Tradeoffs of different types of species occurrence data for use in systematic conservation planning

2006 ◽  
Vol 9 (10) ◽  
pp. 1136-1145 ◽  
Author(s):  
Carlo Rondinini ◽  
Kerrie A. Wilson ◽  
Luigi Boitani ◽  
Hedley Grantham ◽  
Hugh P. Possingham
Keyword(s):  
Conservation Planning ◽  
Systematic Conservation Planning ◽  
Species Occurrence ◽  
Occurrence Data ◽  
Different Types

scholarly journals REBIOMA Data Portal, Tool for Conservation Planning in Madagascar

2018 ◽  
Vol 2 ◽  
pp. e25864
Author(s):  
Rabetrano Tsiky
Keyword(s):  
Species Distribution ◽  
Conservation Planning ◽  
Species Distribution Models ◽  
Continuous Distribution ◽  
Environmental Data ◽  
Easy Access ◽  
Species Occurrence ◽  
Distribution Models ◽  
Occurrence Data ◽  
Data Portal

Recognizing the abundance and the accumulation of information and data on biodiversity that are still poorly exploited and even unfunded, the REBIOMA project (Madagascar Biodiversity Networking), in collaboration with partners, has developed an online dataportal in order to provide easy access to information and critical data, to support conservation planning and the expansion of scientific and professional activities in Madagascar biodiversity. The mission of the REBIOMA data portal is to serve quality-labeled, up-to-date species occurrence data and environmental niche models for Madagascar’s flora and fauna, both marine and terrestrial. REBIOMA is a project of the Wildlife Conservation Society Madagascar and the University of California, Berkeley. REBIOMA serves species occurrence data for marine and terrestrial regions of Madagascar. Following upload, data is automatically validated against a geographic mask and a taxonomic authority. Data providers can decide whether their data will be public, private, or shared only with selected collaborators. Data reviewers can add quality labels to individual records, allowing selection of data for modeling and conservation assessments according to quality. Portal users can query data in numerous ways. One of the key features of the REBIOMA web portal is its support for species distribution models, created from taxonomically valid and quality-reviewed occurrence data. Species distribution models are produced for species for which there are at least eight, reliably reviewed, non-duplicate (per grid cell) records. Maximum Entropy Modeling (MaxEnt for short) is used to produce continuous distribution models from these occurrence records and environmental data for different eras: past (1950), current (2000), and future (2080). The result is generally interpreted as a prediction of habitat suitability. Results for each model are available on the portal and ready for download as ASCII and HTML files. The REBIOMA Data Portal address is http://data.rebioma.net, or visit http://www.rebioma.netfor more general information about the entire REBIOMA project.

Species’ Occurrence Data

2011 ◽  
Author(s):  
A. Townsend Peterson ◽  
Jorge Soberón ◽  
Richard G. Pearson ◽  
Robert P. Anderson ◽  
Enrique Martínez-Meyer ◽  
...  
Keyword(s):  
Species Distributions ◽  
Sampling Bias ◽  
Species Occurrence ◽  
Ecological Conditions ◽  
Broad Applicability ◽  
Occurrence Data ◽  
Data Record ◽  
Different Types ◽  
Correlative Models ◽  
A Site

This chapter discusses the process of transforming a species’ primary occurrence data into a synthetic understanding of the geographic and ecological conditions under which the species occurs. The focus is on correlative models based on occurrence data, since such models can have quite broad applicability. The chapter first considers different types of occurrence data as well as factors that connect the suitability of a site to the existence of a data record documenting the species’ presence or absence at that site. It then examines variations in the geographic and ecological characteristics of species distributions and occurrences, along with sampling bias in geographic and environmental spaces. It also describes the characteristics of absence data before concluding with an assessment of issues of content and availability that affect occurrence data.

Multispecies and Watershed Approaches to Freshwater Fish Conservation

2019 ◽  
Keyword(s):  
Random Forest ◽  
Conservation Planning ◽  
Protected Area ◽  
Regression Trees ◽  
Boosted Regression Trees ◽  
Species Occurrence ◽  
Distribution Modeling ◽  
Occurrence Data ◽  
Forest Models ◽  
Random Forest Models

<em>Abstract</em>.—Systematic conservation planning tools offer powerful and flexible means for addressing the protection of biodiversity in freshwater systems. Tools such as the software Zonation can be used to prioritize streams for protection, restoration, and management of aquatic resources. The flexible nature of these tools allow analyses to be tailored to specific objectives but also introduces uncertainty regarding the effects of selected input options on the rankings of stream segments and the representation of fish species within prioritized streams. The objective of our research was to evaluate the effectiveness of several species distribution modeling techniques (generalized additive models, multivariate adaptive regression splines, boosted regression trees, and random forest models, including an ensemble based on these techniques) for characterizing distributions of fish communities and to identify the influence of different prioritization options of Zonation conservation planning software within five input classes (species occurrence data, removal rule, species weighting, connectivity, and protected area masking) on both the resulting stream segment rankings and the representation of species within priority streams. All combinations of input options were compared based on the correlation and congruence of stream rankings and the mean richness of species, minimum level of species representation, and representation of rare species within streams across priority levels. Of the distribution modeling types we evaluated, boosted regression trees performed the best, followed closely by random forest models. The use of an ensemble approach allowed for the largest number of species with robust predicted distributions. Our results also suggested that protected area masking had the largest effects on conservation priority results, followed by choice of removal rule, while species occurrence data type had limited impacts. The information contained in this chapter is meant to aid planners in understanding how their selection of conservation planning inputs is likely to impact results.

Species occurrence data from the Range-Wide Bull Trout eDNA Project

2017 ◽  
Author(s):  
Michael K. Young ◽  
Daniel J. Isaak ◽  
Kevin S. McKelvey ◽  
Michael K. Schwartz ◽  
Kellie J. Carim ◽  
...  
Keyword(s):  
Bull Trout ◽  
Species Occurrence ◽  
Occurrence Data

Applying systematic conservation planning to improve the allocation of restoration actions at multiple spatial scales

2021 ◽  
Author(s):  
Ben L. Gilby ◽  
Andrew D. Olds ◽  
Christopher J. Brown ◽  
Rod M. Connolly ◽  
Christopher J. Henderson ◽  
...  
Keyword(s):  
Conservation Planning ◽  
Spatial Scales ◽  
Systematic Conservation Planning ◽  
Multiple Spatial Scales

scholarly journals Prior specification in Bayesian occupancy modelling improves analysis of species occurrence data

2018 ◽  
Vol 93 ◽  
pp. 333-343 ◽  
Author(s):  
Charlotte L. Outhwaite ◽  
Richard E. Chandler ◽  
Gary D. Powney ◽  
Ben Collen ◽  
Richard D. Gregory ◽  
...  
Keyword(s):  
Species Occurrence ◽  
Occupancy Modelling ◽  
Prior Specification ◽  
Occurrence Data

CONSISTENCY BETWEEN ORDINATION TECHNIQUES AND DIVERSITY MEASUREMENTS: TWO STRATEGIES FOR SPECIES OCCURRENCE DATA

Ecology ◽  
2003 ◽  
Vol 84 (1) ◽  
pp. 242-251 ◽  
Author(s):  
Raphaël Pélissier ◽  
Pierre Couteron ◽  
Stéphane Dray ◽  
Daniel Sabatier
Keyword(s):  
Species Occurrence ◽  
Occurrence Data ◽  
Ordination Techniques

scholarly journals INVESTIGATING CROSS CONGRUENCE BETWEEN BUTTERFLY TAXA AND ECOLOGICAL COMMUNITY WITHIN THE FRAMEWORK OF SYSTEMATIC CONSERVATION PLANNING: A CASE STUDY FROM LESSER CAUCASUS ECOREGION OF TURKEY

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Banu Kaya özdemirel
Keyword(s):  
Protected Areas ◽  
Biodiversity Conservation ◽  
Site Selection ◽  
Conservation Planning ◽  
Environmental Parameters ◽  
Systematic Conservation Planning ◽  
Ecological Community ◽  
North Eastern ◽  
Lesser Caucasus

Cross taxa congruence was investigated between butterfly taxa and ecological community for fine spatial scale (10 × 10 km² UTM grids) in north-eastern part of Turkey. The study area was evaluated within the scope of systematic conservation planning, and analyses were performed for sets of priority protected areas composed using complementarity-based site selection software Marxan. Cross taxa congruence was subsequently examined both in species richness and ecologic complementarity. Accordingly, it has been observed that the cross-taxon congruence between butterfly taxa and ecological community was relatively better than the results of previous studies. Another remarkable finding is that ecological community was a more robust surrogate than butterfly taxa. Although the results are valuable for conservation studies, they highlight the fact that a simple surrogate-based site selection would be inadequate to represent overall biodiversity.  The weakness of congruence patterns among surrogates would also lead to gaps in biodiversity conservation. These findings therefore draw attention to the necessities of incorporating surrogates of distinct ecology or some other surrogates like environmental parameters into conservation planning. Otherwise, there may be mistakes regarding species representation and the vast majority of species may be misrepresented in protected areas and protected area plans. At this point, it should be emphasized that understating cross taxa congruence and/or relationships is a key component for efficient biodiversity conservation.

scholarly journals Are trade-offs between flexibility and efficiency in systematic conservation planning avoidable ?

2019 ◽  
Author(s):  
Sabrine Drira ◽  
Frida Ben Rais Lasram ◽  
Tarek Hattab ◽  
Yunne Jai Shin ◽  
Amel Ben Rejeb Jenhani ◽  
...  
Keyword(s):  
Conservation Planning ◽  
Large Body ◽  
Efficient Solutions ◽  
Reserve Selection ◽  
Systematic Conservation Planning ◽  
Distribution Models ◽  
Precise Control ◽  
Trade Offs ◽  
Selection Framework ◽  
Selection Of

AbstractSpecies distribution models (SDMs) have been proposed as a way to provide robust inference about species-specific sites suitabilities, and have been increasingly used in systematic conservation planning (SCP) applications. However, despite the fact that the use of SDMs in SCP may raise some potential issues, conservation studies have overlooked to assess the implications of SDMs uncertainties. The integration of these uncertainties in conservation solutions requires the development of a reserve-selection approach based on a suitable optimization algorithm. A large body of research has shown that exact optimization algorithms give very precise control over the gap to optimality of conservation solutions. However, their major shortcoming is that they generate a single binary and indivisible solution. Therefore, they provide no flexibility in the implementation of conservation solutions by stakeholders. On the other hand, heuristic decision-support systems provide large amounts of sub-optimal solutions, and therefore more flexibility. This flexibility arises from the availability of many alternative and sub-optimal conservation solutions. The two principles of efficiency and flexibility are implicitly linked in conservation applications, with the most mathematically efficient solutions being inflexible and the flexible solutions provided by heuristics suffering sub-optimality. In order to avoid the trade-offs between flexibility and efficiency in systematic conservation planning, we propose in this paper a new reserve-selection framework based on mathematical programming optimization combined with a post-selection of SDM outputs. This approach leads to a reserve-selection framework that might provide flexibility while simultaneously addressing efficiency and representativeness of conservation solutions and the adequacy of conservation targets. To exemplify the approach we a nalyzed an experimental design crossing pre- and post-selection of SDM outputs versus heuristics and exact mathematical optimizations. We used the Mediterranean Sea as a biogeographical template for our analyses, integrating the outputs of 8 SDM techniques for 438 fishes species.

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