Test
Conservation science: data and indicators
Este test tiene tipos de pregunta que se abren en el reproductor de siempre.
Preguntas del test (31)
1The international union for the conservation of [blank_start]nature[blank_end]: IUCN
The [blank_start]international[blank_end] union for the [blank_start]conservation[blank_end] of nature (IUCN) has a number of conservation databases
- the IUCN [blank_start]Red[blank_end] list of threatened species assesses the risk of species extinction
- the IUCN red list of [blank_start]ecosystem[blank_end]: assesses the risk of ecosystem collapse
- the world database on key [blank_start]biodiversity[blank_end] areas: assesses sites important for biodiversity
- protected planet: assesses [blank_start]protected[blank_end] areas
- ECOLEX: [blank_start]ECOLEX[blank_end] provides a gateway to environmental law
- Anature
- Binternational
- Cconservation
- DRed
- Eecosystem
- Fprotected
- GECOLEX
- Hbiodiversity
2[blank_start]Red[blank_end] list of threatened species: one of the IUCN databases for conservation
categories of threat
- Extinct, Extinct in the [blank_start]Wild[blank_end]
- [blank_start]CRitrically[blank_end] endangered, ENdangered, Vulnerable
- Near Threatened, Least Concern
- Data Deficient, Not Evaluated
Some assessment criteria for the International Union for the Conservation of Nature (IUCN)
1. [blank_start]decreasing[blank_end] population (past, present and or/projected)
2. geographical range size, and fragmentation, decline or fluctuations
3. small population size, and fragmentation, decline or fluctuations
4. very [blank_start]small[blank_end] populations or very restricted distribution
5. quantitative analysis of extinction risk e.g. PVA- ARed
- BWild
- Ccritically
- Ddecreasing
- Esmall
3Red List Criterion 1: population decline
- the key indicator is the population [blank_start]size[blank_end] of animals, can be: fluctuating, decreasing, decreasing and fluctuating
conservation objective: define the current state of a population, predict its [blank_start]future[blank_end] and identify any threats to its persistance
- counts
- demographic data
- presence/absence data
conservation approach: identify and implement solutions to ensure persistence
- manage drivers of change, if applicable
- [blank_start]protected[blank_end] area: where? how big?
- Asize
- Bfuture
- Cprotected
4Indicators e.g. population [blank_start]viability[blank_end] analysis (PVA)
- [blank_start]population[blank_end] viability [blank_start]analysis[blank_end] aims to estimate the [blank_start]probability[blank_end] that a population of a species, or collection of populations, will persist for some particular [blank_start]time[blank_end] in a particular environment
- one key thing measured
- trying to estimate how [blank_start]long[blank_end] the species will persist in the particular environment, for a particular amount of time > will it die out?
problems with population viability analysis (PVA) - assumes all the individuals are the [blank_start]same[blank_end], there are differences in terms of survival, reproduction, etc.
- Aviability
- Bpopulation
- Canalysis
- Dprobability
- Etime
- Flong
- Gsame
5[blank_start]Population[blank_end] viability [blank_start]analysis[blank_end] indicator
1) a time series PVA, which assumes all individuals in the population are the [blank_start]same[blank_end]
2) a demographic PVA, based on estimates of age or stage specific vital rates, such as survival and reproduction
3) individual-based models and patch-occupancy data
Population [blank_start]viability[blank_end] analysis (PVA) is a species-specific method of risk assessment frequently used in [blank_start]conservation[blank_end] biology. It is traditionally defined as the process that determines the [blank_start]probability[blank_end] that a population will go extinct within a given number of years. More recently, PVA has been described as a marriage of ecology and statistics that brings together species characteristics and environmental variability to forecast population health and [blank_start]extinction[blank_end] risk.- Asame
- Bviability
- CPopulation
- Danalysis
- Econservation
- Fprobability
- Gextinction
6IUCN red list criterion 2: geographic [blank_start]range[blank_end] size
- next thing we might look at is range size > this is good for plants for they cannot more
- there are 2 measures people tend to use
1. extent of [blank_start]occurrence[blank_end] (measured area within a boundary, draw a line around the perimeter of where species live)
2. area of [blank_start]occupancy[blank_end] e.g. sum of occupied grid squares
the [blank_start]extent[blank_end] of occurrence gives a much [blank_start]bigger[blank_end] area compared to the [blank_start]area[blank_end] of occupancy, as outliers will have a dramatic effect
- Arange
- Boccurrence
- Coccupancy
- Dbigger
- Eextent
- Farea
7Red list criterion 3: Fragmentation
- if natural habitat has been [blank_start]fragmented[blank_end] it can be used as direct evidence for fragmentation for taxa with poor dispersal capacity
- fragmentation is important, if there is a lot of a habitat but very dispersed/fragmented this would be detrimental if the species has a low dispersal capacity- Afragmented
8red list criterion 3: small population size
the [blank_start]smaller[blank_end] the population, the closer to extinction but some species are naturally rare so need to distinguish between these 2 things
- this links back to the geographic range size of the species and the idea of the [blank_start]extinction[blank_end] vortex about how [blank_start]biotic[blank_end] and abiotic processes reinforce each other = if really small population that happens to be the last population of the species, is hit by a [blank_start]natural[blank_end] disaster it will wipe out the entire species straight away > so abiotic factor has a massive effect compared to if there were other populations
the extinction [blank_start]vortex[blank_end] = reinforcement among biotic and abiotic processes driving population size to extinction (Gilpe and Soule 1986)
as populations decrease, the [blank_start]time[blank_end] elapsing before extinction occurs more rapidly at smaller population sizes
- variability in abundance highest as population approaches extinction- Asmaller
- Bbiotic
- Cnatural
- Dvortex
- Eextinction
- Ftime
9Classifying threats to biodiversity
- apart from criteria, species are assigned [blank_start]threats[blank_end] and habitats too
threats to species are classified, basically [blank_start]12[blank_end] big categories for each but they have further levels
- Athreats
- B12
10Big threats according to the [blank_start]IUCN[blank_end] red list
- plants are mainly threatened by [blank_start]biological[blank_end] resource use which includes logging and gathering plants
- mammas face similar threats (maxwell et al. 2015)
[blank_start]Habitats[blank_end] are also classified as part of the IUCN red list assessment
- useful to have a standardised approach to compare species, do not need to know them
- Abiological
- BHabitats
- CIUCN
11[blank_start]Red[blank_end] list assessments and species
- there are 96,951 assessments as of january 2019
- [blank_start]55[blank_end]% classed as threatened (CR, EN, VU) and [blank_start]16[blank_end]% data deficient (55, 16)
- but 1.8 million species described so not enough have been assessed > we have [blank_start]not[blank_end] even assessed 10% of species
fact: [blank_start]cycad[blank_end] plants are most threatened
- ARed
- B55
- C16
- Dnot
- Ecycad
12Red list [blank_start]index[blank_end] = calculation to get a [blank_start]red[blank_end] list index value, do this by group so each group has a value
- available for few taxonomic groups only
- to assess [blank_start]extinction[blank_end] risk of groups over time
- an index of 1 = all species are [blank_start]not[blank_end] threatened, least concern
- 0 = all species [blank_start]extinct[blank_end]
Figure from Brummit et al. 2015
can see the effect over time, [blank_start]corals[blank_end] have declined the most rapidly but are not the most threatened
- cycad plants are the most threatened
- Aindex
- Bred
- Cextinction
- Dnot
- Eextinct
- Fcorals
13Challenges in measuring biodiversity
- '[blank_start]dark[blank_end] diversity' is when species that should be there are not
dark [blank_start]diversity[blank_end] = a set of species that are absent from a site but could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool
high completeness (i.e. high observed diversity and low dark diversity) within an ecoregion coupled with high irreplaceability and vulnerability indicate a 'high conservation priority' area- Adark
- Bdiversity
14Challenges in measuring biodiversity: sampling [blank_start]bias[blank_end]
- significant difference in the probability of detecting species between areas
- it will complicate distinguishing areas that are truly high in species richness and endemism from those that are simply sampled more intensely and therefore seem unique
- we know a lot [blank_start]more[blank_end] about animals than plants
- we know a lot [blank_start]more[blank_end] about terrestrial systems than marine- Abias
- Bmore
- Cmore
15Examples of sampling bias: geographical bias, mainly towards well-studied [blank_start]north[blank_end] america, [blank_start]western[blank_end] europe and australia
- these areas look more species rich, but they are [blank_start]not[blank_end] they are just very well sampled
- the map shows plant record
- Anorth
- Bwestern
- Cnot
16[blank_start]Meyer[blank_end] et al. 2015 > Meyer et al. [blank_start]2015[blank_end] plotted species richness from point records of vertebrates
- Meyer et al. compared this to a map with species richness from [blank_start]expert[blank_end] opinion (not just from records) and they were very different
- highlights sampling [blank_start]bias[blank_end]
Can see how different the two maps look, major issue if we want to protect the most species rich areas but we don’t know much about them
We don’t have the information for where is most species rich
- AMeyer
- B2015
- Cexpert
- Dbias
17How many species are there?
- we have no idea
- for a few groups e.g. birds and mammals most species have been described (mammals >5000, birds = 10,426)
but others e.g. insects we have no idea, so tried to build models to estimate in which insects came out as the biggest group
- at the moment 1.8 [blank_start]million[blank_end] species have been described, but the estimate is at [blank_start]8[blank_end].7 million- Amillion
- B8
18How many species have been assessed on the IUCN red list?
- all [blank_start]birds[blank_end] and mammals (we think) have been assessed on the international union for the conservation of nature
- Abirds
19We can avoid challenges of measuring biodiversity by meaning more strategic in how we collect data
The IUCN [blank_start]red[blank_end] list mainly focusses on assessing species, do not focus on other aspects such as ecosystems
looking at the 5 [blank_start]strategic[blank_end] goals for 2020, from the convention on Biological [blank_start]diversity[blank_end], we need variables that will measure other aspects of biodiversity:
essential biodiversity variables, are still in the process of being agreed, but can be used to assess/indicate
- Ared
- Bstrategic
- Cdiversity
20Essential biodiversity variables
- the essential biodiversity variables are [blank_start]standardised[blank_end] measures needed to monitor [blank_start]changes[blank_end] in the health and diversity of nature over time
- e.g. changes in size and distribution of populations of species, habitats and interactions
- many biodiversity variables are screened to identify those that fulfil criteria on
> scalability
> temporal sensitivity
> feasibility
> relevance across taxa and terrestrial, fresh water, and marine realms- Astandardised
- Bchanges
21Essential biodiversity variables
1. genetic composition > [blank_start]allele[blank_end] diversity
2. species populations > abundance and distribution
3. species traits > phenology e.g. timing of leaf colouration
4. [blank_start]community[blank_end] composition > taxonomic diversity, e.g. multitaxa surveys
5. [blank_start]ecosystem[blank_end] structure > habitat structure e.g. remote sensing of forests
6. ecosystem function > nutrient retention e.g. input of [blank_start]nitrogen[blank_end]- Aallele
- Bcommunity
- Cecosystem
- Dnitrogen
22Adaptive management
- [blank_start]not[blank_end] specific to conservation science, widely used in management systems
- how you might plan what you would do for a species
conservation science needs evidence i.e. data- Anot
23we need a lot of information protect species, through surveys or ecological research
then once we have that we can think how we might act e.g. through in-situ habitat [blank_start]management[blank_end], species management, ex-situ breeding, legislation and policy contexts, socio-economic projects
- Amanagement
24The adaptive [blank_start]management[blank_end] cycle: the idea behind = systematic way of thinking about protecting species, considering everything in the context
- the [blank_start]problem[blank_end] context = might be an endangered species
- elicit [blank_start]objectives[blank_end] = might not just be about the species, may be about local community, if they hunt this species, what can be done so they don't have to hunt these species
- 3rd step = develop [blank_start]alternative[blank_end] actions, should address the objects
each objective should have one action, and evaluate how they would score
- need to evaluate consequences etc.
identify what the preferred alternative would be, implement this and then monitor this
- Amanagement
- Bproblem
- Cobjectives
- Dalternative
25Case study of adaptive management: tropical humid [blank_start]forests[blank_end]
- essentially, these are broad leaved, ever[blank_start]green[blank_end] forests occuring around the [blank_start]equator[blank_end]
- map overlaid with biodiversity hotspots (beige areas)
- can see a lot of these humid [blank_start]hotspots[blank_end] are hotspots > very important
- if we think about where most deforestation happens > tends to be the [blank_start]same[blank_end] areas, biggest loss of forests is around these forests are
- these forests are very threatened, high deforestation rates
- 3 different studies tried to estimate forest lost in different areas over different time
- some areas are losing the area half the size of [blank_start]scotland[blank_end] every year
- Aforests
- Bgreen
- Cequator
- Dsame
- Escotland
- Fforests
26Tropical humid forests
- there are different drivers causing forest declines across the world depends where they are
- clearing of forests for [blank_start]palm[blank_end] oil and timber production in South East asia and Africa
- another driver is cutting down forest for cattle and soya bean production for cattle feed in South [blank_start]America[blank_end]
- in [blank_start]Africa[blank_end], small scale clearing for timber and charcoal
- Apalm
- BAmerica
- CAfrica
27there is a lot of habitat [blank_start]fragmentation[blank_end], as road density is [blank_start]increasing[blank_end] in these humid tropical forests
- in Africa a lot of deforestation also occurs for increasing international trade e.g. [blank_start]coffee[blank_end], cacao, soy, beef etc.- Afragmentation
- Bincreasing
- Ccoffee
28Eastern [blank_start]Arc[blank_end] Mountains Biodiversity hotspot in [blank_start]Tanzania[blank_end]
The Udzungwa Scarp forest reserve close to nearby Udzungwa Mountains NP & surrounded by eight villages:
- very high diversity, lots of [blank_start]primates[blank_end]
- Presence of endangered primate and duiker populations (e.g. Endangered Abbott's duiker and Udzunga Red Colobus)
- people have identified threats in 1998 and 2008: Biodiversity depletion [blank_start]higher[blank_end] than in nearby forests
Increased disturbance, e.g. snare hunting, pole-cutting & [blank_start]log[blank_end]ging
Declines in abundance of mammal species ([blank_start]elephants[blank_end] and leopards have already disappeared)
something was happening here but not other forests- ATanzania
- Bprimates
- Chigher
- Dlog
- Eelephants
- FArc
29Action to address threats in Eastern Arc Mountains, biodiversity hotspot in Tanzania
- [blank_start]law[blank_end] enforcement
- reforestation
- [blank_start]protected[blank_end] areas
Initial Government suggested solutions:
>Upgrading status to [blank_start]Nature[blank_end] Reserve
>Improving law enforcement
>Initiating livelihoods programmes to provide alternative [blank_start]protein[blank_end] sources to the local communities
but then in another study they thought about different activities that could be done in the area and trialled them to see how well they worked: in the [blank_start]adaptive[blank_end] management cycle the different activities are the alternatives to address the [blank_start]objectives[blank_end]
- they then evaluated each of the consequences of each of these [blank_start]alternatives[blank_end] to help the objectives
they included:
Evaluating small scale local activities that focus on certain types of income generation:
[blank_start]bee[blank_end]keeping(“Bees”)
dairy [blank_start]goat[blank_end] husbandry (“Goats”)
[blank_start]fish[blank_end] farming (“Fish”)
[blank_start]fuel[blank_end] efficient stoves (“Fuel”)
[blank_start]rabbit[blank_end] farming (“Rabbits”)
[blank_start]tree[blank_end] planting (“Trees”)- Alaw
- Bprotected
- CNature
- Dprotein
- Eadaptive
- Fobjectives
- Galternatives
- Hbee
- Igoat
- Jfish
- Kfuel
- Lrabbit
- Mtree
30They rated the activities
5 [blank_start]objectives[blank_end]: education, research and planning, infrastructure, protecting species and habitats and legacy
- then 6 alternatives
scored them
- planting trees was good for infrastructure
- scored each [blank_start]alternative[blank_end] against each objective = came out with overall score (out of 55)
- rated them in order
- found that planting [blank_start]trees[blank_end] was the best thing they could do
- an example of adaptive management strategy
Sainsbury et al. 2015 Biological Conservation- Aobjectives
- Balternative
- Ctrees
31Extra
- The [blank_start]African[blank_end] Rainforest [blank_start]Conservancy[blank_end] = (ARC) the african [blank_start]rainforest[blank_end] conservancy is a charity that works to protected areas such as the [blank_start]Eastern[blank_end] Arc Mountains in Tanzania
- the eastern arc mountains are 13 isolated mountains in [blank_start]Tanzania[blank_end] and Kenya which is 1 out of [blank_start]24[blank_end] recognised areas with high forest biodiversity (1/24)
- there are lots of threats to the biodiversity of Eastern [blank_start]Arc[blank_end] mountain
- people live off the land = over exploitation
- so ARC charity are using [blank_start]adaptive[blank_end] management strategies to promote more sustainable use
- not only the locals benefit from the area, so does the rest of the world > firewood, medicines, honey
- the rainforest is the [blank_start]water[blank_end] source for a number of surrounding villages
- a lot of land in the Eastern ARC Mountains in Tanzania are converted to [blank_start]farm[blank_end]land
- AConservancy
- BAfrican
- Crainforest
- DEastern
- ETanzania
- F24
- GArc
- Hadaptive
- Iwater
- Jfarm
Información
- Descripción
- Conservation Test sobre Conservation science: data and indicators, creado por sophie waddington el 29/01/2019.
- Autor
- sophie waddington
- Idioma
- English
- Visitas
- 2
- Etiquetas
- Valoración
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