Floristic differentiation along coastal-inland gradients of the Atlantic Forest: insights from an urban ecotone in southeastern Brazil

Abstract

The Atlantic Forest of Brazil exhibits marked climatic and edaphic gradients that generate strong floristic turnover across space. Yet, coastal urban remnants remain underexplored as potential ecotones where climatic filtering and anthropogenic influences interact to shape plant assemblages. Here, we present a comprehensive floristic inventory of the Parque Natural Municipal de Niterói (PARNIT), an urban protected forest in southeastern Brazil, and compare its vascular plant composition with that of 21 other Atlantic Forest protected areas. A total of 707 species were recorded for PARNIT. Multivariate analyses (Jaccard/UPGMA and db-RDA) revealed that mean annual temperature and precipitation during the driest month are the primary drivers of floristic variation among sites. Despite its official classification as Dense Ombrophilous Forest, PARNIT clustered with coastal and seasonally dry areas, suggesting that local communities are structured by climatic filters similar to those operating in semi-deciduous and restinga forests. We propose that PARNIT presents traits of an urban coastal ecotone, capturing the transition between humid and seasonally dry Atlantic Forest types. These results emphasize the role of small urban forests in maintaining biogeographic diversity and highlight the need to revise phytophysiognomic classifications to better reflect the climatic and compositional continuum of the Atlantic Forest.

Keywords:
Ecotone; Floristic inventory; Flora; Parque Natural Municipal de Niterói; Protected area; Urban Forest

Introduction

The Brazilian Atlantic Forest is one of the world's most diverse and threatened biomes, recognized for its exceptional biodiversity and high levels of endemism (Mittermeier et al., 2011; Hrdina & Romportl, 2017; Habel et al., 2019). Despite its ecological importance, the biome has undergone extensive deforestation and fragmentation due to human activities over the past 500 years (Dean, 1996; Joly et al., 2014). Early estimates suggested that only 11-16% of its original extent remains, but more recent assessments - including secondary forests and small fragments - indicate that up to 28% of the biome persists (Rezende et al., 2018a). However, much of this remaining forest is highly fragmented, with most patches being small, isolated, and unprotected, and only 10% officially designated as protected areas (Vieira et al., 2019; Vancine et al., 2024). Nevertheless, the Atlantic Forest still harbors a high degree of species richness, particularly among trees, birds, mammals, reptiles, and amphibians (Metzger, 2009; Lima et al., 2020; Rojas-Padilla et al., 2020; Dalapicolla et al., 2021). And although climate change poses a growing challenge to biodiversity conservation, the primary threat to this biome today is still land-use change (agriculture, urban expansion and logging), leading to severe habitat loss and fragmentation (Davison et al., 2021; Caro et al., 2022). As a consequence, a significant proportion of its flora and fauna faces an increased risk of extinction. Conservation efforts have focused on preserving large, mature forest remnants while managing smaller fragments to maintain ecological connectivity. Restoration initiatives, particularly in key areas, are prioritized to enhance habitat continuity and reduce edge effects. However, the most effective long-term strategy for safeguarding threatened biomes remains the establishment and proper management of protected areas for long periods of time (Souza & Prevedello, 2020; Sivisaca et al., 2024). Still, gauging the success of conservation efforts relies heavily on thorough species inventories and a deep understanding of how biodiversity is distributed along the territory.

The Atlantic Forest domain, which refers to an extensive territory along the eastern South American coast (Neves et al., 2017; Rezende et al., 2018a), can be delimited by the biome’s biotic and environmental characteristics, although political interests that directly affect conservation strategies may also play an important role (Rezende et al., 2018b). Nevertheless, due to its wide latitudinal gradient, the domain encompasses high phytophysiognomic heterogeneity - including dense ombrophilous forests, mixed ombrophilous forests, semi-deciduous seasonal forests, montane forests, altitude fields, restingas, and mangroves (Muylaert et al., 2018). This heterogeneity arises from variations in climate, elevation, soil formation, and geographic history, all of which influence species composition and distribution (Klipel et al., 2023). The presence of massive mountain ranges along the Brazilian eastern coast is largely responsible for introducing environmental heterogeneity and high rates of endemism (Silveira et al., 2019; Kamimura et al., 2022). Consequently, conservation strategies cannot treat the Atlantic Forest as a single, uniform entity, but must instead consider regional ecological nuances (Neves et al., 2017). Understanding these local and regional differences is essential for designing effective conservation measures, as species assemblages and ecological processes vary significantly across the biome.

The municipality of Niterói, located in the state of Rio de Janeiro, Brazil, is fully embedded within the Atlantic Forest domain. Despite its high degree of urbanization, approximately one-third of its territory is encompassed by protected areas (Prefeitura Municipal de Niterói, 2018). Among these, the Parque Natural Municipal de Niterói (PARNIT) stands out as frequently visited and most recently delimited fully protected areas in the region. However, despite its social and ecological relevance, this is the first systematic floristic inventory conducted in the area. It is generally accepted that the vegetation in Niterói is a continuum of other Dense Ombrophilous Forests like other Atlantic Forest remnants in the state of Rio de Janeiro. However, if the singularities of a specific protected area are overlooked, this could underestimate its relevance and compromise its safeguarding in the future. Furthermore, preliminary observations carried out before and during the field trips revealed heavily marked dry seasons accompanied by a landscape shift that is not characteristic of evergreen forests such as the ombrophilous formations. Thus, we aimed to (i) compile a comprehensive checklist of vascular plants for PARNIT based on field collections and herbarium records, and (ii) use this checklist as the empirical basis for a presence/absence comparison with other Atlantic Forest protected areas, testing whether PARNIT aligns floristically with humid ombrophilous forests or shows stronger affinity with coastal and seasonally drier sites along the Atlantic Forest spectrum.

Materials and Methods

Study area

PARNIT is a fully protected municipal conservation unit created in 2014 (Municipal Decree No. 11,744) and later amended in 2020, totaling 897 ha located in the municipality of Niterói, Rio de Janeiro state, Brazil (22.9264S, 43.0789W) (Prefeitura Municipal de Niterói, 2021). The park is an urban forest that protects an important remnant of the Atlantic Forest. The area is composed of a variety of vegetation types, including restinga, mangrove, rocky outcrops, shrubby and forested areas, with elevations ranging from 0-348 m and a tropical climate with dry winters (Aw according to Köppen climate classification) (Alvares et al., 2013). Maximum mean temperatures range from 24.5°C (July) to 30.9 °C (February), while minimum mean temperatures range from 16.9 °C (July) to 23.2 °C (January). Mean annual rainfall is 1103 mm, and the rainy season begins in spring and lasts through summer. Precipitation is lowest in July and August, dropping below 60 mm (Prefeitura Municipal de Niterói, 2021).

The park is spatially discontinuous and structured as a mosaic of areas grouped into three management sectors: (i) Montanha da Viração (including Morro da Viração/Parque da Cidade and associated hills and rock outcrops), (ii) Costeiro-Lagunar (including the surroundings of Lagoa de Piratininga and coastal/lagoon islands, as well as Praia do Sossego and Ponta da Galheta), and (iii) Guanabara (including coastal rocks/caves near the MAC and islands such as Boa Viagem and Cardos) (Prefeitura Municipal de Niterói, 2021). Edaphic and geomorphological conditions vary markedly among sectors, contributing to within-park heterogeneity. Montanha da Viração is dominated by crystalline rocky substrates (gneiss with mafic dikes), steep relief, and shallow soils on slopes and ridges, whereas Costeiro-Lagunar includes fluviomarine plains with poorly drained fine sediments and coastal plains with sandy deposits; Guanabara comprises coastal rocky outcrops and wave-influenced features. These formations occur as a spatially discontinuous mosaic, which likely contributes to within-park heterogeneity; however, the comparative analyses in this study treat PARNIT as a single conservation unit for consistency with the available regional datasets. Thus, our floristic checklist integrates records from all three sectors. For broad-scale comparisons with other protected areas, PARNIT was treated as a single pooled assemblage (presence/absence at the protected-area scale).

Floristic survey and species list

The floristic survey was conducted through monthly expeditions from September 2021 to December 2024, using an active search - “walking” - method (Filgueiras et al., 1994) to cover all major zones of the park, with field effort distributed across the three PARNIT sectors and their main vegetation formations. This approach is commonly used in floristic inventories, aiming to maximize detection across heterogeneous habitats and microhabitats. To reduce repeated sampling of the same microhabitats, we distributed effort across different trails, secondary paths, and habitat patches, and targeted under-sampled environments (e.g., rock outcrops, forest edges, wet depressions, and lagoon/coastal margins) across the park’s mosaic. We acknowledge that some components (e.g., canopy taxa, short-lived herbs, and certain epiphytes) are intrinsically harder to detect and may require additional targeted campaigns or specific techniques (e.g., canopy access) for full representation. Fertile specimens of vascular plants were collected, processed, and deposited in the Herbarium NIT (Herbário de Niterói), and duplicates were sent to the Herbarium RB at the Jardim Botânico do Rio de Janeiro. Collection permit was obtained from Secretaria Municipal de Meio Ambiente e Recursos Hídricos de Niterói (process number: 250000928/2021). Identification followed APG IV (2016) for Angiosperms and PPG I (2016) for ferns and lycophytes. Plants were identified to species level through consulting specialized bibliography and herbaria materials. Our records were then compiled with records from previous collections deposited in other herbaria to produce a vascular plant species checklist. Records were extracted from the JABOT database (https://jabot.jbrj.gov.br/v3/). Species names were verified for spelling and synonyms using the Flora e Funga do Brasil database (http://floradobrasil.jbrj.gov.br/), which was also consulted for determining species distribution ranges and life forms. Species conservation statuses were consulted on two official government lists: the National Center of Flora Conservation (CNCFlora, 2013) and the Ministry of Environment and Climate Change (Brasil, 2022). Threatened species were defined strictly as CR, EN, and VU, and only these categories were used when reporting the number of threatened taxa. Voucher specimen numbers can be found in the final species list (Tables S1 and S2).

Species Accumulation Curve

To evaluate species richness as a function of sampling effort throughout our survey, a species accumulation curve was constructed. This analysis provides insight into the rate at which new species are observed with increasing standardized sampling events and helps determine whether sampling sufficiency has been reached. The cumulative species richness curve was calculated using the ‘specaccum’ function from the vegan package in R (Oksanen et al., 2024) and plotted including a shaded 95% confidence interval.

Estimation of Sampling Effort and Species Richness

In order to estimate the necessary number of sampling events required to portray species richness in the PARNIT area, we employed a statistical approach based on observed species occurrences per sampling event. The following formula was used:

$$n=(SD÷x̅.P{)}^2$$

where n is the required number of sampling events, P is the desired precision (set as 20%), SD is the standard deviation of species richness across sampling events, and (x̅) is the mean species richness per sampling event. Species richness for each sampling event was calculated by summing the number of species found in each field trip on a presence/absence matrix. This analysis was restricted to sampling events carried out during our survey, since previous collecting events might have been random sightings and not part of a standardized sampling event.

To provide estimates of total species richness for the PARNIT area, we employed two non-parametric estimators: Chao and Second-Order Jackknife (Jackknife2), using the same aforementioned presence/absence matrix (Chao & Chiu, 2016). Chao was chosen because it accounts for rare species and provides a conservative estimate of species richness. This means that, though it tends to underestimate richness in a heterogeneous community such as PARNIT, it is best suited for datasets where under-sampling is a concern, as is often the case for dense, highly diverse biomes with tall canopies such as the Atlantic Forest. In contrast, Jackknife2 was chosen because it corrects for heterogeneity in species distribution, providing greater accuracy for larger, more variable datasets where species occur at different frequencies across samples. Together, Chao and Jackknife2 provide complementary perspectives: Chao estimates richness assuming unseen species are mostly rare, while Jackknife2 estimates richness based on broader sampling patterns, correcting for sample size bias.

Composition of protected areas

Species composition of PARNIT was compared to 21 other protected areas from southeastern Brazil located within the original Atlantic Forest coverage. Areas were selected based on proximity and available species lists elaborated through floristic surveys and published at Rio de Janeiro Botanical Garden’s official catalogue - Catálogo de Plantas das Unidades de Conservação do Brasil (https://catalogo-ucs-brasil.jbrj.gov.br/). The existence of each published species list means that the sites were thoroughly sampled and species identification has been revised by specialists. Their names, name acronyms and acronym of Brazilian states in which they are located follow: Parque Nacional do Descobrimento (PND) - BA (Bochorny et al., 2024); Área de Proteção Ambiental Mestre Álvaro (APAMA) - ES (Dutra et al., 2023); Floresta Nacional do Rio Preto (FLONA) - ES (Carrijo et al., 2021); Parque Estadual da Pedra Azul (PEPA) - ES (Marcusso et al., 2022a); Parque Estadual do Forno Grande (PEFG) - ES (Bochorny et al., 2022); Parque Estadual Mata das Flores (PEMF) - ES (Carrijo et al., 2024); Parque Estadual Paulo César Vinha (PEPCV) - ES (Guarnier et al., 2022); Reserva Biológica de Duas Bocas (RBDB) - ES (Marcusso et al., 2022b); Estação Ecológica de Angatuba (EEA) - SP (Colli-Silva et al., 2021a); Estação Ecológica de Bananal (EEB) - SP (Colli-Silva et al., 2021b); Estação Ecológica de Avaré (EEAV) - SP (Colli-Silva et al., 2021c); Parque Estadual Carlos Botelho (PECB) - SP (Colli-Silva et al., 2021d); Parque Estadual de Porto Ferreira (PEPF) - SP (Sabino et al., 2022); Parque Estadual Turístico do Alto Ribeira (PETAR) - SP (Marcusso et al., 2024); Monumento Natural do Arquipélago das Ilhas Cagarras (MNAIC) - RJ (Bovini et al., 2023); Parque Estadual da Costa do Sol (PECS) - RJ (Sá et al., 2021); Parque Estadual da Pedra Selada (PEPS) - RJ (Waga et al., 2022); Parque Estadual da Serra da Concórdia (PESC) - RJ (Waga et al., 2023); Reserva Biológica do Tinguá (RBT) - RJ (Bochorny et al., 2023); Parque Nacional do Itatiaia (PNI) - RJ/MG (Carrijo et al., 2018); Parque Nacional do Caparaó (PNC) - MG (Carrijo et al., 2020). Species lists were filtered to include only vascular plants. A presence/absence matrix was created with all 22 areas and the 6735 species found in them. Scientific names were verified using the flora package in R (https://github.com/gustavobio/flora), which checks for misspellings and synonyms using the Brazilian Flora 2020 database (http://floradobrasil.jbrj.gov.br/).

Jaccard Similarity Index and Cluster Analysis

To explore the relationships among preserved areas based on species composition, we performed a hierarchical cluster analysis using the Jaccard similarity index. This method was chosen in order to group sampling units - in our case protected areas - based on their shared species. Additionally, the Jaccard index measures similarity based on shared presences only, ignoring co-absences (which are less informative ecologically). This reduces the influence of double zeros and makes it ecologically meaningful for comparing species composition between sites, especially when absences could be due to sampling limitations rather than true absence. We employed bootstrap analysis (nboot=1000) to assess the statistical support for clusters. The Jaccard dissimilarity was computed with the 'vegdist()' function from the vegan package. Areas were clustered using the UPGMA (Unweighted Pair Group Method with Arithmetic Mean) method. To assess the statistical support for clusters derived from hierarchical analysis, we used the 'pvclust()' function, which performs hierarchical clustering combined with bootstrap resampling.

Distance-Based Redundancy Analysis (db-RDA)

To model the fraction of species composition explained by environmental factors, we performed a Distance-Based Redundancy Analysis (db-RDA). This multivariate ordination technique is well suited for ecological data as it allows the modeling of community dissimilarity in response to multiple environmental predictors. We tested the hypothesis that variation in plant species composition across protected areas reflects environmental gradients within the Atlantic Forest biome, rather than simple geographic proximity. The analysis was based on a Jaccard dissimilarity matrix derived from species presence/absence data, which served as the response variable. Normalized environmental variables-including climatic and geographic parameters-were used as explanatory variables. The statistical significance of the db-RDA model and its axes was assessed using permutation tests (n = 999). (Legendre & Anderson, 1999).

Dataset of environmental variables obtained from the WorldClim (https://www.worldclim.org/) database using geographic coordinates obtained from Google Earth (https://www.google.com.br/earth/). Preliminarily, the variables chosen to reflect environmental conditions and seasonality included annual mean temperature, maximum temperature of the warmest month, minimum temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, and precipitation of the driest quarter. All environmental variables were normalized (z-scores) to standardize their scales. To minimize redundancy among predictors, we examined the pairwise correlation of environmental variables using the Pearson correlation coefficient. Highly correlated variables (r0.7) were identified and excluded to reduce multicollinearity, which resulted in the analysis including only two of the considered variables: annual mean temperature and precipitation of the driest month. Geographical distance was also included in the analysis to gauge the amount of similarity due to geographic distance alone, and in interaction with the environmental variables. Because comparable soil datasets are not consistently available for all comparison protected areas, we did not include edaphic variables in the regional db-RDA; instead, we focused on climate predictors, while acknowledging that edaphic variation within PARNIT likely influences local floristic turnover.

Data processing and formatting

Data processing and analyses presented henceforth were performed using the R software (v. 4.4.1) (R Core Team, 2024) and the packages ade4 (Dray & Dufour, 2007), dplyr (Wickham et al., 2026), ecodist (Goslee & Urban, 2007), flora (Carvalho, 2024), geosphere (Hijmans, 2026), ggplot2 (Wickham, 2016), magrittr (Bache & Wickham, 2026), stringr (Wickham, 2025) and vegan (Oksanen et al., 2024). All scripts, as well as the present text, were revised for code and grammar correction with the support of chatGPT (https://chatgpt.com/).

Results

Flora of PARNIT

We have compiled a list of 707 species, belonging to 398 genera, 118 families of vascular plants, known to occur within the Park’s area (Tables S1 and S2). By far, the family with the most species was Fabaceae (68), followed by Myrtaceae (47) and Euphorbiaceae (28) (Fig. 1). From the total, only 164 species have been assessed regarding their conservation status, with 543 not yet evaluated. A total of 100 species found in PARNIT are categorized as Least Concern (LC), while 64 are considered threatened at some level between Vulnerable (VU) and Critically Endangered (CR). Regarding endemism rates, 172 of all species found in PARNIT are restricted to the Atlantic Forest biome. Meanwhile, 98 species are endemic to the southeastern region of Brazil (namely Espírito Santo, Minas Gerais, Rio de Janeiro, and São Paulo states), 50 of which have only been recorded in Rio de Janeiro state.

Figure 1:
Number of species per family of angiosperms (left) and ferns/lycophytes (right) found in Parque Natural Municipal de Niterói (PARNIT), Rio de Janeiro, Brazil. Angiosperm families with six species or less are not shown.

Species Richness in PARNIT

The species accumulation curve (Fig. 2) provides a graphical representation of species discovery throughout our survey, showing how quickly new species are detected as further samples are added. The curve should be interpreted as an indicator of sampling completeness under the present protocol, which ultimately includes herbarium records to the total species pool; it does not provide a definitive estimate of total richness, but rather whether additional effort is likely to yield new records. Species richness estimators suggest that the true number of species in PARNIT is likely between 673 (Chao) and 753 (Jackknife2) (Table 1). Considering our collections and records from other herbaria, PARNIT exhibits a high species richness when compared to other protected areas, taking into account their sizes (ha), as reported in Table 2.

Figure 2:
Species accumulation curve for 64 field trips carried out between 2021 and 2024 in Parque Natural Municipal de Niterói (PARNIT), Rio de Janeiro, Brazil. The curve is used to evaluate sampling completeness and the expected gain of additional effort, not to assert that the inventory is exhaustive.

Table 1:
Observed and estimated species richness of Parque Natural Municipal de Niterói (PARNIT), Rio de Janeiro, Brazil.

Species found in fieldwork (2021 -2024)	Total species including historical records	Number of sampling events (2021-2024)	Estimated samples needed	Estimated richness (Chao)	Estimated richness (Jackknife2)
436	707	64	50	673	753

Table 2:
Profile of 22 protected areas - Parque Nacional do Descobrimento (PND); Área de Proteção Ambiental Mestre Álvaro (APAMA); Floresta Nacional do Rio Preto (FLONA); Parque Estadual da Pedra Azul (PEPA); Parque Estadual do Forno Grande (PEFG); Parque Estadual Mata das Flores (PEMF); Parque Estadual Paulo César Vinha (PEPCV); Reserva Biológica de Duas Bocas (RBDB); Estação Ecológica de Angatuba (EEA); Estação Ecológica de Bananal (EEB); Estação Ecológica de Avaré (EEAV); Parque Estadual Carlos Botelho (PECB); Parque Estadual de Porto Ferreira (PEPF); Parque Estadual Turístico do Alto Ribeira (PETAR); Monumento Natural do Arquipélago das Ilhas Cagarras (MNAIC); Parque Estadual da Costa do Sol (PECS); Parque Estadual da Pedra Selada (PEPS); Parque Estadual da Serra da Concórdia (PESC); Reserva Biológica do Tinguá (RBT); Parque Nacional do Itatiaia (PNI); Parque Nacional do Caparaó (PNC) - the state in which they are located - Bahia (BA); Espírito Santo (ES); Minas Gerais (MG); Rio de Janeiro (RJ); São Paulo (SP) - their species richness, size of delimited area and official phytophysiognomy (Dense Ombrophilous Forest (D.O.F.); Seasonal Semideciduous Forests (S.S.F.); High Altitude Fields (H.A.F.); Cerrado; Restinga)

Area	State	Species listed	Size (ha)	Phytophysiognomy
PND	BA	226	22.608	D.O.F. - Lowland
APAMA	ES	548	3.470	D.O.F. - Montane/Submontane
FLONA	ES	721	2.830	D.O.F. - Lowland
PEPA	ES	225	1.240	D.O.F. - Montane/High-montane
PEFG	ES	952	914	D.O.F. - Montane/High-montane
PEMF	ES	345	800	D.O.F. - Montane
PEPCV	ES	673	1.500	Restinga
RBDB	ES	839	3.000	D.O.F.
PNC	MG	1785	31.000	D.O.F./S.S.F. - Montane/High-montane
PNI	RJ/MG	2605	30.000	D.O.F./S.S.F. - Montane/High-montane; H.A.F.
PARNIT	RJ	706	897	D.O.F.
MNAIC	RJ	138	91	Restinga
PECS	RJ	1151	9.841	Restinga/S.S.F.
PEPS	RJ	302	8.036	D.O.F. - Montane
PESC	RJ	231	5.952	S.S.F. - Alluvial/Montane/Submontane
RBT	RJ	1290	26.260	D.O.F. - Lowland/Sub-High-Montane
EEA	SP	233	1.394	S.S.F./Cerrado
EEB	SP	491	884	D.O.F. - Montane/High-montane
EEAV	SP	59	720	Cerrado
PECB	SP	978	37.644	D.O.F. - Montane/Submontane
PEPF	SP	507	611	S.S.F./Cerrado
PETAR	SP	579	35.000	D.O.F.

Floristic similarity and cluster analysis of protected areas

Using the standardized checklist compiled here, we assembled a presence/absence matrix for PARNIT and 21 other protected areas, which formed the input for the UPGMA clustering and db-RDA analyses. The cluster analysis revealed distinct floristic relationships among the studied areas, with PARNIT grouping more closely with other coastal sites rather than with geographically nearer inland areas (Fig. 3). This clustering pattern was reinforced by the db-RDA (Fig. 4), which identified annual mean temperature and precipitation of the driest month as the main environmental drivers of floristic composition. These variables significantly influenced PARNIT’s placement in the ordination space, aligning it with warmer and seasonally dry coastal environments. The first two axes explained a substantial proportion of the variation in floristic composition (db-RDA1: 45.01%; db-RDA2: 29.44%), both of which were statistically significant (permutation test, p 0.05).

Figure 3:
Hierarchical cluster analysis of 22 protected areas from Southeastern Brazil, based on a presence/absence matrix and the 6735 species found in them using the Jaccard similarity index. Correspondence with the map shows that geographic proximity is generally not reflected by clustering through floristic similarity. Parque Nacional do Descobrimento (PND); Área de Proteção Ambiental Mestre Álvaro (APAMA); Floresta Nacional do Rio Preto (FLONA); Parque Estadual da Pedra Azul (PEPA); Parque Estadual do Forno Grande (PEFG); Parque Estadual Mata das Flores (PEMF); Parque Estadual Paulo César Vinha (PEPCV); Reserva Biológica de Duas Bocas (RBDB); Estação Ecológica de Angatuba (EEA); Estação Ecológica de Bananal (EEB); Estação Ecológica de Avaré (EEAV); Parque Estadual Carlos Botelho (PECB); Parque Estadual de Porto Ferreira (PEPF); Parque Estadual Turístico do Alto Ribeira (PETAR); Monumento Natural do Arquipélago das Ilhas Cagarras (MNAIC); Parque Estadual da Costa do Sol (PECS); Parque Estadual da Pedra Selada (PEPS); Parque Estadual da Serra da Concórdia (PESC); Reserva Biológica do Tinguá (RBT); Parque Nacional do Itatiaia (PNI); Parque Nacional do Caparaó (PNC).

Figure 4:
Distance-Based Redundancy Analysis of db-RDA of 22 protected areas from Southeastern Brazil, based on species lists and environmental variables - bio1: annual mean temperature. bio14: precipitation of the driest month; LAT: latitude; Parque Nacional do Descobrimento (PND); Área de Proteção Ambiental Mestre Álvaro (APAMA); Floresta Nacional do Rio Preto (FLONA); Parque Estadual da Pedra Azul (PEPA); Parque Estadual do Forno Grande (PEFG); Parque Estadual Mata das Flores (PEMF); Parque Estadual Paulo César Vinha (PEPCV); Reserva Biológica de Duas Bocas (RBDB); Estação Ecológica de Angatuba (EEA); Estação Ecológica de Bananal (EEB); Estação Ecológica de Avaré (EEAV); Parque Estadual Carlos Botelho (PECB); Parque Estadual de Porto Ferreira (PEPF); Parque Estadual Turístico do Alto Ribeira (PETAR); Monumento Natural do Arquipélago das Ilhas Cagarras (MNAIC); Parque Estadual da Costa do Sol (PECS); Parque Estadual da Pedra Selada (PEPS); Parque Estadual da Serra da Concórdia (PESC); Reserva Biológica do Tinguá (RBT); Parque Nacional do Itatiaia (PNI); Parque Nacional do Caparaó (PNC).

A total of 91 species were exclusive to PARNIT (Table 3), and 51 species were present in more than half of the areas analyzed (Table 4). Moreover, 25 species do not occur in any of the remaining 19 reserves analyzed other than PARNIT and the two other continental coastal areas that share close floristic similarities (PECS and PEPCV) (Table 5).

Table 3:
Species exclusive to Parque Natural Municipal de Niterói (PARNIT), , Rio de Janeiro, Brazil, when compared with other 21 studied areas, and their respective conservation status (LC - Least Concern; VU - Vulnerable; EN - Endangered; CR - Critically Endangered). Species with blank status have not been assessed yet.

Family	Species	Status
Acanthaceae	Avicennia schaueriana Stapf & Leechm. ex Moldenke
Acanthaceae	Thunbergia grandiflora Roxb.
Amaranthaceae	Alternanthera paronychioides A.St.-Hil.	LC
Annonaceae	Annona ferruginea (R.E.Fr.) H.Rainer	CR
Annonaceae	Annona parviflora (A.St.-Hil.) H.Rainer	VU
Araceae	Anthurium luschnathianum Kunth	EN
Araceae	Syngonium angustatum Schott
Araceae	Xanthosoma sagittifolium (L.) Schott
Araliaceae	Dendropanax monogynus (Vell.) Seem.
Arecaceae	Desmoncus polyacanthos Mart.
Aristolochiaceae	Aristolochia cynanchifolia Mart. & Zucc.
Aristolochiaceae	Aristolochia raja Mart. & Zucc.	EN
Aristolochiaceae	Aristolochia rumicifolia Mart. & Zucc.
Aristolochiaceae	Aristolochia trilobata L.
Asparagaceae	Herreria salsaparilha Mart.
Asteraceae	Albertinia brasiliensis Spreng.
Begoniaceae	Begonia sanguinea Raddi	VU
Begoniaceae	Begonia tomentosa Schott	VU
Bignoniaceae	Adenocalymma subsessilifolium DC.
Bignoniaceae	Tynanthus cognatus (Cham.) Miers
Cactaceae	Rhipsalis mesembryanthemoides Haw.	EN
Clusiaceae	Tovomita leucantha (Schltdl.) Planch. & Triana
Combretaceae	Combretum indicum (L.) Jongkind
Convolvulaceae	Ipomoea nil (L.) Roth
Convolvulaceae	Jacquemontia holosericea (Weinm.) O'Donell
Convolvulaceae	Jacquemontia pentanthos (Jacq.) G.Don
Cucurbitaceae	Cayaponia trilobata (Cogn.) Cogn.	LC
Cyperaceae	Cyperus meyenianus Kunth
Cyperaceae	Cyperus odoratus L.
Dioscoreaceae	Dioscorea dodecaneura Vell.
Dioscoreaceae	Dioscorea hassleriana Chodat
Dioscoreaceae	Dioscorea leptostachya Gardner
Dioscoreaceae	Dioscorea marginata Griseb.
Elaeocarpaceae	Sloanea garckeana K.Schum.	LC
Euphorbiaceae	Algernonia brasiliensis Baill.	VU
Euphorbiaceae	Algernonia leandrii (Baill.) G.L.Webster
Euphorbiaceae	Croton urticifolius Lam.
Euphorbiaceae	Dalechampia brasiliensis Lam.
Fabaceae	Chamaecrista glandulosa (L.) Greene
Fabaceae	Clitoria fairchildiana R.A.Howard
Fabaceae	Guilandina bonduc L.
Fabaceae	Inga congesta T.D.Penn.
Fabaceae	Inga cordistipula Mart.	VU
Fabaceae	Mimosa caesalpiniifolia Benth.	LC
Fabaceae	Senegalia duartei Seigler & Ebinger
Fabaceae	Teramnus volubilis Sw.
Gesneriaceae	Sinningia pusilla (Mart.) Baill.	EN
Heliotropiaceae	Euploca procumbens (Mill.) Diane & Hilger
Malpighiaceae	Amorimia rigida (A.Juss.) W.R.Anderson
Malpighiaceae	Heteropterys ternstroemiifolia A.Juss.	EN
Malpighiaceae	Stigmaphyllon vitifolium A.Juss.	CR
Malvaceae	Quararibea angustifolia (Mart.) C.D.M. Ferreira & Bovini	EN
Melastomataceae	Pleroma vimineum (D. Don) D. Don
Meliaceae	Trichilia martiana C.DC.
Microteaceae	Microtea scabrida Urb.	LC
Moraceae	Dorstenia cayapia Vell.	LC
Myrtaceae	Eugenia binata Mazine & Sobral	CR
Myrtaceae	Eugenia delicata T.Fern., M.C.Souza & J.M.A.Braga
Myrtaceae	Eugenia grandifolia O.Berg
Myrtaceae	Eugenia itaguahiensis Nied.	EN
Myrtaceae	Eugenia magnibracteolata Mattos & D.Legrand
Myrtaceae	Eugenia superba T.Fern., M.C.Souza & J.M.A.Braga
Myrtaceae	Eugenia tumescens B.S.Amorim & M.Alves	CR
Myrtaceae	Myrcia gestasiana Cambess.
Myrtaceae	Myrcia rubiginosa Cambess.
Myrtaceae	Myrciaria glomerata O.Berg
Ochnaceae	Ouratea miersii (Planch.) Engl.	EN
Oleaceae	Chionanthus fluminensis (Miers) P.S.Green	CR
Orchidaceae	Cyclopogon bicolor (Ker-Gaw.) Schltr.
Picramniaceae	Picramnia grandifolia Engl.	EN
Piperaceae	Peperomia incana (Haw.) Hook.
Plumbaginaceae	Plumbago auriculata Lam.
Poaceae	Bambusa vulgaris Schrad. ex J.C.Wendl.
Poaceae	Ichnanthus glaber (Raddi) Hitchc.
Polygonaceae	Antigonon leptopus Hook. & Arn.
Pontederiaceae	Heteranthera reniformis Ruiz & Pav.
Pteridaceae	Pteris congesta J.Prado	EN
Pteridaceae	Pteris cretica L.
Pteridaceae	Pteris multifida Poir.
Rubiaceae	Faramea calyciflora A.Rich. ex DC.	CR
Rubiaceae	Psychotria marginata Sw.
Rubiaceae	Psychotria nitidula Cham. & Schltdl.
Sapindaceae	Cardiospermum halicacabum L.
Sapindaceae	Cupania fluminensis Acev.-Rodr.	EN
Sapindaceae	Serjania tenuis Radlk.	VU
Selaginellaceae	Selaginella erythropus (Mart.) Spring
Smilacaceae	Smilax subsessiliflora Duhamel	EN
Solanaceae	Metternichia princeps J.C.Mikan
Velloziaceae	Barbacenia purpurea Hook.
Verbenaceae	Bouchea fluminensis (Vell.) Moldenke	LC

Table 4:
Species present in more than half of the 22 analysed areas. These could be considered generally widespread in the Atlantic Rainforest.

Family	Species
Anacardiaceae	Schinus terebinthifolia Raddi
Anemiaceae	Anemia phyllitidis (L.) Sw.
Annonaceae	Guatteria australis A.St.-Hil.
Apocynaceae	Oxypetalum banksii R.Br. ex Schult.
Apocynaceae	Tabernaemontana laeta Mart.
Asteraceae	Cyrtocymura scorpioides (Lam.) H.Rob.
Blechnaceae	Blechnum occidentale L.
Blechnaceae	Blechnum polypodioides Raddi
Bromeliaceae	Aechmea nudicaulis (L.) Griseb.
Bromeliaceae	Billbergia amoena (Lodd.) Lindl.
Bromeliaceae	Pitcairnia flammea Lindl.
Bromeliaceae	Tillandsia geminiflora Brongn.
Bromeliaceae	Tillandsia stricta Sol.
Bromeliaceae	Tillandsia usneoides (L.) L.
Cactaceae	Pereskia aculeata Mill.
Chloranthaceae	Hedyosmum brasiliense Mart. ex Miq.
Cyperaceae	Scleria latifolia Sw.
Dilleniaceae	Davilla rugosa Poir.
Fabaceae	Dalbergia frutescens (Vell.) Britton
Fabaceae	Desmodium incanum (Sw.) DC.
Fabaceae	Machaerium nyctitans (Vell.) Benth.
Fabaceae	Senna macranthera (DC. ex Collad.) H.S.Irwin & Barneby
Gleicheniaceae	Sticherus bifidus (Willd.) Ching
Lygodiaceae	Lygodium volubile Sw.
Melastomataceae	Clidemia hirta (L.) D.Don
Melastomataceae	Miconia albicans (Sw.) Steud.
Melastomataceae	Miconia latecrenata (DC.) Naudin
Meliaceae	Guarea macrophylla Vahl
Meliaceae	Trichilia elegans A.Juss.
Moraceae	Ficus luschnathiana (Miq.) Miq.
Moraceae	Sorocea bonplandii (Baill.) W.C.Burger et al.
Myrtaceae	Myrcia splendens (Sw.) DC.
Myrtaceae	Myrciaria floribunda (H.West ex Willd.) O.Berg
Myrtaceae	Psidium cattleyanum Sabine
Myrtaceae	Psidium guineense Sw.
Nyctaginaceae	Guapira opposita (Vell.) Reitz
Peraceae	Pera glabrata (Schott) Baill.
Piperaceae	Peperomia corcovadensis Gardner
Piperaceae	Piper arboreum Aubl.
Polygalaceae	Senega paniculata (L.) J.F.B.Pastore & J.R.Abbott
Polypodiaceae	Microgramma vacciniifolia (Langsd. & Fisch.) Copel.
Polypodiaceae	Pleopeltis hirsutissima (Raddi) de la Sota
Polypodiaceae	Serpocaulon catharinae (Langsd. & Fisch.) A.R.Sm.
Primulaceae	Myrsine coriacea (Sw.) R.Br. ex Roem. & Schult.
Pteridaceae	Pteris splendens Kaulf.
Rubiaceae	Borreria verticillata (L.) G.Mey.
Rubiaceae	Psychotria leiocarpa Cham. & Schltdl.
Rubiaceae	Randia armata (Sw.) DC.
Salicaceae	Casearia sylvestris Sw.
Solanaceae	Athenaea fasciculata (Vell.) I.M.C. Rodrigues & Stehmann
Violaceae	Anchietea pyrifolia (Mart.) G.Don

Table 5:
Species that are found exclusively in the botanically similar coastal areas of Parque Natural Municipal de Niterói (PARNIT), Parque Estadual da Costa do Sol (PECS) and Parque Estadual Paulo César Vinha (PEPCV), when compared with all 22 areas analysed.

Family	Species
Amaranthaceae	Blutaparon portulacoides (A.St.-Hil.) Mears
Anacardiaceae	Anacardium occidentale L.
Annonaceae	Annona glabra L.
Arecaceae	Allagoptera arenaria (Gomes) Kuntze
Bromeliaceae	Vriesea neoglutinosa Mez
Cactaceae	Pilosocereus arrabidae (Lem.) Byles & Rowley
Convolvulaceae	Ipomoea imperati (Vahl) Griseb.
Cordiaceae	Varronia curassavica Jacq.
Erythropalaceae	Heisteria perianthomega (Vell.) Sleumer
Fabaceae	Canavalia parviflora Benth.
Fabaceae	Dalbergia ecastaphyllum (L.) Taub.
Fabaceae	Zornia curvata Mohlenbr.
Malpighiaceae	Stigmaphyllon ciliatum (Lam.) A.Juss.
Moraceae	Ficus cyclophylla (Miq.) Miq.
Myrtaceae	Eugenia candolleana DC.
Myrtaceae	Eugenia monosperma Vell.
Ochnaceae	Ouratea cuspidata (A.St.-Hil.) Engl.
Orchidaceae	Vanilla phaeantha Rchb.f.
Poaceae	Paspalum millegrana Schrad. ex Schult.
Polygalaceae	Senega appendiculata (Vell.) J.F.B.Pastore
Portulacaceae	Portulaca mucronata Link
Rubiaceae	Coccocypselum capitatum (Graham) C.B.Costa & Mamede
Rubiaceae	Hexasepalum apiculatum (Willd.) Delprete & J.H.Kirkbr.
Rutaceae	Pilocarpus spicatus A.St.-Hil.
Ximeniaceae	Ximenia americana L.

Discussion

Sampling effort and completeness of inventory

The comprehensive floristic inventory conducted in PARNIT revealed a remarkably rich and distinctive flora for a small urban forest. Although the species accumulation curve for PARNIT has started to slightly level off, it has not yet reached a clear asymptote after 64 field trips (Fig. 2). This suggests that additional species may still be detected with further sampling, although the decreasing slope indicates that we are approaching a more complete inventory. Interestingly, our calculations predicted that 50 (n=49.43) sampling events would be required in order to assess PARNIT’s species richness with the desired precision (Table 1). This discrepancy may arise due to species that are rarely sampled or due to microhabitats that remain under-sampled. The species accumulation curve is presented as a diagnostic of sampling completeness under our survey design, rather than as evidence that the flora has been fully captured. As expected for a spatially discontinuous, heterogeneous urban remnant of a biodiversity hotspot composed of multiple habitat types, the curve does not reach a strict asymptote, indicating that additional sampling is likely to add records-particularly among groups that are typically under-detected in floristic surveys (e.g., canopy species, short-lived herbs, and some epiphytes). Importantly, this pattern does not invalidate the current checklist; instead, it highlights the incremental nature of inventory work in complex mosaics and supports the complementary use of systematic field sampling and historical herbarium records to build the most complete floristic baseline possible.

Regarding the slight disparity between species richness estimators, the lower estimate from Chao is expected, as it is more conservative and primarily considers species detected only once or twice. Jackknife2, in contrast, tends to yield higher estimates as it accounts for species distribution heterogeneity across samples. Notably, however, when data from other time periods and different herbaria are incorporated, the total number of species recorded in PARNIT rises from 436 (collected during our survey) to 707, a number in the range of the estimated richness based on our samples (673-753). This suggests that (i) we are likely close to listing the entire vascular flora of PARNIT, and (ii) while systematic field surveys provide a strong baseline for estimating species richness, historical collections remain essential for capturing the full diversity of vascular plants, particularly those that may be locally rare, seasonal, or previously more abundant in the past. It should be noted that one possible limitation for constructing species accumulation curves and estimating species diversity in our study stems from the sampling method used in our study. Since the walking method only results in the collection of fertile specimens and often species that were already collected are not resampled since it would not add to the species inventory list, our predicting power is likely to be lower than that of a plot-sampling study.

Floristic composition

The floristic data gathered from PARNIT reveal a highly distinctive species pool that underscores its ecological uniqueness and conservation value within the Atlantic Forest biome (Fig. 1). When it comes to species composition, 91 are exclusive to PARNIT and do not occur in any of the other 21 protected areas analyzed (Table 3). Notably, 24 of the 91 species exclusive to PARNIT (26.4%) are officially listed as threatened in at least one of the three national red lists (CNCFlora, 2013; Brasil, 2022), including 12 Endangered (EN), six Critically Endangered (CR), and six Vulnerable (VU) taxa. The remaining species are yet to be evaluated, so this number may be even higher. Additionally, approximately one-fifth of these exclusive species are endemic to the state of Rio de Janeiro, reinforcing the park’s role in safeguarding regional biodiversity. When considering the full floristic inventories of each site, PARNIT harbors a total of 64 threatened species (9.1% of its flora), a proportion higher than that observed in the much larger Reserva do Tinguá (RBT) (5.1%). This pattern reinforces the interpretation that PARNIT functions as an important reservoir of native biodiversity in an urban matrix for rare, narrowly distributed, and ecologically specialized species, despite its smaller area and urban location. It should be noted that species exclusivity is evaluated only within the comparison dataset and should not be interpreted as regional endemism or absence from nearby remnants not included in the compiled catalogues. Furthermore, the presence of exotic cultivated species (Mangifera indica L., Annona muricata L., Agave sisalana Perrine ex Engelm., Sansevieria trifasciata Prain, Spathodea campanulata P.Beauv., Carica papaya L., Kalanchoe crenata (Andrews) Haw., Kalanchoe pinnata (Lam.) Pers., Delonix regia (Bojer ex Hook.) Raf., Plectranthus barbatus Andr., Vitex agnus-castus L., Musa paradisiaca L., Corymbia citriodora (Hook.) K.D.Hill & L.A.S.Johnson) among initial records-subsequently excluded from the final exclusive species list-also reflects the park’s urban setting and past anthropogenic disturbance.

Although not necessarily restricted to the park, several species recorded in PARNIT deserve special attention due to their ecological, biogeographical, or conservation relevance, including taxa from species-rich families such as Myrtaceae. Astronium graveolens occurs at low population densities, while species such as Aspidosperma gomezianum, Connarus nodosus, Ceiba erianthos, Eriotheca pentaphylla, Manilkara subsericea, and Metternichia principis have relatively restricted distributions within the Atlantic Forest. Particularly noteworthy are Annona parviflora and Tabebuia cassinoides, which combine restricted ranges with threatened status. Iconic species such as Paubrasilia echinata and Cariniana legalis are represented by older individuals likely surviving historical logging. Other species contribute to ecosystem functioning in specific ways, such as Joannesia princeps, an important food source for small mammals, and Nectandra oppositifolia, valued for its aromatic bark. Additionally, the park harbors visually striking ornamental trees like Tabernaemontana laeta and Handroanthus chrysotrichus, as well as the endangered Cedrela odorata. Diverse genera are also noteworthy, including seven species of Ficus (Moraceae), eight of Myrcia, and 27 of Eugenia (Myrtaceae).

The floristic composition also reflects the park’s transitional character between different Atlantic Forest formations. According to Oliveira-Filho & Fontes (2000) , several species recorded in PARNIT are characteristic of Seasonal Semideciduous Forests, such as Cecropia glaziovii, Ficus lushmaniana, Hedyosmum brasiliensis, and Handroanthus chrysotrichus. In contrast, others are typically associated with Dense Ombrophilous Forests, including Allophylus petiolatus Radlk., Chrysophyllum flexuosum, Cupania racemosa, Eriotheca pentaphylla, Inga capitata, Ocotea brachybotrya, Pouteria caimito, Pouteria venosa, and Psychotria carthagenensis. This mixture of floristic elements from distinct forest types reinforces the idea that PARNIT represents an ecotonal area, harboring species from multiple phytophysiognomies and contributing to the overall heterogeneity and conservation value of the Atlantic Forest in coastal Rio de Janeiro. Similar ecotonal patterns, where climatic filtering overrides spatial proximity, have been observed across tropical biomes, suggesting convergent processes in vegetation assembly (Pennington et al., 2009). The floristic singularity of PARNIT may also reflect the complex historical assembly of Neotropical tree lineages. As reviewed by Dick & Pennington (2019) , long-term diversification and dispersal processes-such as Boreotropical migrations, long-distance oceanic dispersal, and the Great American Biotic Interchange-have repeatedly shaped the distribution of tropical tree clades. Many dominant Atlantic Forest families (e.g., Fabaceae) include lineages that originated outside South America but later diversified within it, under climatic and edaphic filtering similar to that observed in Amazonian and Andean systems. The coexistence of taxa with both humid and dry affinities in PARNIT may thus represent a local expression of these continental-scale assembly processes, where environmental sorting interacts with deep-time biogeographic legacies to generate high species turnover along short spatial gradients (Dick & Pennington, 2019).

Building on this ecotonal interpretation, it is also important to recognize that much of the flora recorded in PARNIT is shared with other nearby remnants in Niterói and adjacent municipalities. Recent studies conducted within PARNIT itself document substantial overlap in species composition across the park’s mosaic, including inventories from Ilha do Pontal (Santos et al., 2024) and Praia do Sossego (Santos et al., 2025). Likewise, multiple floristic and taxon-focused contributions from the surrounding landscape-particularly the Parque Estadual da Serra da Tiririca (PESET) and coastal environments-reinforce regional continuity of species pools (Barros, 2008; Vasconcelos et al., 2019; Queiroz et al., 2020; Dutra Junior et al., 2024), as do broader datasets from coastal forests and inselberg systems in Niterói that capture similar environmental transitions (Machado et al., 2021a; b). Indeed, several taxa considered exclusive within our dataset have been documented in nearby remnants. Although these works provide critical local context for interpreting compositional similarity, they were not incorporated into our comparative analyses because the inter-area dataset was assembled exclusively from standardized protected-area species catalogues available at the time of data compilation. Future updates to standardized databases integrating these sources will allow even more refined comparisons among adjacent Atlantic Forest remnants. Because PARNIT is a mosaic influenced by urban pressures, its pooled flora likely includes both habitat specialists and disturbance-tolerant generalists; therefore, our regional analyses are interpreted as broad-scale affinities of the Park as a whole rather than as formation-level diagnostics.

Regional comparisons and environmental gradients

Because inventories differ in effort and detectability among growth forms (especially epiphytes, lianas, herbs, and ferns/lycophytes), comparisons should be interpreted as broad-scale compositional affinities rather than exhaustive equivalence among life-form components. Patterns of species turnover across climatic gradients reflect environmental filtering operating at multiple spatial scales, a process widely recognized in tropical forests (Kraft et al., 2014). The multivariate analyses presented here, which considered species lists of other protected areas, further emphasized PARNIT’s floristic uniqueness. In the cluster analysis, the clade that includes PARNIT places it as a sister group to PECS and PEPCV (Parque Estadual da Costa do Sol and Parque Estadual Paulo César Vinha - in Rio de Janeiro and Espírito Santo states, respectively), both of which are classified as restingas, while PECS also has Seasonal Semideciduous Forests (Table 2). PECS is a large but highly fragmented area located in a peculiar region of Rio de Janeiro considered a phytogeographical enclave due to its contrastingly unusual semi-arid climate (Coê & Carvalho, 2013). Although considerably smaller, PEPCV extends along a large portion of Espírito Santo’s coastline and encompasses a wide array of microhabitats. The fact that these three areas, along with MNAIC (Monumento Natural do Arquipélago das Ilhas Cagarras), which is a small archipelago just off the coast of Rio de Janeiro, have clustered together in our analysis highlights the role of environmental factors in structuring plant communities, since the continental areas are very distant geographically. And when we look closely at the 25 species these three continental areas share (Table 5), there are several examples of species adapted to the harsh environments of the coast. This subset likely represents a shared floristic core associated with marginal forest mosaics, consistent with patterns of floristic differentiation along climatic gradients reported by Oliveira-Filho & Fontes (2000) . Although relatively widespread, these taxa may act as indicators of coastal and seasonally dry Atlantic Forest vegetation, characterized by environmental filters such as precipitation seasonality, higher temperatures, salinity, and soil heterogeneity.

In contrast, comparisons with inland ombrophilous forests such as RBT (Reserva Biológica do Tinguá) and seasonal semideciduous forests such as PESC (Parque Estadual da Serra da Concórdia), which are physically much closer, highlight the compositional divergence of PARNIT. Although it shares 223 species with RBT and 54 with PESC, PARNIT retains 461 species that are absent from both, and none of the species exclusive to RBT or PESC are threatened under any of the national conservation assessments. This mixture of floristic elements parallels transitions described in South American seasonally dry tropical forests, where dispersal limitation and historical stability shape distinct metacommunities (Pennington et al., 2009). Such transitions are consistent with large-scale patterns of phylogenetic niche conservatism in tropical biomes, where related lineages retain ancestral climatic affinities (Crisp et al., 2009).

Ultimately, the cluster analysis indicates that our areas can be grouped into three larger clades - one outgroup composed of areas from Cerrado and Seasonal Semideciduous Forests (EEAV, EEA, PEPF), another composed of ombrophilous forests with elevation gradients (which includes RBT and PESC), and a third composed of coastal dry and hot environments, which is where PARNIT is found. These environmental influences were corroborated by the biplot of our Distance-based redundancy analysis. The primary axis (db-RDA1) was strongly correlated with annual mean temperature (bio1), and clearly separated warmer, coastal sites on the positive side-including PARNIT, PEPCV, and PECS-from cooler, inland areas such as RBT, which was positioned on the negative end. This reinforces the interpretation that temperature is a key factor influencing species composition in the Atlantic Forest. The second axis (db-RDA2) was significantly associated with precipitation of the driest month (bio14) and latitude (LAT), revealing a gradient of increasing seasonal dryness along the vertical dimension of the ordination. PARNIT and PECS were closely positioned along this axis, suggesting floristic similarity shaped by analogous climatic regimes. This is particularly meaningful considering that the aforementioned semi-arid conditions in PECS create an exceptionally harsh environment (Coê & Carvalho, 2013). The proximity of PARNIT to PECS in the db-RDA biplot supports the idea that the park may share ecophysiological pressures associated with drought stress, despite being located in a different region and presenting densely covered forested areas.

Thus, our findings highlight the floristic distinctiveness of PARNIT within the Atlantic Forest domain and raise important questions regarding its current phytophysiognomic classification. Although the Brazilian Institute of Geography and Statistics (IBGE, 2012) defines the area as part of the Submontane and Lowland Dense Ombrophilous Forests, our data suggest a stronger floristic similarity with coastal habitats such as restingas and Seasonal Semideciduous Forests. Multivariate analyses grouped PARNIT with distant coastal areas where high annual mean temperature and low precipitation of the driest month are also the main environmental drivers of floristic composition. These results challenge the notion that spatial proximity is the dominant factor shaping floristic similarity across the Atlantic Forest and instead emphasize the role of climatic gradients and edaphic heterogeneity in structuring species assemblages, in agreement with Oliveira-Filho & Fontes (2000) and Scarano (2006) . According to Oliveira-Filho & Fontes (2000), tree species distribution between rain and semideciduous forests in southeastern Brazil should be viewed as a continuum, where floristic differences increase with environmental stress. In this sense, species composition in PARNIT may represent a subset of the Ombrophilous Forest flora, composed of species adapted to higher temperatures and water stress, as observed in other marginal habitats (Le Bagousse-Pinguet et al., 2017; Tomiolo et al., 2020). Our findings reinforce the hypothesis that PARNIT’s flora is more similar to that of warm, seasonally dry coastal forests-such as PECS and PEPCV-than to that of nearby humid ombrophilous forests such as RBT. These results reinforce that PARNIT, like other surrounding remnants, harbors a floristic component that is both unique and complementary within the Atlantic Forest network; a particular transitional floristic assemblage, strongly influenced by environmental filtering. As such, conservation strategies should prioritize this urban remnant not only for its endemic and threatened taxa, but also for its role in capturing the ecological breadth of forest environments shaped by coastal climatic pressures.

Conservation implications and management perspectives

The high number of endemic and threatened species found in PARNIT further underscores its conservation value. Neves et al. (2017) argue that marginal environments - particularly those with high salinity or seasonal drought - host a disproportionate number of endemic species, reinforcing the need to prioritize such areas in conservation planning. The presence of restingas, rocky outcrops, and ecotonal zones within PARNIT likely acts as an environmental filter, selecting for ecophysiologically specialized species, which may partly explain its high rates of endemism and floristic dissimilarity with neighboring sites. Similar observations were made by Machado et al. (2021b) for Leguminosae in the Atlantic Forest, who also noted that floristic compositions in Rio de Janeiro’s coastal regions diverge from the ombrophilous interior. This supports the interpretation that PARNIT's current classification as Dense Ombrophilous Forest might oversimplify its ecological identity, potentially obscuring relevant management and conservation needs. As Scarano (2009) warns, applying uniform classifications to ecologically complex areas can lead to misinformed conservation strategies and inadequate protection measures.

Given the climatic vulnerability of coastal forests (Habel et al., 2019; Chaves et al., 2024) and the fact that their biodiversity may respond strongly to shifts in temperature and precipitation regimes (Davison et al., 2021), long-term ecological monitoring of PARNIT is essential. Management plans should integrate knowledge of local floristic composition, habitat heterogeneity, and species-specific adaptations, rather than relying solely on broad biome-level classifications. Furthermore, urban forests occupying transitional zones may function as local refugia under future drying scenarios, buffering shifts in species distributions along environmental gradients (Toledo et al., 2011).

Collectively, our results reinforce that the Atlantic Forest should be viewed as a biogeographic continuum, shaped by climatic and edaphic filtering that varies regionally in strength and direction (Toledo et al. 2011). The floristic composition of PARNIT, with co-occurring elements of humid and seasonally dry lineages, exemplifies an ecotonal community structured by environmental sorting (Leibold et al., 2004; Kraft et al., 2014). Similar transitions between rainforest and dry-forest floras have been documented throughout tropical South America (Pennington et al., 2009), where dispersal limitation and phylogenetic niche conservatism lead to sharp compositional shifts over small climatic distances (Crisp et al., 2009). PARNIT thus represents a micro-scale expression of these continental processes, showing how urban remnants can preserve evolutionary and ecological signals of broader biogeographic transitions. Recognizing such ecotonal areas within the Atlantic Forest is essential for understanding its internal heterogeneity and for guiding conservation strategies that capture the full range of environmental and phylogenetic diversity.

Supplementary Data

Table S1.

List of Angiosperm Species and Voucher Specimens from the Flora of Parque Natural Municipal de Niterói (PARNIT), Niterói, Rio de Janeiro, Brazil.

Table S2.

List of Ferns and Lycophytes Species and Voucher Specimens from the Flora of Parque Natural Municipal de Niterói (PARNIT), Niterói, Rio de Janeiro, Brazil.

Acknowledgments

Specimen sampling was licensed and supported by Secretaria de Meio Ambiente, Recursos Hídricos e Sustentabilidade - SMARHS.

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Data Availability

All data supporting the findings of this study are available at: https://catalogo-ucs-brasil.jbrj.gov.br/; https://jabot.jbrj.gov.br/v3/consulta.php; https://specieslink.net/search/. Processed datasets and scripts related to this article will be available upon request to the corresponding author.

Funding Information

This study was financed by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro - FAPERJ - Edital No 08/2020 - Programa "Apoio à Conservação da Biodiversidade: Coleções Biológicas do Estado do Rio de Janeiro - 2020” (COLBIO); and received support from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001; and the Programa de Qualificação Institucional PQI-UFF - Edital Nº 02/2019, process n°: 23069.009695/2019-14.

*

Corresponding Author: [e-mail]

Associate Editor:

Vanessa Rezende

Editor-in-Chief:

Thais Elias Almeida

Conflict of Interest

The authors hereby declare that there are no conflicts of interest (personal, scientific, commercial, political, or financial) in the submitted manuscript.

Publication Dates

• Publication in this collection
  21 Aug 2026
• Date of issue
  2026

History

• Received
  15 Oct 2025
• Accepted
  12 May 2026