ACDC 2019 Naturalist

Results: main figures

Study type: Point transect, Radial distance, No clustering.

Units used: Meter for distances, Sq. Kilometer for areas.

Note: Most figures have been rounded for readability, but 'CoefVar Density' have been further modified : converted to %

	Echant	Espèce	Passage	Adulte	Durée	NTot Obs	Max Dist	Analyse	Mod Key Fn	Mod Adj Ser	Left Trunc Dist	Right Trunc Dist	Fit Dist Cuts	ExCod	Effort	NObs	Obs Rate	NumPars AdjSer	Delta AIC	Chi2 P	KS P	CvM Uw P	CvM Cw P	CoefVar Density	Qual Bal 3	Qual Bal 2	Qual Bal 1	Qual Chi2+	Qual KS+	Qual DCv+	Density	Min Density	Max Density	Number	Min Number	Max Number	EDR/ESW	Min EDR/ESW	Max EDR/ESW	PDetec	Min PDetec	Max PDetec	RunFolder
28	1	Sylvia atricapilla	a+b	m	10mn	403	511.41	49	HAZARD	POLY	5	492	13	1	190	401	99.5	0	0	0.25	0.55	0.6	0.7	10	0.65	0.64	0.65	0.58	0.64	0.67	37.58	30.87	45.75	902	741	1098	133.7	124.4	143.6	0.074	0.064	0.085	SylvAtri-ab-10mn-m-haz-pol-la-ra-ma-90vq_6nr

Results: all details

Study type: Point transect, Radial distance, No clustering.

Units used: Meter for distances, Sq. Kilometer for areas.

Note: All values have been left untouched, as output by MCDS (no rounding, no conversion)

	Analyse	Echant	Espèce	Passage	Adulte	Durée	FonctionClé	SérieAjust	TrGche	TrDrte	NbTrchMod	Abrev. Analyse	OptimTrunc	NTot Obs	Min Dist	Max Dist	Mod Key Fn	Mod Adj Ser	Mod Chc Crit	Conf Interv	Left Trunc Dist	Right Trunc Dist	Fit Dist Cuts	ExCod	StartTime	ElapsedTime	RunFolder	NObs	NSamp	Effort	EncRate	CoefVar EncRate	Min EncRate	Max EncRate	DoF EncRate	Left Trunc	Right Trunc	Obs Rate	TotNum Pars	Delta AIC	AIC	Chi2 P	Chi2 P 1	Chi2 P 2	Chi2 P 3	f/h(0)	CoefVar f/h(0)	Min f/h(0)	Max f/h(0)	DoF f/h(0)	PDetec	CoefVar PDetec	Min PDetec	Max PDetec	DoF PDetec	EDR/ESW	CoefVar EDR/ESW	Min EDR/ESW	Max EDR/ESW	DoF EDR/ESW	AICc	BIC	LogLhood	KS P	CvM Uw P	CvM Cw P	Key Fn	Adj Ser	NumPars KeyFn	NumPars AdjSer	Num Covars	EstA(1)	EstA(2)	EstA(3)	DensClu	CoefVar DensClu	Min DensClu	Max DensClu	DoF DensClu	Density	Delta CoefVar Density	CoefVar Density	Min Density	Max Density	DoF Density	Number	CoefVar Number	Min Number	Max Number	DoF Number	Qual Bal 1	Qual Bal 2	Qual Bal 3	Qual Chi2+	Qual KS+	Qual DCv+	Group Left Trunc	Group Right Trunc	Order Same Trunc AIC	Order Close Trunc Chi2 KS DCv	Order Close Trunc DCv	Order Close Trunc Bal 1 Qual	Order Close Trunc Bal 2 Qual	Order Close Trunc Bal 3 Qual	Order Close Trunc Bal Chi2+ Qual	Order Close Trunc Bal KS+ Qual	Order Close Trunc Bal DCv+ Qual	Order Global Chi2 KS DCv	Order Global Bal 1 Qual	Order Global Bal 2 Qual	Order Global Bal 3 Qual	Order Global Bal Chi2+ Qual	Order Global Bal KS+ Qual	Order Global Bal DCv+ Qual	Order Global DeltaAIC Chi2 KS DCv
28	49	1	Sylvia atricapilla	a+b	m	10mn	HAZARD	POLY	4.553960	492.328316	13.000000	SylvAtri-ab-10mn-m-haz-pol-la-ra-ma	1	403	1.212094	511.409745	HAZARD	POLY	AIC	95	4.553960	492.328316	13.000000	1	2023-04-30 15:55:03.377000	1.300000	SylvAtri-ab-10mn-m-haz-pol-la-ra-ma-90vq_6nr	401	96	190	2.110526	0.068677	1.841824	2.418429	95	4.553960	492.328000	99.503722	2.000000	0.000000	4488.174000	0.250081	0.250081	nan	nan	0.000112	0.073005	0.000097	0.000129	399.000000	0.073743	0.073005	0.063896	0.085108	399.000000	133.695000	0.036502	124.440000	143.638200	399.000000	4488.205000	4496.162000	-2242.087000	0.550075	0.600000	0.700000	HAZARD	POLY	2.000000	0.000000	0.000000	99.033550	3.760158	nan	37.584680	0.100231	30.874110	45.753800	330.520400	37.584680	0.000000	0.100231	30.874110	45.753800	330.520400	902	0.100231	741	1098	330.520400	0.653611	0.640192	0.648279	0.583173	0.636554	0.672710	1	4	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	13

Summary computation log

This is mcds.exe version 6.2.0     
 Options;                                                                      
 Type=Point;                                                                   
 Distance=Radial /Measure='Meter';                                             
 Area /Units='Sq. Kilometer';                                                  
 Object=Single;                                                                
 SF=1;                                                                         
 Selection=Sequential;                                                         
 Lookahead=1;                                                                  
 Maxterms=5;                                                                   
 Confidence=95;                                                                
 print=Selection;                                                              
 End;                                                                          
 Data /Structure=Flat;                                                         
 Fields=STR_LABEL,STR_AREA,SMP_LABEL,SMP_EFFORT,DISTANCE;                      
 Infile=anlys\230430-153402\SylvAtri-ab-10mn-m-haz-pol-la-ra-ma-90vq_6nr\data.txt /NoEcho;                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       
 Data will be input from file - [...]POL-LA-RA-MA-90VQ_6NR\DATA.TXT
 End;                                                                          
 Dataset has been stored.
 Estimate;                                                                     
 Distance /Left=4.55396 /Width=492.328;                                        
 Density=All;                                                                  
 Encounter=All;                                                                
 Detection=All;                                                                
 Size=All;                                                                     
 Estimator /Key=HAZARD /Adjust=POLY /Criterion=AIC;                            
 Monotone=Strict;                                                              
 Pick=AIC;                                                                     
 GOF /NClass=13;                                                               
 Cluster /Bias=GXLOG;                                                          
 VarN=Empirical;                                                               
 End;

Detailed computation log

Estimation Options Listing

 Parameter Estimation Specification
 ----------------------------------
 Encounter rate for all data combined
 Detection probability for all data combined
 Density for all data combined

 Distances:
 ----------
 Analysis based on exact distances
 Width specified as:    492.3280    
 Left most value set at:    4.553960

 Estimators:
 -----------
 Estimator  1
 Key: Hazard Rate
 Adjustments - Function                 : Simple polynomials
             - Term selection mode      : Sequential
             - Term selection criterion : Akaike Information Criterion (AIC)
             - Distances scaled by      : W (right truncation distance)

 Estimator selection: Choose estimator with minimum  AIC
 Estimation functions: constrained to be nearly monotone non-increasing

 Variances:
 ----------
 Variance of n: Empirical estimate from sample
                (design-derived estimator R2/P2)
 Variance of f(0): MLE estimate

 Goodness of fit:
 ----------------
 Based on user defined cut points

 Glossary of terms
 -----------------

 Data items:
 n    - number of observed objects (single or clusters of animals)
 L    - total length of transect line(s) 
 k    - number of samples
 K    - point transect effort, typically K=k
 T    - length of time searched in cue counting
 ER   - encounter rate (n/L or n/K or n/T)
 W    - width of line transect or radius of point transect
 x(i) - distance to i-th observation
 s(i) - cluster size of i-th observation
 r-p  - probability for regression test
 chi-p- probability for chi-square goodness-of-fit test

 Parameters or functions of parameters:
 m    - number of parameters in the model
 A(I) - i-th parameter in the estimated probability density function(pdf)
 f(0) - 1/u = value of pdf at zero for line transects
 u    - W*p = ESW, effective detection area for line transects
 h(0) - 2*PI/v
 v    - PI*W*W*p, is the effective detection area for point transects
 p    - probability of observing an object in defined area
 ESW  - for line transects, effective strip width = W*p
 EDR  - for point transects, effective detection radius  = W*sqrt(p)
 rho  - for cue counts, the cue rate
 DS   - estimate of density of clusters
 E(S) - estimate of expected value of cluster size
 D    - estimate of density of animals
 N    - estimate of number of animals in specified area

Detection Fct/Global/Model Fitting

 Effort        :    190.0000    
 # samples     :    96
 Width         :    492.3280    
 Left          :    4.553960    
 # observations:   401

 Model  1
    Hazard Rate key, k(y) = 1 - Exp(-(y/A(1))**-A(2))
       Results:
       Convergence was achieved with   19 function evaluations.
       Final Ln(likelihood) value =  -2242.0870    
       Akaike information criterion =   4488.1743    
       Bayesian information criterion =   4496.1621    
       AICc =   4488.2046    
       Final parameter values:   99.033556      3.7601583

 Model  2
    Hazard Rate key, k(y) = 1 - Exp(-(y/A(1))**-A(2))
    Simple polynomial adjustments of order(s) :  4
       Results:
       Convergence was achieved with   15 function evaluations.
       Final Ln(likelihood) value =  -2241.4494    
       Akaike information criterion =   4488.8989    
       Bayesian information criterion =   4500.8809    
       AICc =   4488.9595    
       Final parameter values:   99.547349      3.6794809    -0.56949598

    Likelihood ratio test between models  1 and  2
       Likelihood ratio test value    =     1.2753
       Probability of a greater value =   0.258774
 *** Model  1 selected over model  2 based on minimum AIC

Detection Fct/Global/Parameter Estimates

 Effort        :    190.0000    
 # samples     :    96
 Width         :    492.3280    
 Left          :    4.553960    
 # observations:   401

 Model
    Hazard Rate key, k(y) = 1 - Exp(-(y/A(1))**-A(2))

              Point        Standard    Percent Coef.        95 Percent
  Parameter   Estimate       Error      of Variation     Confidence Interval
  ---------  -----------  -----------  --------------  ----------------------
    A( 1)      99.03        5.275    
    A( 2)      3.760       0.2116    
    h(0)     0.11189E-03  0.81687E-05       7.30      0.96951E-04  0.12914E-03
    p        0.73743E-01  0.53836E-02       7.30      0.63896E-01  0.85108E-01
    EDR       133.69       4.8802           3.65       124.44       143.64    
  ---------  -----------  -----------  --------------  ----------------------

 Sampling Correlation of Estimated Parameters

         A( 1)   A( 2)
 A( 1)  1.000   0.762
 A( 2)  0.762   1.000

Detection Fct/Global/Plot: Qq-plot

Detection Fct/Global/K-S GOF Test

 Kolmogorov-Smirnov test
 -----------------------

 D_n                      = 0.0398                 p  = 0.5501

 Cramer-von Mises family tests
 -----------------------------

 W-sq (uniform weighting) = 0.1107          0.500 < p <= 0.600
   Relevant critical values:
     W-sq crit(alpha=0.600) = 0.0968
     W-sq crit(alpha=0.500) = 0.1187

 C-sq (cosine weighting)  = 0.0619          0.600 < p <= 0.700
   Relevant critical values:
     C-sq crit(alpha=0.700) = 0.0499
     C-sq crit(alpha=0.600) = 0.0622

Detection Fct/Global/Plot: Detection Probability 1

Detection Fct/Global/Plot: Pdf 1

Detection Fct/Global/Chi-sq GOF Test 1

  Cell           Cut           Observed     Expected   Chi-square
   i            Points          Values       Values       Values
 -----------------------------------------------------------------
   1      4.55        42.1           42       39.25        0.192
   2      42.1        79.6           96      100.21        0.177
   3      79.6        117.          102      104.55        0.062
   4      117.        155.           61       61.01        0.000
   5      155.        192.           41       33.99        1.447
   6      192.        230.           22       20.35        0.134
   7      230.        267.           18       13.08        1.847
   8      267.        305.            6        8.91        0.952
   9      305.        342.            1        6.35        4.512
  10      342.        380.            6        4.70        0.361
  11      380.        417.            4        3.58        0.050
  12      417.        455.            0        2.79        2.791
  13      455.        492.            2        2.22        0.022
 -----------------------------------------------------------------
 Total Chi-square value =    12.5475  Degrees of Freedom = 10.00

Probability of a greater chi-square value, P = 0.25008

 The program has limited capability for pooling.  The user should
 judge the necessity for pooling and if necessary, do pooling by hand.

Density Estimates/Global

 Effort        :    190.0000    
 # samples     :    96
 Width         :    492.3280    
 Left          :    4.553960    
 # observations:   401

 Model  1
    Hazard Rate key, k(y) = 1 - Exp(-(y/A(1))**-A(2))

              Point        Standard    Percent Coef.        95% Percent
  Parameter   Estimate       Error      of Variation     Confidence Interval
  ---------  -----------  -----------  --------------  ----------------------
    D         37.585       3.7671          10.02       30.874       45.754    
    N         902.00       90.408          10.02       741.00       1098.0    
  ---------  -----------  -----------  --------------  ----------------------

 Measurement Units                
 ---------------------------------
 Density: Numbers/Sq. kilometers 
     EDR: meters

 Component Percentages of Var(D)
 -------------------------------
 Detection probability   :  53.1
 Encounter rate          :  46.9

Estimation Summary - Encounter rates

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
                 n       401.00    
                 k       96.000    
                 K       190.00    
                 n/K     2.1105        6.87    95.00  1.8418       2.4184    
                 Left    4.5540    
                 Width   492.33

Estimation Summary - Detection probability

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
 Hazard/Polynomial      
                 m       2.0000    
                 LnL    -2242.1    
                 AIC     4488.2    
                 AICc    4488.2    
                 BIC     4496.2    
                 Chi-p  0.25008    
                 h(0)   0.11189E-03    7.30   399.00 0.96951E-04  0.12914E-03
                 p      0.73743E-01    7.30   399.00 0.63896E-01  0.85108E-01
                 EDR     133.69        3.65   399.00  124.44       143.64

Estimation Summary - Density&Abundance

                         Estimate      %CV     df     95% Confidence Interval
                        ------------------------------------------------------
 Hazard/Polynomial      
                 D       37.585       10.02   330.52  30.874       45.754    
                 N       902.00       10.02   330.52  741.00       1098.0

Generated on 30/04/2023 17:29:56 with Python 3, NumPy 1.23.2, Pandas, ZOOpt 0.4.0, Matplotlib, Jinja 2 ... and AutoDS , with icons from Font Awesome (sources : acdc-2019-nat-ds-params.py, ) .