| Title: | Extinction Date Estimation from Sighting Records |
|---|---|
| Description: | Estimates the historic date of extinction of a species from a time-ordered record of sighting events. Given a table of sighting counts per year, computes extinction date estimators from the sighting-record literature: optimal linear estimation and its Weibull extreme-value persistence test (Roberts & Solow, 2003; Solow, 2005), constant-rate and declining-rate persistence tests (Solow, 1993), a sighting-rate persistence test comparable across records with different observation periods (McInerny, Roberts, Davy & Cribb, 2006), a classical confidence interval on the end of a temporal range (Strauss & Sadler, 1989), a truncation-point extrapolation (Robson & Whitlock, 1964), and a combinatorial persistence test based on inclusion-exclusion over sighting-gap occupancy (Burgman, Grimson & Ferson, 1995). Also implements a nonparametric endpoint test (Solow & Roberts, 2003), a sighting-interval trend index (Jarić & Ebenhard, 2010), and reliability-adjusted inference for uncertain records (Jarić & Roberts, 2014). Every estimator is built on a validated input object and returns a common result class with, where defined, a point estimate, a confidence interval, or a full p-value curve. |
| Authors: | Rodrigo Fonseca Villa [aut, cre] (ORCID: <https://orcid.org/0009-0005-2938-2270>) |
| Maintainer: | Rodrigo Fonseca Villa <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 0.2.0 |
| Built: | 2026-09-19 23:23:00 UTC |
| Source: | https://github.com/rodrigosqrt3/ede |
Computes the probability that, if sighting events were distributed uniformly at random over the candidate observation window, a run of empty periods at least as long as the largest observed run would occur. Uses an inclusion-exclusion (Stirling-number) argument on the occupancy of time bins by sighting events (equation 4 of the source paper).
burgman1995(sd, alpha = 0.05, test_year, data_out = FALSE)burgman1995(sd, alpha = 0.05, test_year, data_out = FALSE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be supplied as a number. |
data_out |
If |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance.
Burgman, M. A., Grimson, R. C., & Ferson, S. (1995). Inferring threat from scientific collections. Conservation Biology, 9(4), 923-928.
Common S3 result class returned by every estimator in this package.
A list with components:
Point estimate, or NA if not defined for this method.
Confidence interval bounds, or NA if not defined.
Either "two-sided" or "one-sided".
Character string identifying the estimator.
Significance level used to compute the estimate.
Modifies the constant-rate Solow model by assigning a reliability in
[0, 1] to each occupied sighting time. Implements equations 4, 6, and
8-10 of Jaric & Roberts (2014), returning the reliability-adjusted point
estimate and upper confidence bound.
jaric_roberts2014(sd, reliability, alpha = 0.05)jaric_roberts2014(sd, reliability, alpha = 0.05)
sd |
A sighting_data object. This method currently requires binary counts (zero or one) because reliability is assigned to individual observations. |
reliability |
Numeric reliabilities in |
alpha |
Significance level, in (0, 1), for the upper confidence bound. |
An ede_estimate object.
Jaric, I., & Roberts, D. L. (2014). Accounting for observation reliability when inferring extinction based on sighting records. Biodiversity and Conservation, 23(11), 2801-2815.
Tests persistence from the average interval between distinct sighting times,
optionally adjusted by the mean trend in consecutive interval lengths. The
trend-adjusted calculation implements equations 5-6 of Jaric & Ebenhard
(2010); trend = FALSE implements equations 3-4.
jaric2010(sd, alpha = 0.05, test_year, data_out = FALSE, trend = TRUE)jaric2010(sd, alpha = 0.05, test_year, data_out = FALSE, trend = TRUE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be supplied as a number. |
data_out |
If |
trend |
Logical. If |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance. The latter contains index p-values; the
column name is retained for compatibility with EDE 0.1.0.
Jaric, I., & Ebenhard, T. (2010). A method for inferring extinction based on sighting records that change in frequency over time. Wildlife Biology, 16(3), 267-275.
A modification of the Solow (1993) persistence test that conditions on
the sighting rate observed up to the last sighting, n / tn, instead of
on the length of the whole observation window. This makes the test
comparable across records with very different total observation
periods: species discovered recently and species discovered long ago,
but sighted at the same rate, are inferred extinct after the same
length of silence.
mcinerny2006(sd, alpha = 0.05, test_year, data_out = FALSE)mcinerny2006(sd, alpha = 0.05, test_year, data_out = FALSE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be later than the last sighting. |
data_out |
If |
Following the source paper, the first sighting is used to anchor the
time origin (t = 0) rather than counted as one of the n sighting
events being tested, so the count entering the formula is n - 1,
where n is the number of distinct sighting times with a positive
count.
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance.
McInerny, G. J., Roberts, D. L., Davy, A. J., & Cribb, P. J. (2006). Significance of sighting rate in inferring extinction and threat. Conservation Biology, 20(2), 562-567.
Estimates the extinction date from the sighting times with a positive count, using the best linear unbiased estimator (BLUE) of Roberts & Solow (2003) under a Weibull-type record-value model for the spacing of the largest order statistics.
ole(sd, alpha = 0.05, k = NULL)ole(sd, alpha = 0.05, k = NULL)
sd |
A sighting_data object. |
alpha |
Significance level for the confidence interval, in (0, 1). |
k |
Number of most recent sighting events to use. Counts greater than one are treated as independent events at the recorded time. By default, all sighting events are used. Must be at least 3. |
An ede_estimate object.
Roberts, D. L., & Solow, A. R. (2003). Flightless birds: When did the dodo become extinct? Nature, 426(6964), 245. Solow, A. R. (2005). Inferring extinction from a sighting record. Mathematical Biosciences, 195(1), 47-55.
Estimates the extinction date by jackknife bias correction of the most
recent sighting. If the two most recent distinct sighting times are
t[n-1] and t[n], the estimate is t[n] + (t[n] - t[n-1]).
robson1964(sd, alpha = 0.05)robson1964(sd, alpha = 0.05)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1), for the approximate one-sided confidence interval. |
An ede_estimate object.
Robson, D. S., & Whitlock, J. H. (1964). Estimation of a truncation point. Biometrika, 51(1/2), 33-39.
Builds the common input object used by every estimator in the package: a time-ordered table of sighting counts, checked for the conditions each estimator in the sighting-record literature assumes (numeric, non-negative, no duplicated times).
sighting_data(data, time_col = 1L, count_col = 2L)sighting_data(data, time_col = 1L, count_col = 2L)
data |
A data frame or matrix. By default the first column is read as time (e.g. year) and the second as the number of sightings recorded at that time. The earliest supplied time defines the observation origin; include an initial zero-count row when observation began before the first sighting. |
time_col, count_col
|
Column name or position for time and sighting count. |
An object of class sighting_data: a data frame with columns
time and count, sorted by time.
Tests the null hypothesis that a species persisted to a candidate time
using only the two most recent distinct sighting times. For candidate time
T, the p-value is (t[n] - t[n-1]) / (T - t[n-1]).
solow_roberts2003(sd, alpha = 0.05, test_year, data_out = FALSE)solow_roberts2003(sd, alpha = 0.05, test_year, data_out = FALSE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be supplied as a number. |
data_out |
If |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance. The latter contains p-values; the column
name is retained for compatibility with EDE 0.1.0.
Solow, A. R., & Roberts, D. L. (2003). A nonparametric test for extinction based on a sighting record. Ecology, 84(5), 1329-1332.
Parametric test of the null hypothesis that a species was still extant at a candidate test year, under a stationary Poisson sighting process.
solow1993(sd, alpha = 0.05, test_year, data_out = FALSE)solow1993(sd, alpha = 0.05, test_year, data_out = FALSE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be supplied as a number. |
data_out |
If |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance.
Solow, A. R. (1993). Inferring extinction from sighting data. Ecology, 74(3), 962-964.
Conditional test of the null hypothesis that a declining species was still extant at a candidate test year, under a non-stationary Poisson process with an exponentially declining rate.
solow1993b(sd, alpha = 0.05, test_year, data_out = FALSE)solow1993b(sd, alpha = 0.05, test_year, data_out = FALSE)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). |
test_year |
Latest year to test. Must be later than the last sighting. |
data_out |
If |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance.
Solow, A. R. (1993b). Inferring extinction in a declining population. Journal of Mathematical Biology, 32(1), 79-82.
Tests persistence using the Weibull extreme-value model for the k most
recent sighting events. This is the hypothesis-test counterpart of
ole(). For a candidate time T, the p-value is equation 16 of Solow
(2005). Earlier EDE versions incorrectly described a Fisher-gap calculation
as a sighting-effort-weighted method from this paper.
solow2005(sd, alpha = 0.05, test_year, data_out = FALSE, k = NULL)solow2005(sd, alpha = 0.05, test_year, data_out = FALSE, k = NULL)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). Persistence is rejected for
the first candidate year at which the p-value falls to
or below |
test_year |
Latest year to test. Must be supplied as a number. |
data_out |
If |
k |
Number of most recent sighting events to use. Counts greater than one are treated as independent events at the recorded time. By default, all sighting events are used. Must be at least 3. |
An ede_estimate object, or (if data_out = TRUE) a data frame
with columns time and chance.
Solow, A. R. (2005). Inferring extinction from a sighting record. Mathematical Biosciences, 195(1), 47-55.
Unbiased point estimator and classical confidence interval for the true endpoint of a temporal range, derived from the distribution of the sample range under a uniform occurrence model.
strauss1989(sd, alpha = 0.05)strauss1989(sd, alpha = 0.05)
sd |
A sighting_data object. |
alpha |
Significance level, in (0, 1). |
An ede_estimate object containing the unbiased point estimate and a one-sided confidence interval.
Strauss, D., & Sadler, P. M. (1989). Classical confidence intervals and Bayesian probability estimates for ends of local taxon ranges. Mathematical Geology, 21(4), 411-427.
Same estimator as strauss1989(), evaluated over a grid of alpha values
from 0.01 to 1, for plotting the confidence curve instead of a single
bound.
strauss1989_curve(sd)strauss1989_curve(sd)
sd |
A sighting_data object. |
A data frame with columns time and chance (1 - alpha).