David
is widely interested in conservation biogeography, but specifically how
spatial information (e.g., GIS data, remote sensing imagery) can be used
to assist and inform conservation planning. His current research interests
include: species distribution modelling, biodiversity monitoring and assessment,
simulation modelling, and GIS. David is particularly interested in questions
pertaining to how to use and improve biodiversity monitoring to make statistical
inferences and support decision making, how to best determine the conservation
value of different landscape units, and how to select and manage candidate
areas as part of a larger reserve network.
Espie,
R.H.M., P.C. James, L.W. Oliphant, I.G. Warkentin and D.J.
Lieske. (2004). Ibis 146: 623-631. Influence of nest-site
and individual quality on breeding performance in Merlins Falco
columbarius. [View abstract][Download paper ]
Lieske,
D.J., I.G. Warkentin, L.W. Oliphant, P.C. James, and R.H.M.
Espie. (2000). Effects of population density on survival in Merlins
(Falco columbarius). Auk 117: 184-193.
[View abstract][Download
paper ]
Lieske,
D.J., L.W. Oliphant, P.C. James, I.G. Warkentin, and R.H.M.
Espie. (1997). Age of first breeding in Merlins (Falco columbarius).
Auk 114: 288-290. [Download paper ]
Submitted
Publications
Lieske,
D.J. and D.J. Bender. Submitted.
Comparative Impact of Spatial Autocorrelation and Location on the
Accuracy and Performance of Species Distribution Models. Ecological
Modelling. [View abstract]
Theses
Ph.D.
Dissertation: Systematic conservation at the regional scale:
the role of species distribution models in priority setting.
[View abstract]
Master's
Thesis: Population dynamics of urban Merlins (Falco columbarius).
Lieske,
D.J. and D.J. Bender. (2006). Visualising species distributions:
the role of geostatistics and GIS in understanding large-scale spatial
variation in breeding birds
[View abstract]
25 June,
2006: Society for Conservation Biology, 20th Annual Meeting (‘Conservation
without Borders’), ‘A comparison of the predictive accuracy
of spatially and non-spatially explicit species distribution models’,
San Jose, California.
6 April,
2006: GIS Research UK (GISRUK) 2006, 14th Annual Meeting, ‘Visualising
species distributions: the role of geostatistics and GIS in understanding
large-scale spatial variation in breeding birds’, University
of Nottingham, UK.
18-22
September, 2004: The Wildlife Society, 11th Annual Meeting, ‘A
comparison of resampling methods for evaluation of resource selection
functions’ (Poster), Calgary, AB, Canada.
18-20
March, 2004: Western Division Canadian Association of Geographers
Annual General Meeting, ‘Biodiversity Assessment Using Species
Richness Hotspots: A Rapid Tool for Conservation Priority Setting?’
(Presentation), Medicine Hat, AB, Canada.
1997:
Prairie Universities Biological Seminars (PUBS), ‘Estimation
of adult survival in merlins (Falco columbarius) and the effect of
population density’ (Presentation), University of Lethbridge,
Lethbridge, AB, Canada.
1996:
Biology 458.3 (Ornithology), ‘Bird population dynamics’
(Presentation), University of Saskatchewan, Saskatoon, SK, Canada.
13-17
August, 1996: Joint Meeting of the American Ornithologist’s
Union and Raptor Research Foundation, ‘Density dependence and
its effect on population growth and reproduction in Merlins’
(Presentation), Boise State University, Boise
Back to Top
Workshop Presentations
27-28
Sept., 2006: ‘Workshop on the R Statistical Package’,
Geomatics and Landscape Ecology Lab (GLEL), Carelton University, Ottawa,
ON, Canada. http://www.ucalgary.ca/~djlieske/R-Carleton
Espie, R.H.M., P.C. James, L.W. Oliphant, I.G. Warkentin, and
D.J. Lieske. 2004. Influence of nest-site and individual quality
on breeding performance in Merlins Falco columbarius. Ibis, 146:
623-631.
We examined the effects of nest-site quality and bird
quality on breeding performance in male and female Merlins Falco
columbarius from a long-term study in Saskatoon, Saskatchewan. In
addition, we tested whether nest-site quality was associated with survival,
as well as lifetime reproductive success (LRS). For females, nest-site
quality had little influence on any of the measures of breeding performance
or survival. Even so, when females switched nest-sites, they tended
to move to better ones. Hatch date was repeatable for the same females
occupying different nest-sites but not for the same sites occupied by
different females. Among males, birds surviving past each age category
tended to occupy nest-sites of higher quality, and LRS was positively
correlated with nest-site quality. The relationship between nest-site
quality and LRS was heavily influenced by the poorest nest-sites. When
males switched nest-sites, they too tended to move to ones of higher
quality. In addition, chick hatch date was repeatable neither for the
same males occupying different sites nor for the same sites occupied
by different males. As with most other raptors, male Merlins provide
most of the food for the pair and their young during the breeding season,
and differences in nest-site quality may have affected the effort needed
by males to secure food. Female Merlins, however, appear still to have
considerable control over the timing of breeding.
Lieske,
D.J., I.G. Warkentin, L.W. Oliphant, P.C. James, and R.H.M. Espie.
(2000). Effects of population density on survival in Merlins (Falco
columbarius). Auk 117: 184-193.
Accurate
estimation of survival probabilities is an important component of population
demographics, and it permits a test of the life-history prediction that
densities influence population dynamics via suppression of survival
rates. As part of a long-term study of urban-nesting Merlins (Falco
columbarius), we estimated survival rates and tested for the effects
of density dependence based on capture histories from 1,354 individuals
(43 males and 110 females caught for the first time as adult breeding
birds, and 597 males and 604 females caught for the first time as locally
produced nestlings). Overall capture probabilities were 0.55 ±
SD of 0.039 per year for adults, 0.10 ± 0.075 per year for juvenile
males, and 0.58 ± 0.23 per year for juvenile females. Mean survival
rate of adults was 0.62 ± 0.11 per year and did not differ significantly
between males and females. Overall juvenile survival rates were 0.23
± 0.032 for males and 0.055 ± 0.012 for females. Band
returns suggest that the discrepancy in survival rates between juvenile
males and females resulted from higher natal dispersal of females rather
than from lower survival. Survival of adults (but not juveniles) was
negatively density dependent, suggesting that density-dependent declines
in survival exerted a regulatory effect on population size.
We examined the effect of age on breeding performance in male and female
Merlins (Falco columbarius) from a natural population using a
long-term data set. In the analysis, we examined whether differences
in chick hatch date and brood size associated with parents of different
ages arose due to selection of superior individuals (differential mortality
hypothesis) or to changes within individuals over time (inadequate experience
hypothesis). In addition, we examined the effect of longevity on production
of recruits and lifetime reproductive success (LRS). In both sexes,
breeding performance improved with age. In females, this was mainly
the result of disproportionate mortality of inferior breeders, with
less evidence to support performance changes within individuals. Among
males, changes in breeding performance with age were largely the result
of improvements within individuals early in their life (between age
1 and 2+). Production of recruits was not dependent on parental age
at the time of breeding for either sex. Recruit production and LRS were
both influenced by longevity, so that longer-lived birds produced more
offspring over their lifetimes and thereby had a greater probability
of producing recruits. The differences between the sexes in terms of
age-dependent breeding performance are likely a consequence of the differing
roles the two parents play in reproduction. Male Merlins provide most
of the food for the pair and their young during the breeding season,
and changes in hunting skill with age may account for individual improvements
in breeding performance.
Lieske,
D.J. and D.J. Bender. Lieske, D.J. and D.J. Bender.
Submitted. Comparative Impact of Spatial Autocorrelation and
Location on the Accuracy and Performance of Species Distribution Models.
Ecological Modelling.
Statistical modelling is a critical tool for predicting species occurrence,
but decisions based on such tools are highly sensitive to the accuracy
of the models and the methods used to produce them. To date, the overwhelming
majority of distribution models disregard both the impact of spatial
autocorrelation (proximity to conspecifics) as well as the possibility
that model relationships may exhibit non-stationarity (depend on geographic
location). We measured the impact of autocorrelation and non-stationarity
using five bird species observed during 7 years of the North American
Breeding Bird Survey. We first built non-spatial occurrence models using
logistic regressions and generalized additive models (GAMs), involving
land cover, climatic and topographic variables. We then compared model
accuracy and goodness of fit for models incorporating spatially-lagged
autocorrelation and localized model estimates (via geographically-weighted
regression, GWR).
Environmental variables were intrinsically autocorrelated, with Moran's
I values in excess of 0.80 at the smallest spatial neighbourhoods. More
elaborate models, based on polynomial or GAM methods, reduced the amount
of autocorrelation in residual errors but were unable to eliminate it.
Consistent with the high levels of residual autocorrelation observed
for the American Crow, the autologistic (ALOG) model not only eliminated
autocorrelation, but substantially improved predictive accuracy (+0.118,
relative to the best GAM model). The remaining species showed a tendency
for only minor changes in predictive accuracy, although from an information-theoretic
perspective, ALOG models were universal improvements over non-spatial
models. Adoption of non-stationary GWR models also improved predictive
accuracy, ranging from +0.078 for the American Crow and +0.008 for the
Purple Finch. The GWR approach resulted in the highest predictive accuracy
for all species except the American Crow, but a comparison of the evidence
ratios of GWR and ALOG models indicated that ALOG models were consistently
favoured over GWR models. While all GWR models exhibited significant
levels of non-stationarity, the mechanisms contributing to this could
only be partially assessed. Based on a generalized estimating equation
(GEE) model, significant within-route correlation occurred for the American
Crow (ρ = 0.54 1 0.26 SE), implicating a broad-scale observer effect
on the probability of observing and recording the presence of this species.
A combination of broad-scale and fine-scale factors were important for
predicting occurrence, but we demonstrate that the incorporation of
spatial factors offers the potential to measure the spatially-explicit
outcomes of intra-specific interactions, and regional differences in
resource usage. We recommend that these methods be considered, particularly
when evidence points to spatially autocorrelated errors, or there are
a priori reasons to suspect geographic variability in resource selection.
Abstracts
for Theses
Lieske,
D.J. 2007. Systematic Conservation at the Regional Scale: the Role
of Species Distribution Models in Priority Setting. Ph.D. Dissertation,
University of Calgary, Calgary, Alberta, 207p.
Present day rates of species loss are of world-wide concern, with species
distribution modelling (SDM) being an important means to identify areas
of high conservation value and direct conservation efforts more efficiently.
The key purpose of this thesis was to implement a full cycle of species
distribution modelling to evaluate the advantages and limitations of
different modelling approaches for identifying candidate areas for conservation.
Key objectives included: (1) assessment of broad- scale spatial pattern
and prevalence of spatial autocorrelation for a set of breeding birds,
observed during the North American Breeding Bird Survey; (2) examination
of the potential for improving predictive accuracy through the incorporation
of autocorrelation and non-stationarity; (3) evaluation of model predictive
accuracy, bias, and generalisability; (4) analysis of the sensitivity
of automated reserve selection to modelling method, reserve selection
algorithm, and information quality.
Assessment of broad-scale pattern indicated that patchy abundance distributions
were common, and nearly universally autocorrelated (24 of 27 species,
or 89%). Modelling results demonstrated that predictive accuracy was
generally related to model complexity. However, the response in goodness-of-fit
was more complicated and depended upon the species in question. The
impact of spatial autocorrelation depended on the species, with the
American Crow benefiting the most from the application of a spatial
autologistic approach. Accuracy assessment, based on random test points,
confirmed that autologistic models provided substantially higher predictive
power, as did the non-stationary models produced by geographically weighted
regression (GWR). From the perspective of generalisability, the simplest
models were the least vulnerable to predictive bias and were also the
most consistently accurate across species. The GWR method was the most
sensitive to the geographic locations used to train the model. The reserve
selection analysis identified that the the combination of a greedy selection
algorithm with high quality information was effective for maximising
the habitat value of the reserve network.
The value of SDMs for conservation planning will be maximised if they
are as biologically plausible as possible. Autologistic regression and
GWR, on a case-by-case basis, can lead to more accurate selection of
high value habitat, thereby improving our ability to support long-term
species persistence.
