment (management objectives matter)

Predictive models for conservation

Questions to ask: will population persist? What factors most influence its future? Which management actions are most likely to succeed?

Models help us compare alternative futures before acting

PVA

Population Viability Analysis

Quantitive framework for estimating the probability that a population will persist or go extinct under specified conditions

• How much of an impact a factor has on a population

Commonly used for:

• Estimating extinction risk

• Comparing alternative management strategies

• Identifying demographic processes limiting recovery

• Inform species recovered plans and/or conservation action

PVA input and outputs

Input field data (population size, age structure, birth rates, death rates, immigration, emigration, environmental variation) and population model (population growth, density dependence, demographic and environmental stochasticity, Allee effects, management scenarios)

Model output is 1000 simulated futures that say probability of extinction and expected population size (confidence intervals and management comparison)

PVA limitations

Dependence on data availability and quality, model assumptions, unknown future conditions

Sensitivity Analysis

measures the effect of a variable on model outcomes or effect of a demographic rate on population success

Adaptive Management

Monitor populations, update models, then refine management actions

Update management strategies as you obtain new information

California Condor

• Life history makes population vulnerable (very low reproductive rate, small population growth rates)

• Listed endangered with 27 left due to lead poisoning, shooting, egg collecting, habitat loss, power line collisions

• PVA showed population growth was most sensitive to adult survival and less sensitive to nest success, chick survival, and fecundity

• Solutions: captive breeding, lead ammunition reduction efforts, veterinary care, and releases

  • Actions reduced adult mortality (deaths) and increased recruitment through reintroductions (immigration)

• Population has grown but still requires intensive management

What is DNA organized into

Chromosomes

What are the 2 genomes a cell contains

nDNA and mtDNA

Alleles

Alternative versions of the same gene

Genotype

Combination of alleles an individual carries

nDNA vs mtDNA

nDNA → biparentally inherited and recombines

• conservation applications: genetic diversity, inbreeding, gene flow, adaptation

mtDNA → maternally inherited and does not recombine

• Conservation applications: phylogeography, species ID, eDNA

Ways to measure genetic diversity?

• Heterozygosity → frequency of individuals with 2 different alleles

• Allelic richness → number of different alleles in a population

• Nucleotide diversity → average DNA sequence differences among individuals

Bottleneck vs founder effects

Population bottleneck → severe, temporary reduction in population size; rare alleles often lost by chance

Found effect → new population established by a few individuals from a larger population; only a subset of genetic diversity is carried forward

Both reduce genetic diversity

Genetic drift

Random changes in allele frequencies

Can eliminate alleles regardless of fitness

Buri Experiment

• Showed genetic drift

• Let flies with white (homo), orange (hetero), and brown (homo) eyes mate freely and kept 8 males and 8 female of each generation

• Over the course of 20 generations, heterozygosity went down and the homozygosity went up

  • Loses genetic diversity

• Often due to some individuals having more offspring than others, individuals not breeding, males having multiple mates compared to other males

Drift vs selection

Drift → unpredictable trajectory (might be good or bad)

• impacts all populations but small populations fastest

• random but had predictable consequences → loss of diversity and fixation of alleles

Both → change allele frequencies and often reduce genetic variation

Selection → advantageous alleles increase predictability

• Selection is who is better adapted

Effective population size (Ne)

• Census size is the actual total count of individuals living in a population

• Ne is almost always smaller than census size because not all individuals reproduce equally or not at all

• While census size drives ecological interactions (like food competition), Ne drivers evolutionary and genetic processes (like inbreeding)

• Ne is reduced by unequal sex ratios, variation in reproductive success, and fluctuating population size

Inbreeding & inbreeding depression

Mating between relatives which increases homozygosity and reduces heterozygosity

Increasing homozygosity can cause

• Expression of harmful recessive alleles

• Reduced genetic diversity

• lower adaptive potential

• Reduced individual fitness

Inbreeding depression → reduced fitness resulting from inbreeding

Causes: lower survival, reduced fertility, developmental abnormalities, greater susceptibility to disease

Genetic Load

The reduction in the mean fitness of a given population relative to a population composed entirely of individuals with optimal genotypes devoid of deleterious alleles

Small populations accumulate deleterious alleles and reduced adaptive variation

Genetic rescue and its risks

Increasing gene flow into an inbred population to improve fitness

• benefits → increase genetic diversity, reduce inbreeding, restore adaptive potential

• Risks → outbreeding depression, introduction of maladaptive alleles, idease transmission, and loss of local adaptation

  • Outbreeding depression: mating with too far divergent individuals is still bad; mate pair is too different, so offspring is not fit for environment; increase of the wrong genetics

What is Isle Royale Wolves a case study of?

Genetic rescue

Isle Royale Wolves case study

• Background: isolated island population, apex predator of the moose

• Population peaked at 50 wolves but declined to only 2 in 2017

  • Low reproduction and skeletal abnormalities

• Genomics revealed severe inbreeding with extensive runs of homozygosity, extremely low genetic variation, and high inbreeding

• 19 wolves translocated in 2019 which introduced new diversity and increased the population

Habitat loss vs fragmentation

Loss: reduction in total amount of habitat

Fragmentation: change in configuration of habitat

Patch size

how large/small the habitat fragment is

• small patches support small populations, higher stochasticity but less habitat heterogeneity means fewer niches and fewer species

• Smaller patches vulnerable to extirpation → single event could wipe out entire population

edge effects

Abiotic: more light, more wind, wider temperature swings, drier

Biotic: increased invasion, higher predation and parasitism, altered plant community composition

Isolation

functional distance between patches, not just geographic distance

• more isolated = fewer immigrants = local extinction less likely to be recolonized

• Landscape connectivity is species specific

Matrix

Surrounding land cover or background environment that lies between discrete habitat patches

Metapopulations

set of local populations occupying discrete habitat patches and connected by occasional dispersal

Types of Metapopulations

1. Classic (Levins) — patches of similiar size and quantity; frequent local extinction and recolonized; no single patch essential

2. Mainland-island — one large extinction resistant “mainland” patch supplies dispersers to smaller “island” patches

3. Patchy — patches are well connected so they function as one large population; local extinctions rare

4. Non-equilibrium (declining) — colonization can’t keep up with extinction

Levins Model

c = colonization rate coefficient

e = local extinction rate coefficient

Metapopulations persists when c > e

• Patch size drives extinction rate (e)

• Isolation and matrix quality drive colonization rate (c)

• Fragmentation pushes e up and c down  collapse tends to be sudden

Rescue effect

Immigration can prevent local extinction / allow rapid recovery

Patches closer to occupied neighbors or better connected by permeable matrix have lower local extinction rates

Source vs Sink

Not all occupied patches are equally valuable

• Source → net exporter of inviduals

• Sink → net importer; would go extinct without immigration

Sinks can appear stable and visibly occupied → conservation ‘trap’ if managers mistake occupancy for habitat quality

Extinction Debt

When a habitat is destroyed, populations don’t immediately disappear but decline slowly toward extinction (inevitable)

populations are the “living dead” → present but doomed to local extinction because c < e and the time lag can be decades long

Restoring connectivity can begin to repay debt before extinction occurs

What is the Glanville Fritillary a case study of?

Habitat fragmentation and patch connectedness

Glanville Fritillary case study

• A butterfly found on islands in Sweden

• ~4200 discrete patches across 50x70km study area

• Only 20% of patches are occupied each year but metapopulation has persisted for decades (high turnover)

• Core Levin’s prediction → persistence is a property of the metapopulation, not an individual patch

• What predicts local extinction (e)

  • Patch area

  • Patch isolation

  • Habitat quality (host plant abundance, microclimate)

• What predicts colonization (c)

  • # and proximity of currently occupied patches

  • Females colonize in strong distance-decay probability

  • Well-connected patches are Patchy metapopulation; outlying patches are classic

Reserve design

1. Protect multiple patches

2. prioritize patches with lowest predicted extinction rates and highest colonization rates

3. don’t dismiss currently empty patches

4. identify and prioritize any “mainland” source patches

5. maintain matrix permeability between protected patches

SLOSS

Single Large Or Several Small

• Single large → lower edge:area ratio, more interior core habitat, supports species that need larger territories or interior specialists

• Several small → spread risk, can capture broader habitat variation

• Metapopulation theory shows that SS will only outperform SL if connectivity is good (c-e balance)

Corridors

Corridors raise colonization (c)

Can also facilitate the spread of disease, invasives, fire, etc

High species specific

Connected patches retain more native plant species than equally sized unconnected patches

Steppingstone patches

Caughley’s Two paradigms

1. Declining population Paradigm: what is causing this population to decline and how to stop it

2. Small population paradigm: given that a population is already small, what risk does smallness itself create (inbreeding, genetic drift, etc.)

   1. Caughley warned against only focusing on this

Both matter → small population size is not just a symptom of a species being in trouble but also a cause of further trouble via mechanisms independent from decline

Declining population paradigm

what is causing this population to decline and how to stop it

Small population paradigm

given that a population is already small, what risk does smallness itself create (inbreeding, genetic drift, etc.)

Forces that affect small populations

Allee effects, drift and inbreeding depression, environmental stochasticity, and demographic stochasticity

Mechanisms of the Allee affect

• mate limitation

• loss of cooperative behavior

• Reduced predator swamping

• Genetic Allee affects (inbreeding)

MVP and the 50/500 rule

Minimum viable population → probalistic, time-bound, foreseeable threats

Ne of 50 — minimum for short-term persistence → based mostly on limiting inbreeding depression

Ne of 500 — minimum for long-term persistence → based mostly on maintaining enough variation for evolution