10.5061/DRYAD.QT3C9
Carvalho, Silvia B.
University of Porto
Gonçalves, João
University of Porto
Guisan, Antoine
University of Lausanne
Honrado, João
University of Porto
Data from: Systematic site selection for multispecies monitoring networks
Dryad
dataset
2015
systematic conservation planning
multi-species
herptiles
species trends
reptile
environmental stratification
field survey effort
amphibian
2015-08-31T20:12:43Z
2015-08-31T20:12:43Z
en
https://doi.org/10.1111/1365-2664.12505
4922686 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
The importance of monitoring biodiversity to detect and understand changes
throughout time and to inform management is increasingly recognized.
Monitoring schemes should be globally unified, spatially integrated across
scales, long term, and cost-efficient. We propose a framework to design
optimized multispecies-targeted monitoring networks over large areas. The
method builds upon previous developments on systematic conservation
planning in terms of optimizing resource allocation in space, and
comprises seven steps: (a) determine which questions will be addressed,
(b) define species to be monitored, (c) compile occurrence data for all
defined species, (d) predict the overall distribution of each species, (e)
collect relevant environmental data and identify homogeneous strata, (f)
set targets for the minimum number of monitoring sites per species and/or
stratum and (g) identify optimal monitoring sites. We tested whether the
monitoring networks designed with our framework have increased performance
when compared to networks obtained with simple-random or stratified-random
sampling by using a set of different indicators. To that end, we designed
monitoring networks using optimized and non-optimized sampling schemes,
applied to a case study in Portugal, where the goal was to design a
monitoring network for amphibians and reptiles, to complement the one
currently established in Spain. Results allowed us to conclude that
monitoring networks designed with our method tend to outperform the
non-optimized ones, in terms of higher species diversity (i.e. higher
number of species and equity across monitoring sites), higher
representation of environmental strata, and particularly higher coverage
of rare species, with less survey effort. Synthesis and applications. We
developed a framework to allocate monitoring sites for multiple species at
broad scales using predictive models and optimization algorithms currently
applied in systematic conservation planning. This framework presents field
survey cost-efficiency advantages when compared to other standard sampling
designs and can significantly contribute to improving the design of
monitoring schemes. Thus, we recommend its application to design new
multispecies monitoring networks or to extend existing ones.
Marxan FilesInput files used in the Marxan software to derive optimized
monitoring networks for the four stratification methods - No
stratification (NS), Protection stratification (PA), Environmental
Stratification (ENV), and Environmental and Protection stratification
(ENVPA); and the three target scenarios: T10, T30 and
T50Marxan_Files.zipCarvalho_S_et_al_2015-JAE_DATA_&_RCODEInput
files and r scripts used to derive non-optimized monitoring schemes for
the four stratification strategies (No stratification (NS), Protection
stratification (PA), Environmental Stratification (ENV), and Environmental
and Protection stratification (ENVPA)) and the three target scenarios
(T10, T30 and T50); and to evaluate the performance of both optimized and
non-optimized networks using the different indicators.
Portugal