ROCHA, Lício Mota da; ROSA, Clarissa; SECCO, Helio; LOPES, Edson Varga

Lício Mota da ROCHA ^** Corresponding author: liciorocha@hotmail.com

Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Recursos Naturais da Amazônia, Rua Vera Paz, s/n, Bairro Salé, 68040-225, Santarém, Pará, Brazil

https://orcid.org/0000-0002-6494-8146

Clarissa ROSA

Instituto Nacional de Pesquisas da Amazônia, Coordenação de Biodiversidade, Av. André Araújo 2936, 69011-970, Manaus, AM, Brazil

Helio SECCO

Universidade Federal do Rio de Janeiro (UFRJ), Instituto de Biodiversidade e Sustentabilidade (NUPEM), Av. São José do Barreto 764, Bairro Barreto, 27965-045, Macaé, Rio de Janeiro, Brazil

Edson Varga LOPES

Universidade Federal do Oeste do Pará, Programa de Pós-Graduação em Recursos Naturais da Amazônia, Rua Vera Paz, s/n, Bairro Salé, 68040-225, Santarém, Pará, Brazil

Universidade Federal do Oeste do Pará, Instituto de Biodiversidade e Florestas, Laboratório de Ecologia e Conservação, Rua Vera Paz, s/n, Bairro Salé, 68040-225, Santarém, Pará, Brazil

* Corresponding author: liciorocha@hotmail.com

ASSOCIATE EDITOR:

Paulo Bobrowiec

Figuras (3)
Tabelas (3)

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Figure 1
Location of the 100-km roadkill sampling section on the BR-163 highway along the Tapajós National Forest environmental protection area, in Belterra county, Pará state, Brazil.

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Figure 2
Clustering analysis of wildlife roadkills recorded along a 100-km section of BR-163 highway in Pará state, Brazil from July 2019 to June 2020. A - all vertebrates; B - amphibians; C - mammals; D - reptiles; E - birds. The solid line represents the distribution of observed roadkills and the dotted lines, the 95% confidence interval. Clustering occurs when the L(r) function (continuous line) is above the upper confidence limit. The parameters used were an initial radius of 100 m with a radius increment of 400 m in 1000 simulations.

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Figure 3
Hotspots of total vertebrate (A), amphibian (B) and reptile (C) roadkills along 100 km of the BR-163 highway in Pará, Brazil. The solid line represents the intensity of the roadkills, and the dotted lines, the 95% confidence interval. The points where the black line crosses the upper limit of the confidence interval indicate the occurrence of hotspots.

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Table 1
Number of records of vertebrate roadkills (N) recorded along 100 km of the BR-163 highway (Pará, Brazil) between July 2019 and June 2020. Taxonomy follows the Brazilian Committee of Ornithological Records (CBRO) for birds (Piacentini et al. 2015Piacentini, V.Q.; Aleixo, A.; Agne, C.E.; Maurício, G.N.; Pacheco, J.F.; Bravo, G.A.; et al. 2015. Annotated checklist of the birds of Brazil by the Brazilian Ornithological Records Committee. Revista Brasileira de Ornitologia, 23: 91-298.), the species list of the Brazilian Society of Herpetology (Costa and Bérnils 2018Costa, H.C.; Bérnils, R.S. 2018. Répteis do Brasil e suas unidades federativas: lista de espécies. Herpetologia Brasileira, 7: 11-57.) for reptiles, and the most recently updated and commented survey of mammals occurring in Brazil (Quintela et al. 2020Quintela, F.M.; Rosa, C.A.; Anderson, F. 2020. Updated and annotated checklist of recent mammals from Brazil. Anais da Academia Brasileira de Ciências, 92: e20191004). None of the identified species is listed as endangered by the International Union for Conservation of Nature (IUCN). TA = roadkill rate (ind km^-1 day^-1).

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Table S1
Climatic data used in the multiple linear regression analyses of the effect of temperature and rainfall on wildlife roadkills sampled on 25 days along 100 km of the BR-163 highway from July 2019 to June 2020. Source: National Institute of Meteorology - INMET (2019/2020).

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Table S2
Multiple linear regression models for predicting the degree of dependence of vertebrate roadkill occurrence along 100 km of the BR-163 highway on 25 days between July 2019 and June 2020 on temperature and precipitation on the days prior to sampling. Models were constructed for the overall data (N-total) and for the data separated by class. The climatic variables considered in the models were (1) precipitation on the day before sampling; (2) accumulated precipitation from the seven days before sampling; (3) average temperature from the day before sampling; and (4) accumulated average temperature from the seven days prior to sampling. R2 = adjusted multiple correlation coefficient. Significance level (P-value) at 5% (α = 0.05). P-values in bold indicate statistical significance.

Taxon	Common name	N	TA
AMPHIBIANS
Anura	frog/treefrog	164	0.0656
Total		164	0.0656
REPTILES
Testudines
Testudinidae
Chelonoidis carbonarius (Spix, 1824)	red-footed tortoise	3	0.0012
Squamata
Amphisbaenidae
Amphisbaena fuliginosa Linnaeus, 1758	blind snake/two headed snake	6	0.0024
Boidae
Boa constrictor Linnaeus, 1758	boa constrictor	17	0.0068
Epicrates cenchria (Linnaeus, 1758)	rainbow boa	9	0.0036
Colubridae
Chironius carinatus (Linnaeus, 1758)	vine snake	1	0.0004
Drymarchon corais (Boie, 1827)	indigo snake	1	0.0004
Phrynonax polylepis (Peters, 1867)	northeastern puffing snake	1	0.0004
Spilotes pullatus (Linnaeus, 1758)	tropical chicken snake	1	0.0004
Dipsadidae
Dipsas indica Laurenti, 1768	neotropical snail- eater	1	0.0004
Erythrolamprus aesculapii (Linnaeus, 1758)	South American false coralsnake	1	0.0004
Erythrolamprus reginae (Wagler, 1824 in Spix, 1824)	royal ground sneke	1	0.0004
Imantodes cenchoa (Linnaeus, 1758)	blunthead tree snake	2	0.0008
Oxyrhopus petolarius (Reuss, 1834)	forest flamesnake	5	0.0020
Pseudoboa neuwiedii (Duméril, Bibron e Duméril, 1854)	Neuwied’s false boa	1	0.0004
Pseudoboa sp.		2	0.0008
Viperidae
Bothrops atrox (Linnaeus, 1758)	common lancehead	6	0.0024
Bothrops taeniatus Wagler, 1824 in Spix, 1824	speckled forest pit viper	1	0.0004
Lachesis muta (Linnaeus, 1766)	South American bushmaster	2	0.0008
Unidentified squamate		1	0.0012
Total		62	0.0248
BIRDS
Tinamiformes
Tinamidae
Crypturellus soui (Herman, 1783)	little tinamou	2	0.0008
Podicipediformes
Podicipedidae
Tachybaptus dominicus (Linnaeus, 1766)	least grebe	1	0.0004
Cathartiformes
Cathartidae
Coragyps atratus (Bechstein, 1793)	black vulture	24	0.0096
Cathartes melambrotus Wetmore, 1964	greater yellow-headed vulture	1	0.0004
Gruiformes
Rallidae
Neocrex erythrops (Sclater, 1867)	paint-billed crake	1	0.0004
Columbiformes
Columbidae
Columbina talpacoti (Temmink, 1810)	ruddy ground-dove	3	0.0012
Patagioenas cayennensis (Bonnaterre, 1792)	pale-vented pigeon	1	0.0004
Opisthocomiformes
Opisthocomidae
Opisthocomus hoazin (Müller, 1776)	hoatzin	1	0.0004
Cuculiformes
Cuculidae
Coccyzus melacoryphus (Vieillot, 1817)	dark-billed cuckoo	1	0.0004
Crotophaga ani (Linnaeus, 1758)	smooth-billed ani	3	0.0012
Strigiformes
Strigidae
Megascops choliba (Vieillot, 1817)	tropical screech-owl	1	0.0004
Nyctibiiformes
Nyctibiidae
Nyctibius griseus (Gmelin, 1789)	common potoo	1	0.0004
Caprimulgiformes
Caprimulgidae
Hydropsalis sp		1	0.0004
Nyctidromus albicollis (Gmelin, 1789)	common pauraque	1	0.0004
Caprimulgidae	nightjar	1	0.0004
Falconiformes
Falconidae
Milvago chimachima (Vieillot, 1816)	yellow-headed caracara	2	0.0008
Passeriformes
Icteridae
Sturnella militaris (Linnaeus, 1758)	red-breasted meadowlark	1	0.0004
Thraupidae
Tachyphonus rufus (Boddaert, 1783)	white-lined tanager	1	0.0004
Thraupis episcopus (Linnaeus, 1766)	blue-gray tanager	2	0.0008
Volatinia Jacarina (Linnaeus, 1766)	blue-black grassquit	1	0.0004
Tityridae
Tityra semifasciata (Spix, 1825)	masked tityra	1	0.0004
Tyrannidae
Myiophobus fasciatus (Statius Müller, 1776)	bran-colored flycatcher	1	0.0004
Pitangus sulphuratus (Linnaeus, 1766)	great kiskadee	1	0.0004
Unidentified Passeriformes		2	0.0008
Unidentified birds		4	0.0016
Total		59	0.0236
MAMMALS
Didelphimorfia
Didelphidae
Didelphis marsupialis Linnaeus, 1758	common opossum	8	0.0032
Didelphis sp	opossum	1	0.0004
Cingulata
Dasypodidae
Dasypus (Dasypus) novemcinctus Linnaeus, 1758	nine-banded armadillo	3	0.0012
Cabassous unicinctus Linnaeus, 1758	southern naked-tailed armadillo	1	0.0004
Pilosa
Myrmecophagidae
Tamandua tetradactyla (Linnaeus, 1758)	collared anteater	20	0.0080
Primata
Callitrichidae
Mico argentatus (Linnaeus, 1771)	silvery marmoset	4	0.0016
Rodentia
Echimyidae
Proechimys sp.	Tome’s spiny-rat	1	0.0004
Rodentia	rodent	2	0.0008
Chiroptera
Phyllostomidae
Artibeus (Artibeus) lituratus (Olfers, 1818)	great fruit-eating bat	1	0.0004
Carollia perspicillata (Linnaeus, 1758)	Seba’s short-tailed bat	1	0.0004
Carnivora
Canidea
Cerdocyon thous (Linnaeus, 1766)	crab-eating fox	8	0.0032
Procyonidae
Nasua nasua (Linnaeus, 1766)	South American coati	5	0.0020
Unidentified mammals		11	0.0044
Total taxa		66	0.0264
Total individuals		351	0.1404

Month/Year	Sample	Precipitation previous day (mm)	Accumulated precipitation previous 7 days (mm)	Average temperature previous day (ºC)	Average temperature previous 7 days (ºC)
Jul/2019	1	0.00	14.70	26.90	28.00
Jul/2019	2	0.00	7.50	27.43	27.89
Aug/2019	3	3.50	37.50	27.06	27.28
Aug/2019	4	0.00	15.90	28.67	27.86
Sep/2019	5	0.00	0.00	28.77	27.47
Sep/2019	6	0.00	1.00	29.30	29.17
Oct/2019	7	0.00	27.90	28.93	27.99
Oct/2019	8	5.60	5.60	28.03	28.55
Oct/2019	9	0.00	0.00	28.27	27.05
Nov/2019	10	0.00	7.60	29.13	28.23
Nov/2019	11	0.00	1.60	28.03	27.64
Dec/2019	12	0.00	39.10	28.23	27.83
Dec/2019	13	0.00	8.00	27.63	27.91
Jan/2020	14	0.00	108.80	27.30	26.32
Jan/2020	15	0.00	12.20	26.53	27.07
Feb/2020	16	31.70	72.30	26.90	26.96
Feb/2020	17	10.30	69.40	27.10	26.72
Mar/2020	18	0.00	43.60	26.13	26.38
Mar/2020	19	0.00	107.40	26.97	26.96
Apr/2020	20	1.30	43.60	25.93	27.58
Apr/2020	21	8.40	142.80	24.97	26.13
Mai/2020	22	13.30	60.10	27.47	26.78
Mai/2020	23	0.00	73.50	26.73	26.42
Jun/2020	24	0.00	39.20	28.10	27.10
Jun/2020	25	7.80	29.40	27.20	27.68

Variable	Coefficient	Standard error	Statistics t	P-value	R²
N-total (model 1)					0.3917
Precipitation from the day before (mm)	0.40907	0.22638	1.807	0.08446
Accumulated precipitation (mm)	0.11981	0.04125	2.905	0.00822
N-total (model 2)					0.4274
Precipitation from the day before (mm)	0.4513	0.2140	2.109	0.04654
Temperature from the day before (ºC)	-4.5989	1.4307	-3.214	0.00399
N-total (model 3)					0.3462
Precipitation from the day before (mm)	0.4955	0.2272	2.181	0.0402
Accumulated temperature (ºC)	-5.4225	2.1572	-2.514	0.0198
N-total (model 4)					0.3368
Temperature from the day before (ºC)	-4.186	2.001	-2.092	0.04820
Accumulated temperature (ºC)	-2.600	2.841	-0.915	0.36999
Amphibian (model 1)					0.3438
Precipitation from the day before (mm)	0.44714	0.21990	2.033	0.0548
Accumulated precipitation (mm)	0.06359	0.05744	1.107	0.2808
Accumulated temperature (ºC)	-2.26010	2.89751	-0.780	0.4441
Amphibian (model 2)					0.3555
Precipitation from the day before (mm)	0.44512	0.21792	2.043	0.0533
Accumulated precipitation (mm)	0.09569	0.03970	2.410	0.0248
Amphibian (model 3)					0.3334
Precipitation from the day before (mm)	0.4983	0.2159	2.308	0.0308
Temperature from the day before (ºC)	-3.1911	1.4436	-2.211	0.0378
Amphibian (model 4)					0.3371
Precipitation from the day before (mm)	0.5082	0.2140	2.375	0.0267
Accumulated temperature (ºC)	-4.5587	2.0313	- -2.244	0.0352
Reptile (model 1)					0.211
Precipitation from the day before (mm)	0.05595	0.05816	0.962	0.3465
Accumulated precipitation (mm)	0.02366	0.01060	2.233	0.0361
Reptile (model 2)					0.2547
Precipitation from the day before (mm)	0.06285	0.05506	1.141	0.2660
Temperature from the day before (ºC)	-0.94370	0.36820	-2.563	0.0177

[1] * Corresponding author: liciorocha@hotmail.com

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Hotspots and hotmoments of wildlife roadkills along a main highway in a high biodiversity area in Brazilian Amazonia

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