Avaliando padrões emergentes e processos ecológicos por ... · High Quality Medium Quality Low...

Avaliando padrões emergentes e processos ecológicos por meio

de simulação de movimentos de aves em paisagens fragmentadas

MILTON CEZAR RIBEIROmiltinho_astronauta@yahoo.com.br

Referata biodiversaINPE, Julho 2010

Assessing simulated bird species responses to landscape structure:spatial explicit IBM

RIBEIRO * FORTIN * METZGER et al., in reviewUofT-CANADA * USP-BRAZIL

MILTON RIBEIRO – mcr@usp.br

STUDY BACKGROUND:• Habitat Loss and Fragmentation

• Negative effect on Biodiversity

HABITAT MATRIX

Habitat loss WITHOUT Fragmentation

Habitat loss WITH Fragmentation

STUDY BACKGROUND:• Fragmentation Threshold:

10-30% of habitat (Andrén 1994; Fahrig 2003)

Radford et al (2005)

STUDY BACKGROUND:

• Brazilian Atlantic Forest : 12% of remaining habitat

• ~90% of habitat for forest species persistence was lost

• How species respond to habitat configuration?

• How habitat qualityinfluences speciesdistribution?

Ribeiro et al 2009

OBJECTIVES:

• What influences the response patterns of simulated species?

Habitat AMOUNT * Habitat QUALITY * AGGREGATION

at patch level at landscape level

APPROACH:

• Individual Based Models• Using generic species profiles that we setup for

the Atlantic Forest bird species

• What influences individuals to move/disperse?• Habitat quality• Degree of crowdingness

• Why Individual Based Models?• Generate testable hyphothesis• Check if expected patterns occurs

APPROACH:

• Individual Based Model

• When individual are dispersing:

• The mortality rate is high on matrix

• Change the movement pattern• Routine maximum distance < explorative

distance

APPROACH:

• Individual Based Model

• “Cost” to move:

• Depends on position of individual• Interior of patch -> low cost• edge proximity -> medium cost• Matrix -> high cost

• Habitat quality:• High quality -> low cost• Medium quality -> medium cost• Low quality -> high cost

Simulated landscapes (n=10,000)

• Habitat amount: from 5 to 70%

• Aggregation: from 0.1 (random) to 1.0 (clumped)

• Habitat Quality: from low (0.1) to high (1.0)

METHODS

Continuous variables – Markov Chain Monte Carlo - MCMC

High Quality Medium Quality Low Quality/Matrix0.7 – 1.0 0.4 – 0.7 0.1 to 0.4

Simulated Landscape: 512x512 – resolution 30m

AMOUNT=60% AGGREG=0.85

Simulated Landscape: 512x512 – resolution 30m

EDGE SENSITIVE HABITAT-DEPEND. – DON’T USE CORRIDOR

EDGE AND CORRIDOR TOLERANT – USE CORRIDOR

GAP CROSSING OF 240M

Species profiles:

GAP CROSSING OF 60M

GAP CROSSING OF 120MEDGE TOLERANT-DON’T USE CORRIDOR

GAPCROSSING

PROBABILITY

Gap Crossing - Awade & Metzger 2008 (understory birds)

Method = Play backThamnophilus caerulescens

HABITAT MATRIX

Response to Edge – Hansbauer et al 2008 (understory birds)

Method = Telemetry

DISTANCE TO EDGE (m)

PreferenceIndex

>200 M

C. caudata

MATRIX HABITAT

Home-range & use of Non-Forest habitatsHansbauer et al 2008 (understory birds) -Method = Telemetry

C. caudata

MATRIX = agriculture; pasture; rural building and silviculture

Habitat

Matrix

Starting

population size =

Habitat amount/HR

Define position

Start simulation

Map database:

Landscape +

auxiliary maps

Species profile: HR,

routine distance,

dispersing distance

landscape

FOR time step=1 to N

Overcrowding on patch?

Functional patches

Habitat qualityDistance to edge/patch

change to disperser

movement state

ALIVE?

Not move

Dispersing?

Follow

disperser rule

Follow routine rule

Estimate prob.

of death, movement

New position

Summary for landscape

Dispersal rate Mortality rateMovement costMovement variability

RESPONSE VARIABLES – *at landscape level*DISPERSAL RATE:

• % of individual dispersing after a simulation

MOVEMENT VARIABILITY:

MORTALITY RATE:• % of mortality after a simulation

MOVEMENT COST: 1

(position * habitat quality)

TOTAL LENGTH

Euclidean DISTANCE

Distance from edge (m)

Edge sensitive

Edge tolerant

Edge and corridor tolerant

Generalist low gap crossing

Generalist medium gap crossing

Distance from edge (m)

lity p

Edge sensitive

Edge tolerant

Generalist low gap crossing

Generalist medium gap crossing

Experimental Design

• Home range size (HR): 10 ha

HR=Surrogate for Carrying capacity, used to define Starting Population Size

• Time step per simulation: 500 movements

• Maximum ROUTINE movement distance: 30 m• maximum EXPLORATIVE movement distance: 150 m

• N replicates: 10,000 runs, for EDGE AND CORRIDOR TOLERANT species profile

Expected Patterns:

HABITAT AMOUNT

HABITAT QUALITY AGGREGATION

Mortality

Dispersal rateMov. Variability

Movement cost

Landscape Ecology And Conservation Lab - USP

IBM simulations – time steps = 500Population size = 100

Edge sensitive Edge and corridor tolerant

Low mobility Medium mobility

Amount of habitat (%)

10 20 30 40 50 60

Landscape-response:Each points is one simulation (500 time steps)For one landscape, and for one species profile

RESULTS

Fitted by Generalized Additive Model (GAM)

Statistical Approach: Model Selection (AIC)

DISPERSAL RATE

10 20 30 40 50 60

Aggregation

20 40 60 80

Quality of landscape

0.3 0.4 0.5 0.6

HABITAT AMOUNT AGGREGATION HABITAT QUALITY

10 20 30 40 50 60

Agregation

20 40 60 80

0.3 0.4 0.5 0.6

MORTALITY RATE

10 20 30 40 50 60

Agregation

20 40 60 80

0.3 0.4 0.5 0.6

MOVEMENT COST

bility

10 20 30 40 50 60

Agregation

bility

20 40 60 80

Quality of Landscape

bility

0.3 0.4 0.5 0.6

MOVEMENT VARIABILITY

Response variables Selected Models DAICc wAICc (wAIC)

Movement variability Amount of habitat+Aggregation 0.00 0.89 0.89

Dispersal rate Quality of habitat patches 0.00 0.52 0.80

Quality of landscape 2.48 0.15

Amount of habitat 2.83 0.13

Mortality rate Quality of habitat patches 0.00 0.24 0.69

Quality of landscape 0.15 0.23

Amount of habitat 0.18 0.22

Movement cost Amount of habitat+Aggregation 0.00 0.93 0.93

Expected Patterns:

HABITAT AMOUNT

Mortality

Movement cost

Observed Patterns:

HABITAT AMOUNT

Mov. VariabilityMovement cost

MortalityDispersal rate Mortality

Movement cost

Future Work

• Other species profiles including those with gap-crossing capability of 60 and 120 m?(functional connectivity)

• Daily-maximum distances >30 m?

• When dispersing-maximum distances >150 m

• Larger HR sizes (>50 ha)? (Top-predators)

Frame-work advantages• A completely continuous modelling

• Habitat amount, quality and aggregation• Individual position completely free (not pixel-

based)• Movement distances (daily or when dispersing):

continuous following a uniform distribution• Home-range size: fixed our variables• Perceptual range position, habitat quality and

mortality • Simulate different species profile, varying all

parameters that allow to adjust to species that can respond to different scales

• Fully spatial explicit response pattern, including density-dependence behaviour

Untangling the effects of landscape spatial

structure, habitat quality, and species

traits on ecological processes

RIBEIRO * MARTENSEN* FORTIN * METZGER - in prepUofT-CANADA * USP-BRAZIL

MILTON RIBEIRO – mcr@usp.br

OUTLINE:• Study background and research motivation• Confounding Effects• BioDIM (Biologically scaled Dispersal Model)• Response patterns• Sensitivity analysis• Results across and within species• Summary

• Future developments for BioDIM

STUDY BACKGROUND:• Biodiversity and ecossystem variability

• How to explain?• How much we can explain?

Background * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

System variability

Processes(responses)

Patterns(the effects)

DispersalMatingReproductionGene flowMortalityForest sucessionBiomass production

Habitat lossFragmentationPatch size distrib.IsolationHabitat qualityConnectivityLand-cover dynamic

DispersalMatingReproductionGene flowMortalityForest sucessionBiomass production

Habitat lossFragmentationPatch size distrib.IsolationHabitat qualityConnectivityLand-cover dynamic

Full system variability

Pattern 1

Pattern 2

Pattern 1

Pattern 2

STUDY BACKGROUND:• Habitat Loss and Fragmentation

• Negative effect on Biodiversity• Habitat quality are important for:

• Species persistence• Population density• Carrying capacity• Reproductive success

• Landscape structure• Influences species movement• Patch accessibility• Dispersal success• Meta-community maintenance

• Species traits• How individuals interact with landscape features• Edge sensitivity / Gap crossing capatity

OBJECTIVES:• Estimate the strength of influence for the three

groups of factors on species response patterns:

Landscape structureHabitat QualitySpecies traits

Studies bottle neck:• Assess the influencing factors independently

APPROACH:

• BioDIM (Individual Based Models)Biologically scaled Dispersal Model

• Using generic species profiles that we setup for the Atlantic Forest bird species

Species profiles:

Binary landscape

EdgeTolerant

Gap crossing60 m

Edge sensitive

Gap crossing 120 m

RESPONSE VARIABLES – *at landscape level*

DISPERSAL RATE: % of individual dispersing after a simulation

MOVEMENT VARIABILITY:

MORTALITY RATE: % of mortality after a simulation

ENCOUNTER RATE: number of enconters Male/Female

MOVEMENT COST: 1

(position * habitat quality)

TOTAL LENGTH

Euclidean DISTANCE

EXPERIMENTAL DESIGN:

Landscape structure:PLAND: Amount of habitat (5% to 70%)AGGREG: Aggregation of habitat (0.1 to 1.0)

Habitat quality:HQBIN: include quality on model: Yes/No?HQLAND: Habitat quality at landscape levelHQFRAG: Habitat quality at patch level

Species traits:SPECSENSIT: Species sensitivity to spatial heterogeneity

(i.e. Species profiles)HORANG: home-range size, varying continuously from 5 to 30 ha;ROUTDIST: maximum routine distance (30 to 90 m; uniform distribution)EXPLDIST: maximum explorative distance (1.0 and 3.0 times the

ROUTDIST, i.e. 90 and 270 m; uniform distribution)

10 000 replicates / 500 time steps

SENSITIVITY ANALYSIS (Saltelli et al. 2008):

Standardized Regression Coefficient:SRC = -1 to +1 & +Std. Error

sensitivity package; Pujol 2008

SENSITIVITY ANALYSIS (Saltelli et al. 2008):

Standardized Regression Coefficient:SRC = -1 to +1 & +Std. Error

sensitivity package; Pujol 2008

Positive effect Negative effect

RESULTSBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

Positive effect

Negative effect

Including all species

Response variables

Explanatory

variables All species

sensitive

tolerant

Edge- and

corridor-

tolerant

Low gap-

crossing

Medium

gap-crossing Observation

Dispersal rate SPECSENSIT + + +

PLAND - - - - - - - - - - - always present

AGGREG - - - - - - - - - - - - + strong/trend/always present

HQBIN 0 0 0 0 0 +

HQLAND 0 0 + - 0 - - partial

HQFRAG 0 0 - 0 0 +

HORANG 0 - - 0 + + trend/partial

ROUTDIST + + + + + + + + 0 trend/partial

EXPLDIST 0 0 0 - - - partial

Movement variability SPECSENSIT 0

PLAND + - + + 0 0 + + partial

AGGREG + 0 0 + + + partial

HQBIN - - - - - 0 partial

HQLAND + + + 0 0 0 0

HQFRAG - - - - - 0 partial

HORANG 0 - - 0 0 0

ROUTDIST 0 - 0 - 0 - partial

EXPLDIST + + + + + + + 0 trend/partial

SPECSENSIT 0 0 0 0 0 0

Movement Cost SPECSENSIT ++

PLAND - - - - - - - - - - - - - - - - - - strong/always present

AGGREG 0 - - - + + trend/always present

HQBIN + + 0 0 + + partial

HQLAND - - 0 - - - - partial

HQFRAG + + + 0 + + + partial

HORANG + + + + + + + + + + + + always present

ROUTDIST 0 0 0 0 0 0

EXPLDIST - 0 - - - - Partial

Within species

Response variables

Explanatory

variables All species

sensitive

tolerant

Edge and

corridor

tolerant

Low gap

crossing

Medium gap

crossing observation

Encounters rate SPECSENSIT + +

PLAND + + + + + + + + + + always present

AGGREG + + 0 + + + + + + + + partial

HQBIN 0 0 - 0 0 0

HQLAND 0 0 0 + 0 0

HQFRAG 0 0 - - 0 0

HORANG - - - - - - - - - - - - - - - - - - strong/always present

ROUTDIST 0 + 0 0 0 0

EXPLDIST 0 0 0 0 0 0

Mortality SPECSENSIT +++

PLAND - - - - - - - - - - - - - strong/always present

AGGREG - - - - - - - - - - - - - - - - strong/always present

HQBIN 0 0 + + 0 0

HQLAND - - 0 - - - 0 partial

HQFRAG + + 0 + + 0 partial

HORANG 0 0 0 0 0 0

ROUTDIST + + + + 0 + partial

EXPLDIST 0 0 0 0 0 0

Within species

SUMMARYBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

• Species sensitivity was the primary factor to explain DISPERSAL rate and MORTALITY

• Amount of habitat: primary factor for MOVEMENT COST

• Home-range size: primary factor for ENCOUNTER Rate

• Movement variability: no strong factor was detected

SUMMARYBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

• Amount of habitat and aggregation were the secondary factor for DISPERSAL rate and MORTALITY

• Home-range size and Species sensitivity: secondary for MOVEMENT COST

• Species sensitivity : secondary factor for ENCOUNTER Rate ; amount and aggregation of habitat are of tertiary influence on ENCOUNTER RATE

• Habitat quality not influenced any response variables

ImplicationsBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

• Important to define “conservation target”• Species? Taxon?

• Landscape spatial heterogeneity was always important, but its strength of influence varied greatly depending on “process of interest” (i.e. response pattern) and species sensitivity

• Although habitat quality are pointed out as important to population’ s maintenance, this type of information are hard to obtain, and are generally measured at patch scale, not at landscape scale

Within Species

Future WorkFuture studiesBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

• Ecological Thresholds • BioDIM & Landscape genetic• BioDIM & 3D• BioDIM & Continuous surface• Apply BioDIM for sampling issues:

landscape genetic

Future WorkEcological thresholdsBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

HABITAT AMOUNT

Future WorkEcological thresholdsBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

HABITAT AGGREGATION

HABITAT AMOUNT

DISPERSAL RATE

population

GENETICSUB-MODEL

Individuals

LOCI structure

Proximity perception (PROX m)

Sex (F/M) rate

Gene exchange rate

FOR individual =1 to

popsize

Is Female

Exit genetic module

Dist < Prox mno

FOR other individual

Other Is Male

Add 1 to # meetings

Change LOCI struct for

potential offspring

Example of LOCI STRUCStart: [0,1,1,0,1,0,1] [1,1] [0,1,0,1,1] [0,0]

End: [0,1,0,0,1,1,1] [1,0] [1,1,0,1,1] [1,0]

Population Size is the sameMovement pattern is the same

Routine daily distance = lower Routine daily distance = higher

Sampling issues on landscape genetic studies

Future studiesBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

Continuous landscapes

Future studiesBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

3D scaled landscapes: a challengeBackground * Effects * BioDIM * Responses * Sensitivity * Results * Summary * Future

-200 0 200 400 600 800 1000 1200 1400

Perfil1 Perfil2 Perfil3

Perfil4 Perfil5

Distance between paired fragments - m

Altitude (meters)

-200 0 200 400 600 800 1000 1200 1400

Perfil3

-200 0 200 400 600 800 1000 1200 1400

Acknowledgment:

Brownyn Rayfield, Josie Hughes, Ilona Naujokaitis-Lewis and Danilo Boscolo for fruitful discussion about ecological modelling and birds behaviour at Atlantic Forest

• National Council for Scientific and Technological Development (CNPq)• The State of São Paulo Research Foundation (FAPESP)• Petrobras Company

Landscape Ecology And Conservation Lab - USP

Avaliando padrões emergentes e processos ecológicos por ... · High Quality Medium Quality Low...

Documents

Transcript of Avaliando padrões emergentes e processos ecológicos por ... · High Quality Medium Quality Low...

يبتك › wp-content › uploads › 2019 › 11 › 2012291… · atp atp j' 0.4 .atp 04 + nad atp 0.4 + nad .fadh2 ,nadh ,atp + nad

Food=Quality Time

Apresentação Institucional Quality Assurance

1375962835_Cartilha de Retencoes Quality

Apresentação Quality Score Contabilidade

Top quality brasil unaflex

Válvula de ar 3/2 vias · 2020. 12. 21. · 3A: Air Valve (3/2 way) Code 1: 100 Series a 12 Valve 10: Single air control 20: Double air control Flow chart Model: 0.7 0.6 0.4 0.2

Data Quality Through Model Quality: A Quality Model for Measuring and Improving the Understandability of Conceptual Models

ACO ShowerDrain Informação técnica em Drenagem Sanitária...Número de ralos Altura de acumulação 0 mm 5 mm 15 mm 1 ralo 0.4 l/s 0.5 l/s 0.6 l/s 2 ralos 0.7 l/s 0.8 l/s 1.0 l/s

Key transition points: the climbing to Quality Management ...€¦ · ... the climbing to Quality Management System ... in the management of several quality processes. This model

quality - LAQI

Power Quality harmonics

Quality Assurance Quality Enablement

COVID-19 E SEUS DESDOBRAMENTOS€¦ · Netherlands 176 188 -12 0.9 45,064 23 5,811 12.9% China 3 2 1 0.4 84,084 0 4,638 5.5% Sweden 379 637 -258 0.7 33,188 67 3,992 12.0% India 6,767

Manual Tecnico Sistema Cambio Versao 0.4

Métodos Matemáticos na Ciência de Dados: Introdução Relâmpagomtm.ufsc.br/coloquiosul/notas_minicurso_8.pdf · 7 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 Figura3–Amostrarotulada.

7,718 0.7 (0.4) 0.4 UGPA3 Análise de Investimentos 2.7% 5 ...€¦ · CSU CardSystem (CARD3) – Lucro de R$ 8,4 milhões do 2T18 e melhor margem operacional A CSU registrou no 2T18

Programa Quality

Revista Rosa News - Edição 0.7

Portfolio Quality