Recognizing knowledge gaps in biodiversity for the preservation of endangered flora

Dr. shree R V

doi:10.65188/nurexus.1010

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Journal of MedVerse Research & Practice

Recognizing knowledge gaps in biodiversity for the preservation of

endangered flora

Dr. Shree R

1

Assistant Professor, Department of Chemistry and Biochemistry,

St. Joseph Arts & Science College (Autonomous), Cuddalore

Email ID: r.shree@gmail.com

Submission Date: 27.12.2024

Accepted Date: 23.01.2025

Published Date: 31.01.2025

DOI: 10.65188/nurexus.1010

article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits

unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Abstract

Background: Biodiversity data gaps can limit the identification and conservation of endangered plant

species. Incomplete geographic coverage, taxonomic uncertainty, and limited genetic information may

affect the assessment of species distribution and conservation priorities.

Objective: To assess spatial, taxonomic, genetic, and climate-related data gaps affecting the study's

selected endemic and endangered plant species.

Methods: This study integrated biodiversity occurrence records, taxonomic information, genetic sequence

records, and climatic variables. Species distribution models were developed using generalized linear

models, random forest, and gradient boosting algorithms. Model performance was assessed using the area

under the receiver operating characteristic curve (AUC), and spatial analyses were used to identify areas

with uneven sampling coverage and potential conservation priorities.

Results: The study dataset contained 10,965 species and 762,655 distribution records. Of these species,

8,295 were reported as having sufficient occurrence records for species distribution modelling, while 691

species were reported to have fewer than five occurrence records. These categories do not account for the

entire dataset and must be reconciled before the final results are reported. The principal spatial and

taxonomic findings should be presented using verified numerical results from the final analysis.

Conclusion: Integrating biodiversity, genetic, taxonomic, and climatic information may help identify gaps

in conservation research. Reliable conservation recommendations require transparent data sources, clearly

defined geographic coverage, validated model outputs, and reproducible analytical methods.

Keywords: Biodiversity, Endangered flora, Geographic distribution, Climate change

Introduction

The tropics harbour vast biodiversity, yet our knowledge remains fragmented. In recent decades,

scientific and conservation efforts have intensified to address these gaps, driven by the alarming decline

of species due to habitat destruction, overexploitation, pollution, invasive species, and climate change

[9]. Aquatic ecosystems, covering less than 1% of the Earth's surface, support over 50% of fish species

and 25% of vertebrates. Despite their ecological significance, policy measures often overlook freshwater

habitats [13].

The demand for botanical resources is global, particularly for medicinal, aesthetic, and commercial

purposes. Sub-Saharan Africa, rich in rare plant species, has become a prime target for botanical

extraction. Trees like sandalwood, valued for their essential oils, and rosewood, crucial for fuel, are

increasingly exploited [8]. Indigenous knowledge, passed down for generations, has played a crucial role

ORIGINAL ARTICLE

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in ecological management. However, only recently has the scientific community begun to acknowledge

its value [5]. Important gaps in biodiversity data remain across many ecosystems, particularly in areas

with limited geographic sampling, incomplete taxonomic information, or insufficient genetic data. These

gaps can restrict the accurate assessment of species distributions and hinder the identification of priority

areas for conservation.

Protected areas (PAs) struggle to maintain rare and threatened species due to financial constraints.

Prioritization based on regional extinction risks can assist PA managers in species monitoring [14].

Despite their ecological significance, historical botanical collections are rarely recognized under global

conservation frameworks. Efforts are needed to integrate these collections into biodiversity management

strategies [11]. Birds, essential ecosystem contributors and environmental indicators, lack a coordinated

global conservation framework. A research and conservation priority index (RCPI) has been proposed to

address these gaps [7].

Improved wildlife monitoring is crucial for effective conservation, particularly in developing nations

rich in biodiversity. Expanding ecological surveillance is essential to bridge critical knowledge gaps

[15]. Environmental DNA (eDNA) has emerged as a valuable tool for species identification, aiding

conservation efforts in ecologically significant yet understudied regions [1]. Addressing biodiversity

knowledge gaps requires prioritization, especially in vulnerable ecosystems. Large carnivore populations

have declined significantly, underscoring the need for systematic population monitoring [10]. Effective

management of invasive species must incorporate community engagement rather than relying solely on

government initiatives [3,4].

Materials and Methods

Study Design and Data Sources

This study used biodiversity records to examine gaps in the distributional, taxonomic, genetic, and climatic

information available for endemic plant species. Records associated with 123 wildlife conservation areas

were cross-referenced to compile information on plant species and their distribution. Taxonomic

information and species occurrence records were used to assess the availability and completeness of

biodiversity data. The compiled dataset was subsequently used for spatial analysis and species distribution

modelling to identify gaps in species occurrence records and areas requiring further investigation. The

identification of species, geographic coverage of the conservation areas, database sources, and criteria used

for selecting the conservation areas should be consistent with the original study records to ensure the

reproducibility of the analysis.

Georeferencing and Spatial Data

Species distribution records were georeferenced at a quarter-degree square (QDS) resolution, corresponding

to approximately 25 × 25 km. Spatial information was compiled from the National Vegetation Map, the

Custodians of Endangered Wildflowers initiative, and multiple biodiversity databases. These datasets were

supplemented with additional field-verified records to improve the spatial coverage and reliability of

occurrence information.

Genetic Data Analysis

Genetic data availability was assessed using records from GenBank. The database, containing DNA

sequence information for approximately 260,000 species, was queried for indigenous organisms to evaluate

the availability and potential taxonomic biases in genetic sequencing data. Analyses were performed using

R version 3.5.2. Genetic data availability was subsequently compared with species conservation status to

identify potentially underrepresented threatened species.

Species Distribution Modelling

Species distribution modelling was performed using occurrence records available for the plant species

included in the study dataset. Species with at least five recorded occurrences were considered for species

distribution modelling, while species with fewer than five occurrence records were assessed separately

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because of the limited availability of distributional information. The manuscript reports that 8,295 species

had at least five occurrence records and that 691 species had fewer than five records. Spatial range

estimates for the latter group were derived using ArcGIS version 10.5, as reported in the original

manuscript. These two categories account for 8,986 species out of the reported total of 10,965 species. The

classification of the remaining 1,979 species is not explained in the available text and must be resolved

before the final species counts and modelling results can be considered complete.

Climate Suitability Analysis

SDM outputs were overlaid with climate suitability maps to identify regions predicted to be ecologically

favourable for endemic plant species. Spatial resolution was standardized across datasets to facilitate

comparison. Areas with high predicted species richness were identified based on the combined spatial

modelling outputs. Coastal grid cells containing 50% or less land area were excluded to minimize potential

underestimation of species richness.

Assessment of Spatial and Taxonomic Gaps

Spatial sampling coverage was evaluated by comparing observed species richness with species richness

predicted by the SDMs. Sampling effort was assessed using sampling-density metrics to identify areas with

inadequate or uneven collection coverage. Road-network data were overlaid on sampling records to assess

potential accessibility-related biases in species collection.

Taxonomic gaps were assessed by comparing the availability of genetic sequence data with species

conservation status, including IUCN Red List classifications. This analysis was used to identify threatened

species that were underrepresented in genetic databases. Spatial and taxonomic gaps were subsequently

integrated to identify priority areas and species requiring additional sampling, genetic characterization, and

conservation research.

Data Analysis

Data integration, statistical analysis, and species distribution modelling were performed using R, while

spatial analyses and range estimation were conducted using ArcGIS version 10.5. Model outputs were

evaluated using AUC-based performance measures. Species richness, sampling density, genetic data

availability, conservation status, and predicted climatic suitability were integrated to identify biodiversity

hotspots and potential gaps in current conservation and research coverage.

Results

The spatial distribution of biodiversity data gaps

By combining Species Distribution Models (SDMs) and existing biodiversity frequency reports, we

mapped the regional characteristics of actual and predicted native species diversity across 1790 grid cells.

Our findings indicate that 4% of the country's indigenous organisms remain untested, despite our SDMs

showing that every grid cell contains an area with a temperature within a seasonal range of at least 69.

While SDMs and reported records display similar overall patterns of relative diversity, the predicted

established biodiversity from SDMs aligns well with current knowledge, even in grid cells with complete

ecosystems. The spatial analysis identified variation in predicted plant species richness across the study

region. Areas with higher predicted richness were identified from the species distribution model outputs.

The geographic units, grid-cell definitions, and species-richness estimates are reported according to the

verified spatial analysis. The names of the regions and ecological zones used in the analysis should

correspond to established geographic classifications and be supported by appropriate sources.

Distribution of biodiversity data gaps

This collection encompasses species from 175 families and 1061 genera, exhibiting diverse biological data

organization across taxonomic and chronological scales. The leading 10 families, in terms of native species

count, account for 61% of the indigenous plants in the database. Forty family groups are represented by just

one native species each. The Proteaceae, Asteraceae, and Fabaceae families boast the highest number of

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unique species location occurrence records. The top 10 families by sample constitute 69% of all occurrence

records in the database. In this study, three groups are represented by a single record. As expected, if all

species had equal sampling probability, generally, more species-rich groups were sampled more

extensively than less species-rich ones. However, sampling intensity varies significantly among families.

For example, the Anemiaceae family, despite having only one endemic species, has 508 entries.

Conversely, numerous underrepresented groups may warrant additional conservation attention.

Distribution of Threatened Plant Taxa

Regarding the family-wise distribution of endangered species, the IHR's Fab plants (84 threatened species),

Cyperaceae (65 species), and Poaceae (36 species) families were the most prevalent (Figure 1). Threatened

plant taxa were classified into the life-form categories used in the original analysis. The number of taxa in

each category is presented in Figure 2. The category labels, number of categories, and corresponding

counts should be checked against the underlying dataset to ensure that all groups are correctly defined and

that the reported totals are consistent. The vulnerable species exhibit significant disparities in their

distribution across states, influenced by forest cover and geographical location (Table 1).

Figure 1: Distribution of Threatened Plant Taxa

Table 1: Outcomes of IHR

Families

Number of Taxa

Fabaceae

84

Cyperaceae

65

Poaceae

36

Scrophulariaceae

26

Magnoliaceae

24

Orchidaceae

22

Pinaceae

16

Betulaceae

8

Cupressaceae

8

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Lythraceae

4

The Eastern Himalayan region, comprising states such as SK, MN, ML, TR, MZ, NL, and AR, along with

two constituent areas (AS hills and WB hills), harbors a greater number of endangered species compared to

the Western Himalayan states (UK, JK, and HP). Despite this, the Eastern Himalayan territories have been

subject to less scientific investigation, leaving much of their wildlife largely unexplored. Among the Indian

Himalayan Region (IHR) sectors, SK (203 species), HP (190 species), and JK (189 species) boast the

highest counts of threatened groups (refer to table 2).

Table 2: Life of threatened taxa

States of IHR

Number of taxa

H

S

T

C

Br

Pt

MZ

80

32

25

7

0

1

NL

75

35

33

10

1

5

SK

125

40

45

8

1

4

TR

60

25

60

10

0

1

UK

78

20

48

4

1

3

WB

30

0

15

0

1

AR

75

30

40

20

0

3

AS

60

10

35

2

0

2

HP

120

40

55

5

3

5

JK

130

40

45

5

1

7

MN

100

25

33

5

0

2

ML

110

38

45

10

0

2

The table summarizes the distribution of different plant taxa across 12 states of the Indian Himalayan

Region (IHR). Trees (T) and herbaceous plants (H) are the most abundant groups, with JK (Jammu &

Kashmir) and SK (Sikkim) having the highest numbers of taxa. Shrubs (S) and climbers (C) show moderate

representation, while bryophytes (Br) and pteridophytes (Pt) are comparatively rare across all states. This

indicates that the IHR harbors rich diversity in higher plants, particularly herbs and trees, whereas lower

plants are less widespread.

Population trends of threatened taxa

Over the past few generations, the composition of plant species has changed in response to various

ecological and social disturbances. Population trends among the assessed threatened plant taxa were

classified according to the criteria and data sources used in the study. The proportions of taxa with stable,

declining, increasing, and other or undetermined trends are reported in Figure 3 and Table 3. The

denominator used to calculate each percentage, the source of the population-trend information, and the

treatment of taxa with unavailable trend data are specified to ensure that all reported categories are

interpretable and internally consistent.

IUCN data indicate that merely 12% of species are currently experiencing population declines.

Furthermore, 35% of vulnerable plant species remain unassessed due to inaccessible locations or

insufficient published research.

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Table 3: Number of threatened plant taxa recorded by state in the Indian Himalayan Region

Number of Texas

States

UK

124

WB

25

SK

203

TR

103

MZ

121

NL

110

MN

147

ML

170

HP

190

JK

189

AR

147

AS

101

The table shows the total number of taxa recorded in different states of the Indian Himalayan Region (IHR).

Himachal Pradesh (HP) and Jammu & Kashmir (JK) have the highest species richness, with 190 and 189

taxa respectively, indicating high biodiversity. In contrast, West Bengal (WB) has the lowest, with only 25

taxa. Other states like ML, MN, SK, and AR also show relatively high diversity, highlighting regional

variation in plant species richness across the IHR.

Discussion

Recent research has increasingly emphasized that endangered plant species do not exist in isolation but are

embedded within complex ecological networks. Isbell et al. and Achieng et al. have highlighted that plant

survival is closely linked to interactions with pollinators, seed dispersers, soil microbiota, and symbiotic

partners, and that biodiversity loss disrupts these interconnected systems [5,1]. Similarly, studies focusing

on biodiversity hotspots have demonstrated that disruptions to associated insect and animal communities

can indirectly accelerate plant population declines, reinforcing the need to consider ecosystem-level

processes rather than single-species conservation [9,10]. Consequently, conservation strategies that focus

solely on individual species without accounting for these ecological interactions risk failure, as the

fundamental processes supporting growth, reproduction, and resilience remain unaddressed.

A holistic conservation approach is therefore essential to safeguard vulnerable plant populations.

Hernandez et al. emphasized that effective conservation planning must integrate ecological research, threat

assessment, and prioritization frameworks to address both species-level and ecosystem-level needs [4].

Innovative conservation techniques such as ex situ propagation, seed banking, and in vitro technologies

have been widely recommended by Kulak et al. and Ye et al., who demonstrated their importance in

preserving genetic diversity and preventing irreversible losses, particularly for narrowly distributed or

critically endangered plant taxa [7,15]. In addition, large-scale collaborative initiatives, such as those

described by Pirie et al., illustrate how coordinated global networks can successfully reduce extinction risk

when conservation actions are informed by rigorous science and shared expertise [11,12].

Community engagement and traditional ecological knowledge also play a critical role in holistic

conservation strategies. Sinthumule underscored that incorporating indigenous and local knowledge

systems enhances conservation effectiveness by aligning scientific interventions with long-standing

sustainable practices [13]. Furthermore, Kor and Diazgranados demonstrated that identifying important

plant areas based on ecological, cultural, and utilitarian values can help prioritize habitats that are vital for

both biodiversity conservation and human well-being [6]. Monitoring and evaluation remain equally

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important, as emphasized by Stephenson et al., who noted that systematic assessment of flora, fauna, and

funga is essential for measuring conservation impact and adapting management strategies over time [14].

Strengths of the Study

The study integrates multiple biodiversity, taxonomic, genetic, climatic, and spatial datasets to provide a

comprehensive assessment of endemic and endangered flora. The use of multiple SDM algorithms with

AUC-based ensemble weighting strengthens the prediction of species distributions. Incorporation of field-

verified records, genetic database information, and sampling-effort assessment provides a multidimensional

approach to identifying conservation priorities and data gaps.

Limitations of the Study

The absence of reliable true-absence records required the use of pseudo-absences, which may influence

SDM predictions. Species with fewer than five occurrence records could not be modelled using the same

approach and therefore required alternative spatial range estimation. Predicted climatic suitability and

species richness may not fully represent actual distributions because habitat fragmentation, species

interactions, and other ecological factors were not completely incorporated. Sampling records may also be

affected by accessibility and road-network-related biases, potentially resulting in uneven representation of

some geographic regions or taxa.

Conclusion

Conserving endangered plant species is essential for maintaining ecological balance, preserving

biodiversity, and sustaining resources vital to human well-being. Identifying and addressing gaps in

biodiversity research, including incomplete species distribution records, taxonomic uncertainties, limited

genetic information, and inadequate assessment of climatic suitability, can strengthen conservation

planning. Integrating reliable biodiversity data, genetic tools, and traditional ecological knowledge may

improve species identification and help prioritize conservation efforts. Furthermore, systematic threat

assessment and long-term monitoring are necessary to evaluate the impacts of habitat loss,

overexploitation, invasive species, and climate change on threatened plant populations. Strengthening data

availability, improving research methods, and implementing targeted, environmentally sustainable

conservation strategies are therefore important for protecting endangered flora, enhancing ecosystem

resilience, and supporting biodiversity conservation for future generations.

Declaration

Conflict of Interest: The authors declare that they have no competing interests or conflicts of interest

related to this work.

Funding Source: Nil

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