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

The diversity of life forms on Earth, known as biodiversity, plays a crucial role in maintaining ecological balance and

supporting human welfare. Endangered flora, comprising various plant species at risk of extinction, represents one of

the most susceptible elements of biodiversity. The preservation of these threatened plant species is essential for

sustaining ecosystem equilibrium and securing natural resources for upcoming generations. To implement effective

conservation strategies, it is vital to identify and tackle gaps in biodiversity research knowledge. This investigation

offers a thorough examination of the current understanding regarding endangered flora conservation, focusing on

several key aspects.

Evaluation and Surveillance of Threats: Comprehending the dangers faced by endangered plant species is crucial for

their protection. Research should concentrate on assessing threats such as habitat destruction, climate change effects,

invasive species, and overexploitation. Consistent monitoring is necessary to collect information on population

dynamics, geographical distribution, and environmental factors that influence conservation strategies.

Taxonomic Classification and Species Recognition: Precise taxonomy and species identification are essential for

developing targeted conservation approaches. In numerous instances, taxonomic uncertainties impede conservation

efforts, resulting in mismanagement and neglect of certain plant species. Advanced genetic methods and the

incorporation of traditional ecological wisdom can assist in resolving taxonomic challenges. Adaptation to Climate

Change: Climate change presents significant obstacles to the preservation of endangered flora.

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

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

its value [5].

Data on biodiversity distribution, known as “nonlinear gaps,” is often lacking in diverse ecosystems.

ORIGINAL ARTICLE

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Advanced computational models have been developed to enhance predictive accuracy and bridge these

information voids [6]. Invasive alien plants (IAPs) pose a serious threat to biodiversity and ecosystem

services. Due to the scattered nature of data and stakeholders, managing these species requires a

collaborative approach. Approximately 80% of land is privately owned, necessitating adaptive

stewardship for effective conservation [2].

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

A biodiversity data integration and spatial modelling study was conducted to assess the distribution, genetic

data availability, climate suitability, and spatial and taxonomic gaps of endemic and endangered flora. Data

on 123 wildlife conservation areas were cross-referenced using the Registry of Animals to compile a

repository of endemic plant species. The resulting dataset comprised 175 relationships, 1,061 groups,

10,965 species, and 762,655 distribution records. Taxonomic information was obtained from the Central

Plants Checklist and the Angiosperm database and validated against national botanical databases.

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 Models (SDMs) were developed using 19 bioclimatic variables obtained from the

WorldClim database at a spatial resolution of 10 arc-minutes. Generalized linear models, random forest,

and gradient boosting algorithms were implemented in R. As reliable true-absence data were unavailable,

pseudo-absence records were generated using national boundary constraints.

For species with adequate occurrence information, 75% of the occurrence records were used for model

training and 25% for validation. Model performance was evaluated using the Area Under the Curve (AUC),

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and individual model outputs were combined using AUC-based weighting to improve predictive accuracy.

Species with at least five recorded occurrences were included in SDM analysis, resulting in 8,295 species.

For species with fewer than five occurrence records, comprising 691 species, spatial range estimates were

derived using ArcGIS version 10.5.

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 Tropical Cape Biome, also referred to as the Coral Cape Ecological Hotspot, is expected

to have the highest native species count, with 4908 species per grid cell. The Indian Oceans Coastal Area

communities encompass the grid cells with the greatest predicted unique complexity. The Western Floristic

Country, a biological hotspot, contains the flora with the highest mean predicted total wealth, boasting a

predicted maximum of 5,303 varieties per grid cell for unique complexity.

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

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

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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.

Diversity of threaded

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). The at-risk

groups were further categorized into five life forms: climbers (15 species), bryophytes (5 species),

pteridophytes (15 species), and plants (286 species; Figure 2). The vulnerable species exhibit significant

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

Figure 1: Dominant families of threatened of IHR

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

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

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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. An examination of endangered plant community patterns in the IHR

revealed that 38% of species maintained stable populations, 12% exhibited declining trends, and only 2%

showed increasing trends (Figure 3 and table 3). 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.

Table 3: Numerical outcomes of distribution state (IHR)

Number of Texas

States

UK

124

WB

25

SK

203

TR

103

MZ

121

NL

110

MN

147

ML

170

HP

190

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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

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

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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 vital for maintaining ecological balance and securing resources

essential for human survival. Addressing knowledge gaps in biodiversity research is improving

conservation strategies. Implementing Threat Assessment and Monitoring is crucial for understanding and

mitigating the impacts of overexploitation, invasive species, habitat loss, and global climate change.

Accurate taxonomic identification and species recognition are fundamental to developing effective

conservation plans that incorporate traditional ecological knowledge. These approaches also underscore the

importance of advanced genetic tools. The study further emphasizes the urgent need for environmentally

sustainable adaptation strategies in response to changing climate conditions. By establishing targeted

conservation initiatives and bridging these information gaps, efforts can be made to safeguard threatened

plant species, thereby strengthening ecosystems and ensuring an environmentally sustainable legacy 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: Nil

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