A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation.

Efficient biodiversity conservation requires that limited resources be allocated in accordance with national responsibilities and priorities. Without appropriate computational tools, the process of determining these national responsibilities and conservation priorities is time intensive when considering many species across geographic scales. Here, we have developed a computational tool as a module for the ArcGIS geographic information system. The ArcGIS National Responsibility Assessment Tool (NRA-Tool) can be used to create hierarchical lists of national responsibilities and priorities for global species conservation. Our tool will allow conservationists to prioritize conservation efforts and to focus limited resources on relevant species and regions. We showcase our tool with data on 258 bird species and various biophysical regions, including Environmental Zones in 58 Asian countries and regions. Our tool provides a decision support system for conservation policy with attractive and easily interpretable visual outputs illustrating national responsibilities and priorities for species conservation. The graphical output allows for smooth integration into assessment reports, such as the European Article 17 report, the Living Planet Index report, or similar regional and global reports.

Introduction

State signatories to the Convention on Biological Diversity must not only define their own strategy to protect biodiversity, they must also set their own priorities considering available resources. Even more importantly, biodiversity rich countries with few resources may be able to justify the demand of additional resources for international institutions. There is still room to increase the global efficiency of biodiversity conservation by aligning national conservation actions with current knowledge of species distribution ranges and habitats. Species and habitats are not equally distributed in and across countries and continents. Some are widespread with a distribution area spanning several countries, while others have a small distribution range concentrated within a single country. The political responsibility for the conservation of any one species is rarely completely clear, which impacts the efficiency of protection measures [1]. Thus far, conservation efforts have been based on the use of red lists, a popular indicator of the threat status of a species and an easy way to define conservation priorities, especially on finer geographic scales. Red lists can facilitate simple explanations of the complex phenomenon of “endangerment” [2, 3], resulting in high public acceptance [4-6]. However, red lists are at best a suboptimal tool for setting conservation priorities in a country or region since a threat status does not always accurately reflect conservation requirements across the entire distribution range [7-12].

A complementary concept is that of national responsibilities (NRs). National responsibilities consider the size of the distribution range of a species within a country to be proportional to that country’s conservation responsibilities. Hence, a country covering a large proportion of the total distribution area of a threatened species would have a greater responsibility for the protection of this species then a similarly sized country that contains a smaller proportion of the total distribution area of this species. A methodological review of the existing approaches to the determination of national responsibilities [13] has shown the drawbacks of existing methods, especially with regard to data needs, comparability across countries, and the disentanglement of red lists and national responsibilities. Generally, the concept of national responsibility as a spatial prioritization tool takes into consideration the variability of contributions to overall species or habitat viability and persistence across distribution ranges. Hence, particular parts of species or habitat ranges (i.e., areas with high abundance of a species) are more important than others for the global conservation of a species. The concept of national responsibility captures the quality of irreplaceability that defines certain parts of a distribution range [14], and serves as a proxy for the global persistence probability of species or habitats when a particular area is lost.

National responsibility assessments identify which country or countries should lead conservation actions directed at particular species and habitats. Once national responsibilities have been determined, countries can employ additional tools that utilize the available information to select species, habitats, and regions in which practical conservation actions should be prioritized (Table 1).

Table 1

Approaches for the determination of conservation priorities and respective references.

Approach	References
Combined use of spatial distributions of species, habitats, ecosystems and their services, connectivity measures, species compositions and economic costs	[15–20]
Spatial characteristics of species distributions	[21, 22]
Community composition	[23]
Patterns of genetic and morphological variation	[24, 25]
Geographic and evolutionary rarity	[26, 27]
Trait or phylogenetic distinctiveness	[28]
Trait‐based metrics	[29]
Movement behavior	[30]
Conservation condition, biodiversity value, pressure factor, and cover relevance of habitat types	[31]
Social and ecological dynamism	[32]
Human disturbances	[33]
Complementary comparison of flagship and background species	[34]
Multivariate statistics based on variables such as state of knowledge, forest loss, forest loss acceleration, protected area size and relative species diversity	[35]

Hence, determining national responsibilities [36] and conservation priorities (CPs, [37]) allows nations to take action where it is most urgently needed and helps decision makers to allocate resources efficiently towards species monitoring, management, and protection [1, 38]. For example, this process could support the United Nations Environment Programme (UNEP) in the identification of biodiversity targets for developmental programs. Entities such as the Intergovernmental Science-Policy Platform for Biodiversity and Ecosystem Services (IPBES), the Group of Earth Observations Biodiversity Observation Network (GEO BON), and international non-governmental organizations could use assessments of national responsibilities and conservation priorities as a basis for evaluating which regions would reap the greatest benefit from capacity-building efforts [1, 7].

The sheer number of species, known and unknown, makes it nearly impossible to manually determine national responsibilities and conservation priorities across all countries and regions. Such a global assessment would be highly useful for directing international and domestic conservation policy, and since a manual assessment is not feasible, a tool is needed to automate the process. To be successful, the tool must be able to overlay species or habitat distributions onto biogeographic regions with political boundaries in a geographic information system (GIS) [7, 39, 40]. Furthermore, for comparability between regions and applicability on different ecological scales or administrative levels, such an approach needs to be freely scalable to account for the size of administrative boundaries [7, 36].

Although there are highly specialized instruments for spatial prioritization, allocation of conservation efforts and spending, and reserve planning (e.g. Marxan [17] and Zonation [15]), their application at global scale is difficult and they do not provide a clear definition of the conservation responsibilities of particular regions or countries.

Here, we describe a GIS tool to determine national responsibilities and conservation priorities globally. The method underlying the GIS tool [36, 37] is limited only by the availability of distribution data for species and habitats, and is much less data demanding than other approaches, while still scientifically robust [13]. The ArcGIS National Responsibility Assessment Tool (NRA-Tool) uses freely available shapefiles of species distributions, environmental zones, and political borders to automate the analysis for a large set of species for which data are available. Data sources include the Spatial Data & Mapping Resources and the Red List database from the IUCN [41, 42].

We explain the GIS module’s user interface and illustrate the general concept and functionality with data from four species of shrews, which have their distribution center either only in Europe or are widespread across Eurasia. As a case study, we also provide national responsibility assessments for 258 bird species of Asia.

Methods

Implementation of the national responsibility and conservation priority method

In general, our method can be used to assess the responsibility of an administrative unit on any spatial scale. The scale of analysis will be defined by the “focal area” (FA; often the country for which a responsibility assessment must be made) and the “reference area” (RA). The reference area is the region in which the focal area must be fully contained and the size to which the focal area relates. For the assessment of national responsibilities, a sub-continental (e.g. Asia, Europe, North and South America), continental (e.g. Eurasia, Australia) or global scale is appropriate. For some applications it may be useful to choose a reference area that is defined by a common legal and economic framework and differs in shape and extent from all continents and sub-continents (e.g. the European Union). To avoid pitfalls caused by special constellations, we recommend using the global scale as a reference area in the following cases: (i) different borderlines for a subcontinent (e.g. Europe including parts of Turkey and Kazakhstan versus an extent based strictly on national borders) [43]), (ii) inclusion or exclusion of parts of a country that are on other continents (e.g., the overseas departments and territories of France), or (iii) countries divided by a sub-continental border (e.g. Russia).

Examples of the different tasks during the process of GIS analysis are shown in Figs 1–3 and Figs 5 and 6, while the identification of national responsibilities and conservation priorities implemented in the NRA tool is based on the decision tree shown in Fig 4 and the scores or classes derived from them in Table 2.

Fig 1

Task 1 –find data on the distribution of focal species.

Here shown for four species of shrews across Europe: Crocidura sicula (endemic in Sicily, Italy), Sorex coronatus with a regional rather closed distribution, Sorex alpinus (disjunct distribution), and Sorex minutus, widely spread across Eurasia (Sources: [).

Fig 3

Task 3 –determine the ratio of the focal area of the country and the reference area (here FA = France; European part of the territory only; RA = Europe, sub-continental border is based on national borderlines; sources: [43–46]).

Fig 5

Task 4 –determine the overlap between the different types of distributions of the four shrew species, the different Global Environmental Zones, and the reference area of Europe (sources: [43–46, 50]).

Fig 6

Task 5 –define the ratio of the parts of the distribution of the focal species and the Global Environmental Zones contained in the focal area of the country France (European part of the territory only) and the respective parts of the distribution of the focal species and the Global Environmental Zones fully contained in the reference area of Europe (sources: [43–46, 50]).

Fig 4

Decision tree for identifying national responsibilities in species conservation after [36] (modified).

Step one is to select the taxonomic unit. Step two is to determine the distribution pattern of the species: “local” defines a species with a patchy distribution within one biogeographic region (in the case of Europe, sensu European Habitats Directive, Council Directive 92/43/EEC), and “wide” refers to a species distribution spanning more than one biogeographic region. The third category is “regional”, wherein two-thirds of the distribution area of a species is located in one biogeographic region. Examples can be found in [. The final step is to calculate the proportional distribution of a species in the focal area. Two proportions are calculated–the expected distribution proportion (DPexp) and the observed distribution proportion (DPobs).

Table 2

Classes of conservation priorities based on scores (in brackets) for national responsibility and IUCN threat status following [36].

IUCN Category	National responsibility
	Very high	High	Medium	Basic
Extinct in the wild	Class 1 (25)	Class 1 (20)	Class 2 (17)	Class 2 (16)
Critically Endangered	Class 1 (22)	Class 2 (17)	Class 2 (14)	Class 2 (13)
Endangered	Class 1 (20)	Class 2 (15)	Class 3 (12)	Class 3 (11)
Vulnerable	Class 2 (18)	Class 2 (13)	Class 3 (10)	Class 4 (9)
Near Threatened	Class 2 (16)	Class 3 (11)	Class 4 (8)	Class 4 (7)
Least Concern	Class 3 (11)	Class 4 (6)	Class 4 (3)	Class 4 (2)
Data Deficient Not Evaluated

Task 2 –check the suitability of the chosen reference area.

Here, the distribution area of the focal species Sorex coronatus is fully contained in the reference area Europe (sub-continental border is based on national borderlines; Sources: [).

Schmeller et al. [13] reviewed different approaches for determining national responsibilities and suggested a standardized method that is freely scalable and can provide an improved basis for setting conservation priorities. The method is also applicable to habitats or ecosystems [7] and comprises three steps (Fig 4).

The expected distribution proportion (DPexp) in the focal area is the ratio of the distribution area of a species inside the reference area (sensu Schmeller et al. [36, 37]) to the total area of the reference area (Eq 1); the observed distribution proportion (DPobs) in the focal area is the ratio of the distribution area of the species in a focal area to the total area of the focal area (Eq 2) [36, 37, 47].

To determine conservation priorities, the national responsibility assessment is combined with an assessment of the IUCN threat status of species [36, 48, 49] (Table 2).

An advantage of the approaches proposed in [36] is the integration of biogeographical information, such as regions defined by co-occurrence of species, distribution of large biomes, or climatic factors, into the delineation of ecological zones [7, 40] (Figs 5 and 6).

Our analysis in this example reveals that France has a high responsibility score for Sorex coronatus because most of the distribution of this species is within the territory of France (compare Fig 4 and Table 2). For two species (Sorex alpinus, Sorex minutus) France has a low responsibility score. Sorex alpinus shows preferences for alpine habitats that are less common in the focal area (France) but comprise large regions of Switzerland and Austria. For Sorex minutus, Russia scores very high on the responsibility metric because it includes a large segment of this widespread generalist’s range. France has no responsibility for Crocidura sicula, which is endemic in Sicily, Italy. However, because this shrew can be found only on Sicily and a few surrounding small islands, Italy has a high national responsibility score.

Description of the National Responsibility Assessment Tool

Structure

The NRA-Tool needs four predefined layers with polygons to allow assessments on a national to global scale (S1 File). The four types of basic layers are (i) files showing the geographical distribution of the focal species (FS, e.g. Fig 1), (ii) the physical geographical regions or spatial units that are either described by co-occurrence of floral and faunal elements (biogeographical unit, BU) or by a combination of bioclimatic factors (ecological unit/region; EcU) that substantially determine the distribution (Fig 5), (iii) the borders of the reference area, and (iv) the focal area(s) to be analyzed. Instead of having a separate file for the reference area, the biogeographical or ecological unit/region files can be used to define these borders. All GIS layers should be in WGS84 projection for global analyses [51] or in the same region-specific equal area projection for analyses on a smaller scale to provide comparable results. Below, we outline the main components of the tool.

Provision and preparation of taxonomic units or habitat units

Analyses of regionalized responsibilities, in general, are based on an assessment of the spatial overlap between the geographical distributions of species (taxonomic unit, TU) or special habitats of conservation concern and administrative units [36, 37]. What is important is that an area can be clearly delineated as a polygon for the unit of concern (distribution area), based on available data. Examples of sources include the webservices of IUCN (https://www.iucnredlist.org/) and Map of Life (https://www.mol.org) [52]. The distribution of each species or habitat category must be available as a separate layer for use in our tool. Files downloaded from the IUCN webserver require additional processing so that data for each species is separated into a unique shapefile, and renamed by adding the prescript “s-” (following the naming convention described in more detail in the section “Technical requirements”). These shapefiles must be accompanied by an ASCII text file that contains the species names separated by semicolons (see S3 File for example).

Focal area and reference area

The focal area is the geographical area for which conservation priorities are determined. For national responsibility assessments, the borders of an administrative unit, such as a country or province, should be used to demarcate the focal area. The focal area must be completely enclosed by the reference area.

The reference area defines the extent and serves as a reference to determine whether the focal area contains a higher percentage of the distribution range than expected by the size of the focal area. The selection of the reference area will depend on the goal of the assessment. If the goal is to define priorities for a particular geographic region, the reference area should be the combined spatial extent of all biogeographical units in which at least one of the assessed species occurs. If the goal is to determine the national responsibility of a lower-level administrative unit, such as a province, then the reference area can be a higher-level administrative unit, such as a country. Results are comparable only within the same assessment.

All three layers described above (reference area, biogeographical unit, focal area) should contain at least one polygon. Each polygon should relate to and be sufficiently described by one field in the table of attributes. In most cases, the biogeographical unit layer and focal area layer (e.g. countries) will have more than one unit/polygon covered by the reference area.

The biogeographical unit files we provide with our tool consist of polygons of a lower-level scale that can be grouped by a higher-level attribute. The higher-level attributes can be used to create larger polygons by a simple dissolve procedure that aggregates all objects with the same attribute in the next highest level unit relative to the original scale. These new, enlarged polygons can then be used as natural reference areas based on biogeographical units. Alternatively, geographical units, such as continental borders, or administrative units, such as the member states of the EU, can be used for the creation of the reference area polygon.

Assessing the distributions

When distribution data have been obtained for the selected species, distribution areas are designated as “local,” “regional,” or “wide” based on the number of biogeographical units covered by the distribution area of the selected species. This step follows the recommendations of Schmeller et al. [1, 7]. Alternatively, categorization can be based on the area of overlap with biogeographical units (see S2 File for examples).

Two classifications of biogeographical units are available in the NRA-Tool for terrestrial ecosystems: The Terrestrial Ecoregions of the World (TErW, [53]) and the Global Environmental Zones (GEnZ, [50]). Both classifications subdivide their first level units (Terrestrial Ecoregions resp. Global Environmental Zones) into sub-regions of a lower geographical extent based on additional regional criteria. Following arguments provided by Schmeller et al. [1], we strongly suggest using GEnZ [50, 54] as biogeographical units for implementation at the continental and global scale. Notably, the NRA-Tool also provides a spatial assessment of conservation priority in the form of maps and associated attribute tables for all focal areas.

Our tool is not limited to analyses of terrestrial ecosystems. The architecture allows for any ecosystem classification, provided the layers consist of a complete set of spatially inclusive and comprehensive polygons fully covering the reference area. Thus, the NRA-Tool can be used to perform global assessments of species living only in freshwater ecosystems or even species that are exclusively marine [55, 56].

Workflow

The workflow (Fig 7) starts with the selection of the taxonomic unit (TU) to be analyzed from the dataset of all taxonomic units. The distribution pattern is then classified as “local,” “regional,” or “wide” based on the shapefiles of the reference area and the focal areas, and the distribution of the taxonomic unit with respect to the focal species. In the second step, the NRA-Tool calculates the expected and observed distribution areas and determines national responsibility scores and conservation priorities for the focal species as described above. As an output, conservation priority classes are assigned to all or selected countries or regions for the focal species. The results are provided as maps (shapefiles) with respective attribute tables containing the values of national responsibility scores and/or conservation priority of the assessed focal species. The tool also provides the same information and a short summary in an ASCII text file that can be stored digitally for further analyses or visualization.

Fig 7

The workflow of the National Responsibility Assessment Tool (IUCN: International Union for Conservation of Nature; NR: National Responsibility; CP: Conservation Priority; DPexp: expected distribution proportion, and DPobs: observed distribution proportion).

The NRA-Tool offers two options for classifying distribution patterns: the Polygon Count-Approach (PC-A) [1, 7] and the Polygon Area-Approach (PA-A). The difference between the Polygon Area-Approach and the Polygon Count-Approach option is the way biogeographic units are related to the focal species distributions and focal areas in regard to the determination of distributions of selected species as “local”, “regional”, or “wide” (for examples see S2 File).

In the Polygon Count-Approach, the number of biogeographical units covered by the distribution of the focal species is used to determine whether its distribution is “local,” “regional,” or “wide,” (Fig 7). These class borders are flexible and can be changed to other values for further analyses. However, we strongly recommend using the standard setting that is described in [1, 7].

Using the count of biogeographical units can be misleading, especially in cases where the environmental conditions change rapidly over space and the overall area of biogeographical units overlapping with the focal area of an endemic species is small. In such cases, it is common to find three or more biogeographical units within a very small area, when only one biogeographical unit might be found in a similarly sized area in a region with less spatial variability, for example. The alternative approach implemented in the NRA-Tool calculates the real area proportion of the various biogeographical units that overlap with the distribution area of the focal species (S1 and S2 Files). To avoid biased area calculations, this method requires data with adequate spatial resolution in the correct geographical projection. This approach also requires detailed analyses of the resulting statistical distributions of the proportional area by which each biogeographical unit overlaps the distribution of the focal species. The Polygon Area-Approach is still in experimental stage, and most results published so far have used the Polygon Count-Approach with biomes or environmental zones [50]. We recommend using the Polygon Count-Approach (PC-A, ‘by Biome count’ option in the menu) described in [1, 7] in calculations for practical applications.

With this manuscript, we provide four appendices containing supporting information on the program and its functioning. S1 File illustrates the "User interface”, S2 File gives an example for the Polygon Count-Approach and Polygon Area-Approach calculations, S3 File provides the list of species used in the analyses and S4 File describes the performance and explains opportunities for optimization.

Technical requirements

The NRA-Tool is a module that can be added to the ArcGIS Toolbox. It was developed in ArcGIS 10.x and C# [57] using Visual Studio 17 [58] with.NET 4.6.1 [59], ArcGIS runtime SDK for.NET [60], and ArcObjects SDK [61].

Files to be used with the NRA-Tool must be named according to the following convention: The species distribution file names must start with a lowercase “s” followed by a hyphen. After the hyphen, the name can be chosen freely (e.g., “s-vulpes_vulpes.shp” for the red fox). For (global) ecological units or reference areas, file names must start with a lowercase “g” followed by a hyphen (e.g., “g-biomes.shp” and “g-border_of_asia”). Focal area file names must start with a lowercase “f” followed by a hyphen (e.g., “f-asian_countries.shp”). Files not named according to these conventions will not be displayed and therefore will not be selectable in the tool.

In ArcGIS, geodata should have a spatial reference if they are used for spatial analyses based on calculations of distance and area [51]. To avoid problems and erroneous results caused by incompatible projections, all input files for the NRA-Tool should use the same ArcGIS georeferencing and projection system. Generally, we recommend WGS84 for global analyses. Analyses on continental or smaller scales should be performed with more appropriate conformal area projections where polygon areas represent country areas. This is especially critical when using the Polygon Area-Approach. Other sources of bias must be considered when using the NRA-Tool, including the use of different formats, and the spatial resolution of data [1, 36]. Accordingly, we recommend that users check the georeferencing, projections, and resolutions of the input shapefiles as well as the CPU, RAM, and disk space of their computer system prior to using the NRA-Tool.

The computation times for national responsibility and conservation priority assessments are highly dependent on computer performance and are affected by the limitations of the operating system and hardware, as well as the spatial data input. For example, when calculations were made for 58 countries and regions on an area-only basis (i.e., comparison of areas without considering the shape, spatial extent, and overlap of the different units of concern) using a laptop with a 1.8 GHz processor and 4 GB RAM, the total computation time for the analyses of national responsibility and conservation priority for one species (Cyornis rubeculoides) based on TErW [53] was approximately 8 seconds, and based on GEnZ [62] was approximately 50 seconds Despite the longer runtime, when using complex, high-resolution spatial and environmental data to compute distribution range data for many species, we recommend using the GEnZ shapefile downloadable from [62] and applying the methods in [36, 37]. This task is computationally demanding and the runtime may be many hours or even days, especially if the analyses consider the whole globe as the reference area.

Further development

In addition to the development and improvement of the ArcGIS tool, we have started the development of a similar tool as an extension for the Open Source GIS QGIS [63], which will be made available as Open Source in future. The Polygon Area-Approach currently only uses information about the range/extent of the species distributions and should be expanded to allow for the use of abundance data. Additionally, it might be possible to integrate more options for particularly spatially-oriented conservation priority assessments with similar approaches, e.g. [31].

Availability of software and data

The NRA-Tool can be downloaded directly from [64, 65] or the interactive representation of the SCALES-project [66] called SCALETOOL [66-68]. The GEnZ can be found and downloaded from [62]. The publicly available species distribution dataset for selected shrew species is derived from IUCN Red List data and can be downloaded from [44] (not for commercial use). World continent data are available from ESRI [43], while the geographical data for administrative units (country areas, borderlines) from EuroGeographics can be downloaded from [45]. For the background map we used cross-blended hypsometric tints with relief, water, drains, and ocean bottom in scale of 1:10 million that is publicly available under the Creative Commons license from Natural Earth [46].

Case studies of bird species in Asia by Global Environmental Zones counts and Global Environmental Zones area

Here, we selected 58 Asian countries and regions as the focal areas or reference areas and categorized them according to their biogeographic characteristics: (1) tropical or temperate climate, (2) small or large area, (3) island or mainland. Birds that are (1) widespread and (2) migratory are considered too, although their distribution ranges exceed or lie outside of the reference area, respectively. However, it is not the aim of this study to discuss special aspects of national responsibility assessments related to migration or animal movement; our purpose is simply to demonstrate our tool, using this dataset as an example. We determined the national responsibility scores and conservation priorities for 258 bird species (from BirdLife International http://www.birdlife.org) in the 58 Asian focal countries (see S3 File). Nine of the bird species were vulnerable (VU); eight were near-threatened (NT), and 241 were of least concern (LC).

We performed two analyses, both of which used GEnZ [50], but differed by the choice of either the ‘By biome-area’ option in the panel (Polygon Area-Approach) or the ‘By biome count’ (Polygon Count-Approach) option. Both approaches use the polygons of the chosen map as the ecological units/regions (GEnZ in our case).

S1 Data gives an example for the content of the output files (dBase) for the results based on the Polygon Count-Approach and the Polygon Area-Approach shown in Figs 8 and 9. S2 Data provides a comparison of results for countries having medium national responsibility for at least one out of 258 species studied. The authors are solely responsible for the content and functionality of these materials. Queries (other than absence of the material) should be directed to the corresponding author.

Fig 8

Number out of 258 analyzed species in Asian regions and countries for which a country has a certain national responsibility.

BUs = GEnZ.

Fig 9

Conservation priorities for the number out of 258 analyzed species in Asian regions and countries that fall in a certain conservation priority class.

BUs = GEnZ.

Results

Using the Polygon Count-Approach two bird species were classified as “local” (locally distributed), six as “regional” (regionally distributed), and 250 as “wide” (widely distributed) according to Schmeller et al. [1, 36] (Table 3, S1 and S2 Data).

Table 3

Summary statistics for the number of species per country and the ranking of countries based on the two approaches, the Polygon Count-Approach and the Polygon Area-Approach, and stored in the results tables created by the ArcGIS NRA-Tool (see S1 and S2 Data).

		Number of Species
		Mini-mum		25% Quartile		50% Quartile (Median)		75% Quartile		Maxi-mum	Arithmetic Mean	SD
Species per Country	PC-A	1		10.75		21.00		38.25		150	36.17	38.12
	PA-A	1		10.50		20.50		39.75		152	36.31	38.73
	Thresholds (rounded)	1		11		21		40		152
	PA-A—PC-A	-6.00		-0.25		0.00		1.00		4.00	0.13	1.65
	Range		0–25%		25–50%		50–75%		75–100%		Overall
Country Rank	PC-A = PA-A (true)		3		4		5		11		23
	PC-A <> PA-A (false)		10		10		7		2		29
	Sum (true+false)		13		14		12		13		52
	Percentage (true)		23.08%		28.57%		41.67%		84.62%		44.23%
	Percentage (false)		76.92%		71.43%		58.33%		15.38%		55.77%

National responsibility

Our assessment of national responsibility shows that only a few countries, most in the south of Asia (China, Laos, Brunei, Cambodia, India, Indonesia, Malaysia, Myanmar/Burma, Thailand, Vietnam, and Taiwan), have high to very high national responsibility scores for the analyzed bird species (Fig 8A and 8B) with China responsible for the highest number of species. The ranking of the countries in the list corresponds to the number of species for which they have high and very high national responsibility scores.

Thirteen countries (Myanmar, Vietnam, Nepal, Bhutan, Laos, China, Thailand, India, Cambodia, Bangladesh, Malaysia, Indonesia, Taiwan; Fig 8C and 8D) have medium national responsibility scores for at least 40 species, which represents the 75%-quartile of the distribution of the number of species for which a country is responsible (see Table 3, S2 Data). The countries are ranked according to the number of species for which they have medium national responsibility. Comparing the results produced by the two approaches available in our tool, we found some differences. When we used the PA-A instead of the PC-A, no country gained more than four additional species and the maximum number of species for which a country lost medium responsibility was 10. However, over all countries the net change was zero (arithmetic mean = 0.13, median = 0). Looking at rank switching above the 75%-quartile, we saw only one exchange, which occurred between Nepal and Bhutan (2 out of 13 = 15.38%). When we used the PA-A instead of the PC-A, Bhutan had a medium responsibility score for three additional species. This is in stark contrast to the rank switches we observed below the 25%-quartile of the distribution. Here, we found that 10 out of 13 (76.92%) countries changed rank, which shows the summation of rank changes over larger ranges and in different positions, but not paired exchanges in the same positions (Table 3).

Generally, large countries like Russia, China, and India receive low national responsibility scores for a high number of species (Fig 8E and 8F).

Conservation priority

Using the Polygon Area-Approach with GEnZ [50] as biogeographical units and IUCN global Red List status to determine conservation priority, none of the 258 bird species in the focal area fell within Class 1 (Fig 9A and 9B), due to their low threat status. Generally, the results for both approaches were similar for national responsibility as well as for conservation priority (Fig 9). However, using the Polygon Area-Approach based on intersections of the overlapping polygons leads to results more balanced among countries compared to the simple Polygon Count-Approach originally used in [1, 7, 36, 37].

Discussion

The standardized determination of national responsibilities and conservation priorities across regions with multiple jurisdictions and administrative borders is an important step to advance and coordinate international conservation efforts. Here, we presented a software tool to assist in the determination of national responsibilities and conservation priorities. We showcased our tool with an example dataset of 258 Asian bird species. Our tool improves geoprocessing procedures for calculating national responsibilities and conservation priorities using a large spatial dataset. The tool also provides users with an interface and attractive visual outputs to facilitate the inclusion of national responsibility and conservation priority assessments in national and regional biodiversity reports. It is also possible to use it in combination with software tools for conservation prioritization assessments based on different algorithmic foundations like Marxan with Zones [17] and Zonation [16, 15], or multivariate statistical analyses [33]. These avenues of integration ensure that our tool can provide important assistance in making informed policy decisions [1].

Our results show that the national responsibility assessment is sensitive to the size of focal areas and focal species ranges when area and biophysical regions, such as the GenZ, are used to classify focal species distributions. Both global and regional assessment scales [36] are strongly dependent on spatial distributions, the extent of overlap between focal species distribution and focal area, and the number of biogeographical units in the focal area. A more limited global species distribution is likely to result in a smaller proportion of overlap between biogeographical units and the reference area. At the same time, the proportion of overlap between the focal species distribution and the focal area will probably be high. Accordingly, regional responsibility is a biogeographic metric that is related to the distribution range [69]. If a species is widespread outside of a region of interest, then, for a given reference area, the regional responsibility score for the species in the focal area will be low [69].

Maps of national responsibility and conservation priority obtained from our data using the Polygon Count-Approach and the Polygon Area-Approach showed that countries with at least “medium” responsibility for a high number of species fall into conservation priority Class 2. The Russian Federation did not have a high responsibility score for any species in the regional assessment (see Fig 4). This is because Russia shares many widespread species with Europe, has few endemic species relative to its size, and covers fewer Global Environmental Zones compared to other large counties, such as China, for example.

We found that countries previously identified as Asian biodiversity hotspots [70, 71] had higher responsibility scores for a larger number of species compared with countries outside designated hotspot regions. According to Pimm et al. [70], these hotspots overlapped by 68% with BirdLife International's Endemic Bird Areas, 82% with the areas designated as International Centres of Plant Diversity and Endemism by IUCN/WWF, and 92% with the most critically endangered eco-regions on the WWF/US Global 200 List. The assessment of national responsibility and conservation priorities allowed us to perform further analysis and mapping using attribute tables. For example, in our case study we obtained the number of species associated with a “very high” and “high” level of national responsibility for multiple focal species in each focal area. The national responsibility approach, therefore, provides additional policy-relevant information by identifying those species for which a country has high to very high responsibility scores within biodiversity hotspots. With this information, decision makers can allocate limited resources to the most urgently needed protection measures, including capacity-building [1, 72].

For more in-depth analyses and interpretation, the tool provides the results not only in map form but also in tables containing all input information, calculated areas, and resulting scores (Table 3, S1 and S2 Data). These outputs can provide insight into the discrepancies between the results of the two methodical approaches offered by our tool. These two approaches should be compared and evaluated in further methodological studies focusing on statistical effects and the functional relationship between environmental variability across countries and value distributions.

Our own analysis shows that the more advanced PA-A provides more differentiated results than the PC-A because it takes area of overlap into account rather than simply using the number of overlapping polygons. This leads to differences in weighting, especially when large countries have relatively little overlap with focal and reference areas. The size of a country also plays a role when considering the number of species for which basic responsibility must be assumed. The larger the territory of a country, the greater the probability that it will include significant portions of the range of a species in the corresponding reference area—a species for which the country then bears basic responsibility.

The NRA-Tool described here will allow the determination of national responsibility and conservation priorities across large geographic scales and across all species (and habitats) for which distribution data are available. With the NRA-Tool we are able to conduct global analyses and to inform global processes, such as IPBES assessments, about national responsibilities of each member state and to make suggestions on conservation priorities for different species. It can also be used to identify information gaps resulting from a lack of monitoring programs that target species for which countries have a “high” to “very high” degree of responsibility [72]. The results provided by the NRA-Tool, which are hierarchical lists, can be used to start capacity-building efforts in less surveyed regions and countries. The results can also be used in the various other ways outlined earlier [1]. With this information, policy and decision makers will be better equipped to assess when and how policy should be adapted, reinforced, or developed to fulfill the Convention on Biological Diversity’s Aichi targets. The maps and tables produced with the NRA-Tool are visual supports for making decisions about international biodiversity conservation.

NRA-tool user interface.

(PDF)

Click here for additional data file.

An example for the calculations of the Polygon Count-Approach and the Polygon Area-Approach.

(PDF)

Click here for additional data file.

List of species used in the illustration example.

(ZIP)

Click here for additional data file.

Performance and possibilities for optimization.

(PDF)

Click here for additional data file.

(ZIP)

Click here for additional data file.

Example for the content of the output files (dBase) for the results based on the Polygon Count-Approach and the Polygon Area-Approach shown in Figs 8 and 9.

(ODS)

Click here for additional data file.

Comparison of results for countries having medium national responsibility for at least one out of 258 species studied.

(ODS)

Click here for additional data file.

21 Apr 2020

PONE-D-20-05865

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

PLOS ONE

Dear Dr. Klenke,

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Two experts in the field have reviewed the paper, who have provided detailed and constructive comments. Although both they find the study interesting, they raise a number of questions and concerns with it, so I am recommending that you undertake a major revision of your manuscript.

Overall, both reviewers see the need of providing information about the conceptual framework on which is based this GIS tool. I agree that, in general, the manuscript is hard to follow because of numerous acronyms and many taken-for-granted concepts. Although the concept of national responsibility in spatial prioritization approaches has been defined and explained previously in different papers, authors should make an additional effort to explain the basics of this framework in order to make clear how this tool works and adapt the description of the software to those readers that are not familiar with this framework. Otherwise, the reader can easily get lost.

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: This manuscript regards the application of a prioritization method together with the national responsibility approach (an approach already used in several scientific works) in a novel GIS tool. This tool is presented with data from Asia. The manuscript is well written but there are a number of major concerns that need to be addressed.

Introduction

I think that national responsibility and conservation priority approaches should be thoroughly presented. What is national responsibility? How can this be derived? This in addition to the specific explanation given in the method section. There are a number of prioritization methods (including or not responsibility) applied in the literature and a brief overview should be given (see also indications in the discussion section). Data availability and type can influence the applicability of spatial prioritization approaches. This should be introduced as it can be relevant for application of the tool to other regions.

Methods

There are some aspects that deserve further explanation. Please give more details on what is meant with focal and reference area (I don’t think referring to Schmeller and colleagues suffices). Regarding the additional factor in the prioritization process, I miss how the different scores and classes were decided and assigned.

I think that a graphical framework of the National Responsibility Assessment Tool would enable a better understanding of the type of data, steps and requirements needed for its application (maybe integrated in fig. 1).

L119-120: I suggest anticipating that this can be used at the global as well as at other scales (regional? national?).

L126-127: I do not understand what files authors refer to. The message of this sentence is not clear.

L127: “All layers resp. GIS” is not clear.

I found really complex to follow the “Focal area and reference area” section. A table could help in reporting what are the different options. One additional suggestion is to add the factors used in the applied example (see comment on S1). This would enable also to use as example specific species. It is not clear whether species data can be points, polygons and/or based on grids.

Even though I do not have a technical background regarding ArcGIS, there is one important point from my side. This tool works in ArcGIS that is a private platform. There are many other programmes such as QGIS and R statistics that are open source and can be accessed without any restrictions. Why didn’t authors decided to produce tools or scripts for open source programmes? I think this would help the application of the approach.

L259-260: It is not clear if one single biogeographic category is assigned to each country.

L260-261: Which scientific reference is used to identify widespread and migratory species?

Fig. 3: I do not think this map is relevant to understand the proposed process or to show its results! This could be part of one of the Supplementary files.

Overall I think that acronyms do not help the reader.

Results

L273: Are the ranges of the number of biogeographic zones used to differentiate between local, regional or widely distributed species fixed? If these are fixed, as I have understood, such ranges should be reported in the method section and removed from the results.

Fig. 4: Not clear what the numbers reported in the figure legend mean. The caption misses this information and what the different colours mean.

Fig. 5: Not clear what the numbers reported in the figure legend mean. The caption misses this information and what the different colours mean.

Discussion

L308-309: Friendly and attractive environment! I think authors can state this once they have users' feedback.

Results for the study case show that in some cases there can be a strong dependency on the national responsibility category (i.e. on species distribution) as many species usually are classified as least concerned. A discussion of this and other possible limitations should be integrated in the discussion.

L323-328: It would be nice to have some results on this overlap in the supplementary material.

I suggest to highlight the possibility or not of adding some indicators of conservation priority. For example, current and future acting forces can help to set priorities also in terms of conservation and management activities. There are a number of works that use these factors to identify priorities (e.g. examples from different continents: Zhang et al. 2014; Campagnaro et al. 2018; Carvalho et al. 2020). These works can be used to make additional comments on the need of spatial information and compare different proposed tools. These works can also help in highlighting possible integrations to the spatial tool that authors are presenting.

Campagnaro, T. et al. (2018). Identifying habitat type conservation priorities under the Habitats Directive: Application to two Italian biogeographical regions. Sustainability, 10(4), 1189.

Carvalho, F. et al. (2020). Methods for prioritizing protected areas using individual and aggregate rankings. Environmental Conservation, 1-10.

Zhang, L. et al. (2014). Determination of priority nature conservation areas and human disturbances in the Yangtze River Basin, China. Journal for nature conservation, 22(4), 326-336.

Supporting material

S1: I think that some examples can be reported in the main text (see comments on the method section). For example, “Reference Area: Asia border” and “Focal Area: Asian countries”. This would benefit comprehension of the national responsibility tool.

S1 L18-20: I suggest reporting these possible issues in the main text.

S2 L12: Small typo: “CNTRY_NAME”.

S3: Are the reported examples of possible cases already presented in other publications? I find this supplementary extremely useful to better understand possible cases.

Reviewer #2: Thank you for the opportunity to review this manuscript. This study develops and demonstrates a GIS-based tool, which can be used to produce National Responsibilities and Conservation Priorities for multiple species using freely available data.

For me, this study demonstrates a great tool, which is relatively easy to use and has a pretty good flexibility to be applied on different scales and locations. Furthermore, using freely available species distribution and ecoregion data and setting a standardized assessment for countries are the strengths of this tool. In my opinion, this can certainly contribute to setting conservation prioritizations for policy makers.

Although I know the focus of this study is about the tool itself, I have a question about the method behind this tool, which is the issue about wide-ranging nomadic species and migratory species.

Could this method cause an issue like “tragedy of the commons” for wide and evenly distributed species? For example, would wide-ranging nomadic species be considered as basic in NR throughout all countries it lives? How would you address this issue in the method?

In Runge et al. (2015), they suggest that it might be more suitable to use the minimum range nomads occupy across multiple years because of their fluctuated distribution. The minimum range might contain some climate refugial sites or high quality habitats for those wide-ranging species.

Runge et al. (2015) Geographic range size and extinction risk assessment in nomadic species. Conservation Biology

For migratory species, I’m curious about how you deal with them in the study. Would you mind to provide some information about this in the manuscript? since this study also includes several migratory species. Do you use their breeding ranges, non-breeding ranges, or passage ranges, or all combined, or all but separated (which means one migratory bird might be counted as NR and CP in countries where it breeds, winters, and passes by). I suppose the last method, which is using all ranges separately, make more sense because migratory populations rely on all habitats for different life stages. However, some migratory birds in Asia might have their non-breeding ranges or passage ranges extend to Oceania (e.g., Australia and New Zealand)

This may influence your results (Fig. 4, and 5) because the proportion of migratory birds among all avian communities can be very high in the north hemisphere. See Somveille et al. (2013) Mapping Global Diversity Patterns for Migratory Birds. PLOS ONE.

Minor comments as follows

line 32: to prioritize conservation what? to prioritize conservation resources? funds? effort? actions?

line 54: could you provide one or a few sentences in the introduction to define or explain “national responsibility”? If I didn’t read any previous studies about NR, I would only realize what it really is until the Methods…

line 184: While these two BUs may be useful for terrestrial species, incorporating “Freshwater Ecoregions of the World” might further enlarge the applicability of this tool. The distribution of freshwater biodiversity may be more relevant to the shape and size and boundary of watersheds/river basins than local climate or terrestrial vegetation. The freshwater ecoregion data is also freely available online. See Abell et al. (2008) Freshwater ecoregions of the world: A new map of biogeographic units for freshwater biodiversity conservation. BioScience.

line 312: Which part of your results supports this statement about “sensitive”? Is there any quantified sensitivity? such as sensitivity analysis or a plot about the correlation between the range size of FS and biophysical regions and NR? or simply based on the description.

line 528: “probability” or “responsibility”?

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Reviewer #1: No

Reviewer #2: No

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21 Sep 2020

We have overhauled most of the sections in our text based on your and the reviewers comments, provided more detailed information about the conceptual framework on which the ArcGIS NRA-tool is based, reduced the number of acronyms used, explained the basics of this framework in order to make clear how this tool works, and we tried to adapt the description of the software to those readers that are not familiar with this framework.

We would like to emphasize that it is our main aim to present a software tool for research. The research results provided with our manuscript are rather meant as an example and an illustration of the utility and usability of this tool but not as a sophisticated analysis of the national responsibilities countries do have for threatened bird species in Asia and where the main priorities for conservation effort should be set.

We tried to make sure that the manuscript meets PLOS ONE criteria for manuscripts that describe new software for applications following the guidelines mentioned in your decision letter from April 21st of this year.

Utility: From our knowledge, there is no other GIS tool available, which is based on the methods presented by Schmeller et al. in several publications mentioned as references in our manuscript. After publication in PLOS ONE we will open opportunities for active collaboration and further development and overhand the complete source code to the public via github and/or sourceforge securing long term availability and maintenance. The future maintenance, software development and growth will depend on the interest of the scientific community, therefore.

Validation: Until now, there was no option for the automatization and detailed documentation of analyses of National Responsibilities and Conservation Priorities based on the methods described by Schmeller et al. With our ArcGIS-NRA-Tool, these partly difficult and especially time consuming steps of the analyses can be done automatically as demonstrated with the examples described in our manuscript.

Availability: The tool is currently hosted in https://github.com/ and will be made publicly available via https://sourceforge.net/ under the GNU General Public Licence after our manuscript is accepted. The links will be updated in the final version of the manuscript, permissions will be set to “public”, and the source code will be made available. Besides, our tool is already advertised in the web presentation of the EH FP7 SCALES project (www.scales-project.net) and at the web presentation of the SCALES-Taiwan project (http://homepage.ntu.edu.tw/~yplin/Scales-Taiwan.htm). We will amend the links in these web pages too. A long term backup will be made in the archive of the Helmholtz Centre for Environmental Research (UFZ) in Leipzig.

With our revision we are providing a marked-up copy of our manuscript that highlights changes made to the original version (labeled 'Revised Manuscript with Track Changes'), an unmarked version of our revised paper without tracked changes (labeled ‘Manuscript’), four revised and five new figures, one revised and one new table. We have included information from one file of the supplemental material into the main text and dropped this file, revised and renumbered the remaining 4 files and added two new files with results to the supplemental material.

Comments and questions of the reviewers with our answers and respective revisions:

Reviewer #1:

This manuscript regards the application of a prioritization method together with the national responsibility approach (an approach already used in several scientific works) in a novel GIS tool. This tool is presented with data from Asia. The manuscript is well written but there are a number of major concerns that need to be addressed.

I think that national responsibility and conservation priority approaches should be thoroughly presented. What is national responsibility? How can this be derived? This in addition to the specific explanation given in the method section. There are a number of prioritization methods (including or not responsibility) applied in the literature and a brief overview should be given (see also indications in the discussion section). Data availability and type can influence the applicability of spatial prioritization approaches. This should be introduced as it can be relevant for application of the tool to other regions.

Thank you for the suggestions. We have changed this part in the introduction and extended it by more detailed explanations about national responsibility and approaches for the determination of conservation priorities. However, it is not the aim of our paper to review such approaches but to present a software tool that can be used to perform a certain type of analyses based on methods already described before. This tool should not be used without respective knowledge and experience in this field as it is required for any scientific work.

Methods

There are some aspects that deserve further explanation. Please give more details on what is meant with focal and reference area (I don’t think referring to Schmeller and colleagues suffices). Regarding the additional factor in the prioritization process, I miss how the different scores and classes were decided and assigned. I think that a graphical framework of the National Responsibility Assessment Tool would enable a better understanding of the type of data, steps and requirements needed for its application (maybe integrated in fig. 1).

We have overhauled the whole section and provided new figures and maps explaining the different terms and the process. There is already a graphical framework explaining the workflow (Fig. 2) and the user interface as well as the data needed (S2). We think that a potential user should study all this material provided by us in detail and read the respective references to get familiar with the approaches and the program first. Again, it is not the aim of this paper to explain and discuss approaches for the determination of national responsibilities, we want to introduce a tool. We also separated the more technical parts from the main text and provided them in the supplemental material to make the paper easier to read.

L119-120: I suggest anticipating that this can be used at the global as well as at other scales (regional? national?).

We stated this in an introductory sentence referring to the special case of global analyses and the data needed for this. At the end of the paragraph we were writing:

129 However, analyses can be conducted also at other scales and with other administrative

130 references.

We moved this sentence to the beginning and inserted a link to Supplement S1 to make this clearer.

L126-127: I do not understand what files authors refer to. The message of this sentence is not clear.

The approach requires the definition of the Reference Area. The borders of this area can be set either by a special file ( e.g. created by a dissolve operation based on a shapefile of the continents of the world) or just by referring in the respective fields in the user interface to either the file used for the Geographical Regions or the Ecological Unit/Region. We suggest to have a glance on Supplement S1 while reading this section because this document shows the respective screenshots of the user interface. We refer to S1 in this paragraph now.

L127: “All layers resp. GIS” is not clear.

We agree that this part of the sentence may be confusing and have tried to write more clearly what we mean. Thank you!

I found really complex to follow the “Focal area and reference area” section. A table could help in reporting what are the different options.

We now explain this part more in detail with a more detailed description of the method and a set of examples in five new figures.

One additional suggestion is to add the factors used in the applied example(see comment on S1). This would enable also to use as example specific species. It is not clear whether species data can be points, polygons and/or based on grids.

Thank you. However, we clearly wrote:

119 The ArcGIS-NRA-Tool needs four predefined layers with polygons to allow assessments …

It is not possible to use data organized in points or grids, this is not a limitation. It would be just inappropriate to use such type of data with this kind of geographical method.

Even though I do not have a technical background regarding ArcGIS, there is one important point from my side. This tool works in ArcGIS that is a private platform. There are many other programmes such as QGIS and R statistics that are open source and can be accessed without any restrictions. Why didn’t authors decided t produce tools or scripts for open source programmes? I think this would help the application of the approach.

Thank you. We agree with this opinion. For R we don’t see any necessity to provide a special program because an experienced user can do this very easily by itself. ArcGIS is widely used in administrations and scientific institutions and also by organisations like e.g., the IUCN. Therefore we started the development of such a tool with ArcGIS. At this time QGIS was not that widespread and commonly used as it is today. However, we also have already prepared a version for QGIS, which is still in a testing phase but will be released soon too. In the section “Further development” we have added a respective paragraph to the manuscript.

L259-260: It is not clear if one single biogeographic category is assigned to each country.

As mentioned already before, we have tried to explain this part more in detail with a more detailed description of the method and a set of examples in five new figures. The tool provides two different approaches, one is using simple counting of the number of polygons, which are overlapped / touched by the species area and a certain country the other one is performing an intersection among the different layers to calculate the accurate proportions of the overlapping areas.

L260-261: Which scientific reference is used to identify widespread and migratory species?

We didn’t use any reference for that. This sentences simply mean that we didn’t exclude species that are either living in areas bigger than the chosen Reference Area (Asia) = widespread and/or are migratory species, means leaving the Reference Area at least for parts of the year. However, it was not the aim of this study to discuss special aspects of national responsibility assessments related to migration or animal movement, we only want to give an example for the use of our tool. We added a short sentence about this to the manuscript.

Fig. 3: I do not think this map is relevant to understand the proposed process or to show its results! This could be part of one of the Supplementary files.

Thank you for the suggestion. We agree and have dropped this figure from the manuscript.

Overall I think that acronyms do not help the reader.

Thank you! We agree. We only used the abbreviations to keep the text shorter. Because PLOS ONE has no word limits we decided to use abbreviations only if we think it is helpful.

L273: Are the ranges of the number of biogeographic zones used to differentiate between local, regional or widely distributed species fixed? If these are fixed, as I have understood, such ranges should be reported in the method section and removed from the results.

Thank you! We agree and have removed this information from the results but referred to references and a figure in the methods section.

Fig. 4: Not clear what the numbers reported in the figure legend mean. The caption misses this information and what the different colours mean.

Thank you! We have revised and improved this Figure (now Figure 8)

Fig. 5: Not clear what the numbers reported in the figure legend mean. The caption misses this information and what the different colours mean.

Thank you! We have revised and improved this Figure (now Figure 9)

L308-309: Friendly and attractive environment! I think authors can state this once they have users' feedback.

Thank you! We agree and have deleted this statement from the text.

Results for the study case show that in some cases there can be a strong dependency on the national responsibility category (i.e. on species distribution) as many species usually are classified as least concerned. A discussion of this and other possible limitations should be integrated in the discussion.

We don’t understand this sentence. The methodological approach and possible limitations were already addressed in the methodological papers. This is not the aim of our manuscript. There are no such limitations related directly to the tool. Additionally, we have discussed special aspects in Lines 312 to 322 in the revised manuscript.

L323-328: It would be nice to have some results on this overlap in the supplementary material.

Thank you for the suggestion. This might be a misunderstanding. We didn’t do any special analyses in this regard. We only linked our results to information provided by the papers cited. We revised this paragraph to make this more clear. However, now we provide still more data from the output files produced by our tool (Supplement S5) and some statistics, which will be presented in an additional table in the manuscript (Table 2), and supported by Supplement S6. This material is used for a more detailed interpretation, which we have added to this section.

I suggest to highlight the possibility or not of adding some indicators of conservation priority. For example, current and future acting forces can help to set priorities also in terms of conservation and management activities. There are a number of works that use these factors to identify priorities (e.g. examples from different continents: Zhang et al. 2014; Campagnaro et al. 2018; Carvalho et al. 2020). These works can be used to make additional comments on the need of spatial information and compare different proposed tools. These works can also help in highlighting possible integrations to the spatial tool that authors are presenting.

Thank you for your suggestions. However, although it is not the aim of the paper to review different other methods and tools, we have integrated a paragraph giving a short overview in the introduction, provided some ideas for integration of appropriate spatial conservation prioritization approaches in the section “Further development” and referred to other software tools, types of analyses and methodological approaches, which could be used in sophisticated combined approaches in the discussion section.

S1: I think that some examples can be reported in the main text (see comments on the method section). For example, “Reference Area: Asia border” and “Focal Area: Asian countries”. This would benefit comprehension of the national responsibility tool.

and

S1 L18-20: I suggest reporting these possible issues in the main text.

We are grateful for these suggestions and have moved the whole content of Supplement S1 to the part “Technical requirements” in the section “Description of the National Responsibility Assessment Tool” of the main text. Additionally, as mentioned above, we have already added some new paragraphs to explain the approach a little bit more in detail with an other example in the “Methods” section.

S2 L12: Small typo: “CNTRY_NAME”.

This is not a typo, it is the name of the field for the Focal Region you can see in right panel of the user interface in Figure S2.1. Shapefiles use dBase format for attribute tables. dBase field names are limited to the string length of 10 characters only. Because we have moved the whole content of S1 to the main text S2 is now S1.

S3: Are the reported examples of possible cases already presented in other publications? I find this supplementary extremely useful to better understand possible cases.

Thank you! No, these examples are purely theoretical and have not been published so far. We only used them to better illustrate the difference between both approaches addressed in it. We feel that this artificial construct is more helpful to understand the problems we have to deal with than an example with real maps and species distributions where the reader can be distracted by shape and size of a certain polygon. However, we felt it is better to keep it separated from the main text. Because we have moved the whole content of S1 to the main text S3 is now S2.

Reviewer #2:

Thank you for the opportunity to review this manuscript. This study develops and demonstrates a GIS-based tool, which can be used to produce National Responsibilities and Conservation Priorities for multiple species using freely available data. For me, this study demonstrates a great tool, which is relatively easy to use and has a pretty good flexibility to be applied on different scales and locations. Furthermore, using freely available species distribution and ecoregion data and setting a standardized assessment for countries are the strengths of this tool. In my opinion, this can certainly contribute to setting conservation prioritizations for policy makers.

Although I know the focus of this study is about the tool itself, I have a question about the method behind this tool, which is the issue about wide-ranging nomadic species and migratory species. Could this method cause an issue like “tragedy of the commons” for wide and evenly distributed species? For example, would wide-ranging nomadic species be considered as basic in NR throughout all countries it lives? How would you address this issue in the method?

Thank you for raising this question. Indeed, a wide ranging or migratory species with a distribution area covering many countries and eco-regions would be probably considered rather as basic throughout all countries it lives. That means that no country would have a special National Responsibility. However, in this case the IUCN Red List status would have more weight and the burden should be shared between all countries. It doesn’t mean that this species must not be protected, it only means that not one or some more countries would have a higher responsibility because the species mainly occurs in it or them respectively. The scores of National Responsibility will be correlated with the size of the countries in this case. The country with the largest area would also have the highest responsibility.

Especially for migratory species, detailed analyses could be made focusing either only on the breeding range, areas which are either important during the time of migration or in winter. There are a lot of options for such analyses. However, this is not a question of the tool or special options in it, it is rather a question of selection of species, geographical focus, and stratification in the data. Hence it is in the responsibility of the researcher and the design of the study.

To address and answer such questions we have integrated already options to change the parameters for the analyses (Supplement S1, Fig. S1.2b) and the two approaches. However, it takes more special investigations with standardised theoretical and real data as well to find out more about such effects and possible causes of bias. This is planned for the future and also one reason why we want to provide this tool to the community and other researchers to address such problems.

In Runge et al. (2015), they suggest that it might be more suitable to use the minimum range nomads occupy across multiple years because of their fluctuated distribution. The minimum range might contain some climate refugial sites or high quality habitats for those wide-ranging species.

Runge et al. (2015) Geographic range size and extinction risk assessment in nomadic species. Conservation Biology

Thank you. This is an interesting aspect. However, the tool presented is not limited regarding this. It depends on research question, knowledge of the researcher, aim of the study etc., which polygons will be used for the analysis. Our tool only helps to automatize some steps within this work flow it does not answer questions or make decisions the researcher should do.

For migratory species, I’m curious about how you deal with them in the study. Would you mind to provide some information about this in the manuscript? since this study also includes several migratory species. Do you use their breeding ranges, non-breeding ranges, or passage ranges, or all combined, or all but separated (which means one migratory bird might be counted as NR and CP in countries where it breeds, winters, and passes by). I suppose the last method, which is using all ranges separately, make more sense because migratory populations rely on all habitats for different life stages. However, some migratory birds in Asia might have their non-breeding ranges or passage ranges extend to Oceania (e.g., Australia and New Zealand)

This may influence your results (Fig. 4, and 5) because the proportion of migratory birds among all avian communities can be very high in the north hemisphere. See Somveille et al. (2013) Mapping Global Diversity Patterns for Migratory Birds. PLOS ONE.

Thank you for raising this question. Indeed, migratory species need a special treatment and more sophisticated analyses and interpretation of results in such studies. Depending on the question a researcher has, it is possible to use separate breeding, wintering and passing by ranges with the tool, if the researcher separates these data in the input files. However, our example was only meant as an illustration of the opportunities. It was not our aim to do a detailed analysis in this case. This is planned for the future. We only mentioned migratory and widespread species because we didn’t want to exclude such species from the analysis. A complete assessment would require the detailed discussion of each species and, therefore, go far beyond the aim of our manuscript.

Minor comments as follows

line 32: to prioritize conservation what? to prioritize conservation resources? funds? effort? Actions?

Thank you! We have specified this in the respective sentence.

line 54: could you provide one or a few sentences in the introduction to define or explain “national responsibility”? If I didn’t read any previous studies about NR, I would only realize what it really is until the Methods…

We have added a sentence to explain this concept. Thank you!

line 184: While these two BUs may be useful for terrestrial species, incorporating “Freshwater Ecoregions of the World” might further enlarge the applicability of this tool. The distribution of freshwater biodiversity maybe more relevant to the shape and size and boundary of watersheds/river basins than local climate or terrestrial vegetation. The freshwater ecoregion data is also freely available online. See Abell et al. (2008)

Freshwater ecoregions of the world: A new map of biogeographic units for freshwater biodiversity conservation. BioScience.

Thank you for mentioning this aspect. Indeed, the tool and this approach are not limited to terrestrial ecosystems. We have added a paragraph explaining this and referring to resources for freshwater and marine ecoregions.

line 312: Which part of your results supports this statement about “sensitive”? Is there any quantified sensitivity? such as sensitivity analysis or a plot about the correlation between the range size of FS and biophysical regions and NR? or simply based on the description.

We didn’t do any specific sensitivity analysis. However, we got already some experience in former analyses and one also can derive such effects simply from the type of analysis and distribution of polygons. However, as already mentioned before in this letter and also mentioned at the end of the discussion in our manuscript, one aim to develop and release this tool was to support such type of studies. We added additional sentences at the end of the “Discussion” section in the manuscript.

line 528: “probability” or “responsibility”?

Thank you! We have revised to “responsibility”

Additional information

The program will be described in github.com and sourceforge.org with the following text:

ArcGIS-NRA-Tool

ArcGIS Tool for the Assessment of National Responsibilities for Endangered Species and Habitats

The aim of the source code is to develop a National Responsibility Assessment Tool that can be used as plug-in for ArcGIS (https://github.com/popecologist/ArcGIS-NRA-Tool and http://popecologist.github.io respectively or https://sourceforge.net/projects/arcgis-nra-tool/).

There are two binary versions of the add-in: SpeciesTool.NET.20140619.esriAddIn - Version from 2014-06-14 compiled with Visual Studio 12, Microsoft .NET 3.4, and the matching (older) SDKs ArcGISRuntime and ArcObjects from ESRI. SpeciesTool.NET.20200228.esriAddIn - Version from 2020-02-28 compiled with Visual Studio 17, Microsoft .NET 4.6.1, and the and the matching (newer) SDKs ArcGISRuntime 100.2.0 and ArcObjects for ArcGIS 10.6.1 from ESRI.

Copyright (c) 2020 Yu-Pin Lin / 林裕彬 Department of Bioenvironmental Systems Engineering National Taiwan University No. 1, Sec. 4, Roosevelt Road Taipei 10617 Taiwan R.O.C. Office Phone: 886-2-33663467; Fax: 886-2-2368-6980 E-mail: yplin@ntu.edu.tw http://homepage.ntu.edu.tw/~yplin/Scales-Taiwan.htm

Credits: Academia Sinica (programming) Reinhard A. Klenke (revising, updating)

The development of the ArcGIS-NRA-Tool was mainly funded by Ministry of Science and Technology of Taiwan (former National Science Council of Taiwan, code NSC101-2923-I-002-001-MY2), and a contribution from the EU FP7 project SCALES: Securing the Conservation of biodiversity across Administrative Levels and spatial, temporal, and Ecological Scales, under the European Union’s Framework Program 7 (Code: 226852 FP7-ENVIRONMENT ENV.2008.2.1.4.4., www. scales-project.net.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/. Please cite and refer to the tool in any report, scientific paper or other type of publication either in print or electronically with the reference mentioned below.

Unfortunately we still need proprietary libraries from third parties such as ESRI (e.g. ArcGIS SDK, ArcObjects SDK) and from Microsoft to be linked again this source code. The need for these publicly available but proprietary libraries is a drawback. Therefore, we suggest to anyone who thinks of doing substantial further work on the program to give highest priority to tasks changing the program in a way that it can do the same job without the proprietary libraries.

Installation of the ArcGIS-add-in: There might be a "No GUI components found in this Add-In. Add-In version does not match." error during installation. This error only occurs when a user tries to install the add-in using the in the Customize dialog. When the add-in is double-clicked from Windows Explorer, the add-in is installed successfully. This is a defect (NIM095435 http://support.esri.com/bugs/nimbus/TklNMDk1NDM1. A potential workaround is to either: the Add-In in Windows Explorer to install OR add folder through in Add-In Manager (see more at: https://community.esri.com/thread/162324).

References: Lin Y-P, Schmeller D S, Ding T S, Wang Y Ch, Lien W-Y, Henle K, Klenke R A (2020): A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation. PLOS ONE. doi: xxxxxx

Each separate file of the C# code is starting with the following lines referring to the GNU General Public License and to the Article in PLOS ONE:

/*

* This file is part of the ArcGIS National Responsibility Assessment Tool

* source code (https://github.com/popecologist/ArcGIS-NRA Tool or http://xxx.github.io).

*

* Copyright (c) 2020 Yu-Pin Lin / 林裕彬

* Department of Bioenvironmental Systems Engineering

* National Taiwan University

* No. 1, Sec. 4, Roosevelt Road

* Taipei

* 10617 Taiwan

* R.O.C.

* Office Phone: 886-2-33663467; Fax: 886-2-2368-6980

* E-mail: yplin@ntu.edu.tw

* http://homepage.ntu.edu.tw/~yplin/Scales-Taiwan.htm

*

* Credits:

* Academia Sinica (programming)

* Reinhard A. Klenke (revising, updating)

*

* The development of the ArcGIS-NRA-Tool was mainly funded

* by Minister of Science and Technology of Taiwan

* (National Science Council of Taiwan) (NSC101-2923-I-002-001-MY2),

* and a contribution from the EU FP7 project

* SCALES: Securing the Conservation of biodiversity across

* Administrative Levels and spatial, temporal, and Ecological Scales,

* under the European Union’s Framework Program 7

* (grant Code: 226852 FP7-ENVIRONMENT ENV.2008.2.1.4.4.;

* www. scales-project.net.

*

* This program is free software: you can redistribute it and/or modify

* it under the terms of the GNU General Public License as published by

* the Free Software Foundation, version 3.

*

* This program is distributed in the hope that it will be useful, but

* WITHOUT ANY WARRANTY; without even the implied warranty of

* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU

* General Public License for more details.

*

* You should have received a copy of the GNU General Public License

* along with this program. If not, see .

*

* Please cite and refer to the tool in any report, scientific paper or

* other type of publication either in print or electronically with the

* reference mentioned below.

*

* References:

* Lin Y-P, Schmeller D S, Ding T S, Wang Y Ch, Lien W-Y, Henle K,

* Klenke R A (2020): A GIS-based policy support tool to determine national

* responsibilities and priorities for biodiversity conservation.

* PLOS ONE. doi: xxxxxx

*/

Submitted filename: 20200921-Response2Reviewers.pdf

Click here for additional data file.

14 Oct 2020

PONE-D-20-05865R1

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

PLOS ONE

Dear Dr. Klenke,

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: N/A

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #2: No

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I thank the authors for considering all my comments and following most of them. Authors made some important changes based on suggestions of both reviewers and I think the manuscript has greatly improved compared to the former version. I really hope this tool will find large use in the biodiversity conservation world.

However, I still have some minor comments. I final language revision is needed.

i. I think you should avoid mentioning “Schmeller and collegues” in the abstract.

ii. L120-122, L500-501: What about the four species of shrews? (e.g. L141-143).

iii. L503: Repetition: “provides users an user interface”

iv. L508: It is a strange sentence and a bit redundant (“the bunch of methods mentioned in the introduction already before”).

v. L530-531: Which group? Do you mean medium/small size countries?

vi. L560: I think that it should be “..earlier by Schmeller et al. [1]”. There are other cases in the text.

Good luck and best regards

Reviewer #2: Thank you for this opportunity to review this work again. Generally, this manuscript is much improved and being revised according to suggestions and comments from reviewers. Specifically, now the authors clearly explained what national responsibility is and clarified the differences between this approach and other prioritization methods for biodiversity conservation. I generally satisfied with this revised version especially with the science part (which is more important for me). Nevertheless, I highly recommend authors be more careful on their writing and do a thorough check because there are many typos, redundant words, and confusing sentences throughout the manuscript (maybe more than the first version). Although I personally do not think these typos would heavily influence my decision for this manuscript, in some cases these small mistakes could severely reduce the readability of a great work.

While I only listed a few things I saw here, a more thorough check is highly recommended.

Lines 54-56 and 57-61: same or different paragraphs?

Line 78-89: While I really appreciate the comprehensiveness of this long list about "other methods", it is a bit too long and thus interrupts the logic flow of the Introduction...

Could you make this list a bit shorter (maybe group some of these into a few groups?! e.g., species-focusing, habitat-focusing, socioeconomic-focusing, mixed approaches,...etc)? or add one sentence at the end of this paragraph to guide the focus of readers back to national responsibilities (something like line 111-113)?

Line 112: “like” “e.g.” redundant. Please pick one

Line 112: “,” after Zonation

Line 113: they do not XXX for the estimation… a verb is lacking here

Line 119-120: Could you rewrite this sentence? It is a bit strange...something like “…for a large set of species for which data are available such as the species range data in the IUCN Red List database”

Ling 127: suggest deleting “However”

Line 134: “like” “e.g.” redundant. Please pick one

Line 136-137: “only” redundant

Line 141: suggest deleting “However”

Line 141: suggest using past tense because you have already done it

Line 163-164: “also””too” redundant

Line 191-195: suggest dividing this long sentence into two short sentences to improve the readability

Line 210-212: I am not sure what does this sentence mean…

Line 212: For Sorex minutus”,”

Line 213: “the” highest responsibility

Line 213: suggest replacing “the” with “this”

Line 225: suggest deleting “of course”

Line 225: suggest deleting “also”

Line 228: suggest deleting “area”

Line 235: suggest changing to something like

“…or in the same projection for analyses on a regional scale to provide...”

Line 239: suggest deleting “animal and plant”

Line 243: suggest changing “…on data freely available from different sources” to something like

“…or on freely available data.”

Line 245: suggest changing “ in shapefile format from (<- a typo here)” to “as shapefiles”

Line 245-246: suggest changing to “The distribution of each species or habitat category should be saved individually for the analyses”

Line 248: suggest changing to “files downloaded from the IUCN...”

Line 260: suggest deleting “of this type”

Line 284: suggest changing “in the form of” to “as”

Line 298: suggest “we strongly suggest using the GEnZ level…”

Line 302-307: suggest turning this whole paragraph into one or two sentences at the end of previous paragraph

Line 328: suggest deleting “still”

Line 329: suggest deleting “the” right before Biogeographic Units

Line 338: suggest deleting “those”

Line 348: suggest deleting the first “the”

Line 361: suggest adding “of” right behind “layers”

Line 364: suggest using “e.g.,” within parentheses and “for example” outside parentheses. Nevertheless, no matter which one you prefer, be consistent

Line 379-380: This sentence is identical with line 369-371 but with different references? One could be deleted

Line 403: suggest deleting “still”

Line 405: “such as” “e.g.” redundant. Please pick one

Line 439-440: “also” “as well” redundant. Please pick one

Line 442: Why are there two China here…

Line 443: Vietnam”,”

Line 458: suggest deleting “more”

Line 458-467: I'm not sure what is the importance of this detailed quantified comparison described in this paragraph and table 2 if there is NO DISCUSSION following up?

The different results from PA-A and PC-A are expected because they use different information...

Suggest moving most part of this paragraph and table 2 to supplementary files. A few sentences describing the overall differences/patterns between these two approaches (like what you did for “Conservation priority”) and Figs 8 and 9 should be enough.

Alternatively (you don't need to do this, just a suggestion), an analysis on the relationship between the change of ranking versus the environmental variability (heterogeneity) across countries might be more interesting...because the authors DID mention environmental variability could be one of the reasons causing the differences between these two approaches.

Line 507: “like” “e.g.” redundant. Please pick one

Line 548: suggest changing “focus” to “allocate”

Line 549-550: “…also including guiding capacity building” not sure what does this mean

Line 553: suggest changing “…for which we have distribution data available” to “…for which distribution data are available”

**********

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Reviewer #1: No

Reviewer #2: No

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14 Nov 2020

Comments and questions of the reviewers with our answers and respective revisions

PONE-D-20-05865R1

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

PLOS ONE

...

Overall, reviewers agree that the manuscript needs a deep review for language/grammar. I would highly encourage you to seek editorial help or have a native English speaker review of the manuscript before next submission.

Thank you. We asked a native speaker from our team for a check of language and grammar and tried to improve the text based on her suggestions.

Reviewer #1: I thank the authors for considering all my comments and following most of them. Authors made some important changes based on suggestions of both reviewers and I think the manuscript has greatly improved compared to the former version. I really hope this tool will find large use in the biodiversity conservation world.

However, I still have some minor comments. I final language revision is needed.

We want to thank reviewer #1 for the very helpful suggestions and tried to carefully consider all of them in our revision. The manuscript was also checked by a native speaker and revised substantially.

i. I think you should avoid mentioning “Schmeller and colleagues” in the abstract.

We changed the introduction.

ii. L120-122, L500-501: What about the four species of shrews? (e.g. L141-143).

Thank you, we changed it to: “To demonstrate the use of our tool and to illustrate potential pitfalls, we illustrate our approach using four shrew species with different distribution areas (Fig 1) and 258 Asian bird species”

iii. L503: Repetition: “provides users an user interface”

We changed it to: “provides users with an interface”

iv. L508: It is a strange sentence and a bit redundant (“the bunch of methods mentioned in the introduction already before”).

We deleted this part.

v. L530-531: Which group? Do you mean medium/small size countries?

We changed it to: “showed that countries with at least “medium” responsibility for a high number of species fall in conservation priority Class 2.”

vi. L560: I think that it should be “..earlier by Schmeller et al. [1]”. There are other cases in the text.

We revised all cases and either changed the wording and removed by/according or we mentioned the authors.

Reviewer #2: Thank you for this opportunity to review this work again. Generally, this manuscript is much improved and being revised according to suggestions and comments from reviewers. Specifically, now the authors clearly explained what national responsibility is and clarified the differences between this approach and other prioritization methods for biodiversity conservation. I generally satisfied with this revised version especially with the science part (which is more important for me). Nevertheless, I highly recommend authors be more careful on their writing and do a thorough check because there are many typos, redundant words, and confusing sentences throughout the manuscript (maybe more than the first version). Although I personally do not think these typos would heavily influence my decision for this manuscript, in some cases these small mistakes could severely reduce the readability of a great work.

While I only listed a few things I saw here, a more thorough check is highly recommended.

We want to thank reviewer #2 for the numerous and very helpful suggestions and the high effort in proof reading of our text. We tried to carefully consider almost all of them in our revision. We also beg your pardon for submitting a manuscript still containing so many language issues. To improve grammar, orthography, and style, the manuscript has been checked by a native speaker and revised substantially by the authors.

Lines 54-56 and 57-61: same or different paragraphs?

We merged it to one paragraph.

Line 78-89: While I really appreciate the comprehensiveness of this long list about "other methods", it is a bit too long and thus interrupts the logic flow of the Introduction...

Could you make this list a bit shorter (maybe group some of these into a few groups?! e.g., species-focusing, habitat-focusing, socioeconomic-focusing, mixed approaches,...etc)? or add one sentence at the end of this paragraph to guide the focus of readers back to national responsibilities (something like line 111-113)?

Thank you, we compiled the list in a table to separate it from the text.

Line 112: “like” “e.g.” redundant. Please pick one

We deleted “e.g.”

Line 112: “,” after Zonation

We inserted a comma.

Line 113: they do not XXX for the estimation… a verb is lacking here

Thank you, we changed the sentence.

Line 119-120: Could you rewrite this sentence? It is a bit strange...something like “…for a large set of species for which data are available such as the species range data in the IUCN Red List database”

Thank you, we changed it to: “such as the Spatial Data & Mapping Resources and the Red List database from IUCN [41, 42]”

Ling 127: suggest deleting “However”

We deleted “However”

Line 134: “like” “e.g.” redundant. Please pick one

We deleted “e.g.”

Line 136-137: “only” redundant

We deleted “only”

Line 141: suggest deleting “However”

We deleted “However”

Line 141: suggest using past tense because you have already done it

We changed the tense.

Line 163-164: “also””too” redundant

We deleted “too”

Line 191-195: suggest dividing this long sentence into two short sentences to improve the readability

We split the sentence in two shorter ones.

Line 210-212: I am not sure what does this sentence mean…

Thank you. We rewrote the sentence: “Sorex alpinus shows preferences for alpine habitats that are less common in the focal area (France) but comprise large regions of Switzerland and Austria. “

Line 212: For Sorex minutus”,”

We inserted a comma.

Line 213: “the” highest responsibility

We revised to: “For Sorex minutus, Russia scores very high on the responsibility metric ...”

Line 213: suggest replacing “the” with “this”

We replaced “the” with “this”.

Line 225: suggest deleting “of course”

We have replaced “of course” with “such”

Line 225: suggest deleting “also”

Thank you. However, we think, deleting “also” would change the meaning of this sentence and left it as it is.

Line 228: suggest deleting “area”

We deleted “area”.

Line 235: suggest changing to something like

“…or in the same projection for analyses on a regional scale to provide...”

Thank you. We changed it to: “…or in the same equal area projection for analyses on a smaller scale to provide...”

Line 239: suggest deleting “animal and plant”

We deleted “animal and plant”

Line 243: suggest changing “…on data freely available from different sources” to something like

“…or on freely available data.”

Thank you. We followed this suggestion.

Line 245: suggest changing “ in shapefile format from (<- a typo here)” to “as shapefiles”

We changed the sentence.

Line 245-246: suggest changing to “The distribution of each species or habitat category should be saved individually for the analyses”

Thank you. We changed the two sentences referring to this issue to one, which better explains what we mean, hopefully.: “… Examples of sources include the webservices of IUCN (https://www.iucnredlist.org/) and Map of Life (https://www.mol.org) [52]. The distribution of each species or habitat category must be available as a separate layer for use in our tool.”

Line 248: suggest changing to “files downloaded from the IUCN...”

We followed your suggestion and changed it to: “Files downloaded from the IUCN webserver... “

Line 260: suggest deleting “of this type”

We deleted “of this type”.

Line 284: suggest changing “in the form of” to “as”

We changed “in the form of shapefiles” to: “as separate layers”, which we think is more appropriate.

Line 298: suggest “we strongly suggest using the GEnZ level…”

We followed your suggestion.

Line 302-307: suggest turning this whole paragraph into one or two sentences at the end of previous paragraph

Thank you. However, we think it would be better to break this down into two paragraphs as it will make it more clear to the reader that the tool has no limitations and that sources are available for ecosystems other than just terrestrial.

Line 328: suggest deleting “still”

We deleted “still”.

Line 329: suggest deleting “the” right before Biogeographic Units

We deleted “the” right before Biogeographic Units.

Line 338: suggest deleting “those”

We deleted “those”.

Line 348: suggest deleting the first “the”

We deleted the first “the”.

Line 361: suggest adding “of” right behind “layers”

We changed the whole paragraph starting with: “Files to be used with the NRA-Tool must be named according to the following convention: ...”

Line 364: suggest using “e.g.,” within parentheses and “for example” outside parentheses. Nevertheless, no matter which one you prefer, be consistent

Thank you. We followed your suggestions and changed “for example” to ““e.g.,” in parentheses.

Line 379-380: This sentence is identical with line 369-371 but with different references? One could be deleted

We deleted the sentence in lines 369-371.

Line 403: suggest deleting “still”

We deleted “still”.

Line 405: “such as” “e.g.” redundant. Please pick one

We deleted “such”.

Line 439-440: “also” “as well” redundant. Please pick one

We deleted “also”

Line 442: Why are there two China here…

t’s a typo. We deleted one China.

Line 443: Vietnam”,”

We inserted a comma after Vietnam.

Line 458: suggest deleting “more”

Thank you. We deleted “more”

Line 458-467: I'm not sure what is the importance of this detailed quantified comparison described in this paragraph and table 2 if there is NO DISCUSSION following up?

The different results from PA-A and PC-A are expected because they use different information...

Suggest moving most part of this paragraph and table 2 to supplementary files. A few sentences describing the overall differences/patterns between these two approaches (like what you did for “Conservation priority”) and Figs 8 and 9 should be enough.

Alternatively (you don't need to do this, just a suggestion), an analysis on the relationship between the change of ranking versus the environmental variability (heterogeneity) across countries might be more interesting...because the authors DID mention environmental variability could be one of the reasons causing the differences between these two approaches.

Thank you. We have inserted a new paragraph addressing the results and issues raised by the reviewer respectively: “For more in-depth analyses and interpretation, the tool provides the results not only in map form but also in tables containing all input information, calculated areas, and resulting scores (Table 3, S5 and S6). These outputs can provide insight into the discrepancies between the results of the two methodical approaches offered by our tool. These two approaches should be compared and evaluated in further methodological studies focusing on statistical effects and the functional relation between environmental variability across countries and value distributions.

Our own analysis shows that the more advanced PA-A provides more differentiated results than the PC-A because it takes area of overlap into account rather than simply using the number of overlapping polygons. This leads to differences in weighting, especially when large countries have relatively little overlap with focal and reference areas. The size of a country also plays a role when considering the number of species for which basic responsibility must be assumed. The larger the territory of a country, the greater the probability that it will include significant portions of the range of a species in the corresponding reference area—a species for which the country then bears basic responsibility. ”

Line 507: “like” “e.g.” redundant. Please pick one

We deleted “e.g.”

Line 548: suggest changing “focus” to “allocate”

We changed the sentence, moved it to the end of the section and wrote: “With this information, policy and decision makers will be better equipped to assess when and how policy should be adapted, reinforced, or developed to fulfill the Convention on Biological Diversity’s Aichi targets.”

Line 549-550: “…also including guiding capacity building” not sure what does this mean

Thank you. Please see our reply to your comment to Line 548 above.

Line 553: suggest changing “…for which we have distribution data available” to “…for which distribution data are available”

We followed this suggestion.

17 Nov 2020

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

PONE-D-20-05865R2

Dear Dr. Klenke,

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Pedro Abellán

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

24 Nov 2020

PONE-D-20-05865R2

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

Dear Dr. Klenke:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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PLOS ONE